Denser.ai vs Stonly

Make an informed decision with our comprehensive comparison. Discover which RAG solution perfectly fits your needs.

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Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare Denser.ai and Stonly across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

When choosing between Denser.ai and Stonly, understanding their unique strengths and architectural differences is crucial for making an informed decision. Both platforms serve the RAG (Retrieval-Augmented Generation) space but cater to different use cases and organizational needs.

Quick Decision Guide

  • Choose Denser.ai if: you value state-of-the-art hybrid retrieval (75.33 ndcg@10) outperforms pure vector search with published benchmarks
  • Choose Stonly if: you value exceptional ease of use - 4.8/5 g2 rating with intuitive visual editor praised in 32 reviews

About Denser.ai

Denser.ai Landing Page Screenshot

Denser.ai is open-source hybrid rag with state-of-the-art retrieval architecture. Denser.ai is a developer-focused RAG platform built by former Amazon Kendra principal scientist Zhiheng Huang, combining open-source retrieval technology with no-code deployment. Its hybrid architecture fuses Elasticsearch, Milvus vector search, and XGBoost ML reranking to achieve 75.33 NDCG@10 (vs 73.16 for pure vector search) and 96.50% Recall@20 on benchmarks. Trade-offs: no SOC2/HIPAA certifications, limited native integrations, ~4-person team size impacts enterprise support. Founded in 2023, headquartered in Silicon Valley, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
88/100
Starting Price
$19/mo

About Stonly

Stonly Landing Page Screenshot

Stonly is interactive knowledge base platform with enterprise ai-powered answers. Stonly is a customer support knowledge management platform with embedded AI capabilities focused on interactive step-by-step guides and help desk agent assistance. Its AI Answers feature (Enterprise-only add-on) achieves 71% self-serve success rates, but it's fundamentally a knowledge base platform with AI features—not a pure RAG-as-a-Service solution. Founded in 2017, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
96/100
Starting Price
$249/mo

Key Differences at a Glance

In terms of user ratings, Stonly in overall satisfaction. From a cost perspective, Denser.ai starts at a lower price point. The platforms also differ in their primary focus: RAG Platform versus Knowledge Management. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

We'll analyze features, pricing, performance benchmarks, security compliance, integration capabilities, and real-world use cases to help you determine which platform best fits your organization's needs. All data is independently verified from official documentation and third-party review platforms.

Detailed Feature Comparison

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Denser.ai
logo of stonly
Stonly
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CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
  • Document formats: PDFs, Word (.docx), PowerPoint (.pptx), CSV, TXT, HTML
  • Website crawling: Full domain ingestion of "hundreds of thousands of web pages" in under 5 minutes
  • Processing scale: "Tens of billions of words" claimed
  • Google Drive: Native integration with real-time sync
  • SQL databases: MySQL, PostgreSQL, Oracle, SQL Server, AWS RDS, Azure SQL Database, Google Cloud SQL
  • Natural language to SQL: Ask questions, get answers directly from database queries
  • Note: YouTube transcripts: Via Zapier workflows only (no native support)
  • Note: Dropbox, Notion, OneDrive: Requires Zapier middleware (no native integration)
  • File limits: 5MB on free tier
  • Knowledge updates: Manual - users add/remove documents as needed
  • Note: No automated scheduled retraining documented
  • Async building via SageMaker enables batch ingestion workflows
  • PDF uploads confirmed
  • Public website crawling: Pages not requiring authentication
  • Zendesk help center content indexing
  • Proprietary interactive guide format as primary content model
  • Note: No Google Drive, Dropbox, Notion, or SharePoint integrations for data ingestion
  • Note: No YouTube transcript extraction (videos can be embedded but not processed)
  • Note: No direct Word document (.docx) or HTML file imports confirmed
  • Note: No automatic content syncing from external sources - updates are manual through Stonly's visual editor
  • Content limits by tier: Basic (5 guides, 400 views/mo), Small Business (unlimited guides, 4K views/mo), Enterprise (custom)
  • Content versioning: Side-by-side comparison and instant restore on Business and Enterprise plans
  • Lets you ingest more than 1,400 file formats—PDF, DOCX, TXT, Markdown, HTML, and many more—via simple drag-and-drop or API.
  • Crawls entire sites through sitemaps and URLs, automatically indexing public help-desk articles, FAQs, and docs.
  • Turns multimedia into text on the fly: YouTube videos, podcasts, and other media are auto-transcribed with built-in OCR and speech-to-text. View Transcription Guide
  • Connects to Google Drive, SharePoint, Notion, Confluence, HubSpot, and more through API connectors or Zapier. See Zapier Connectors
  • Supports both manual uploads and auto-sync retraining, so your knowledge base always stays up to date.
Hybrid Retrieval Architecture ( Core Differentiator)
  • Three-component system: Elasticsearch + Milvus + XGBoost ML reranking
  • Elasticsearch: Keyword-based searches for precise term matching
  • Milvus vector database: Semantic similarity search using dense embeddings
  • XGBoost machine learning: Gradient boosting fuses results with BERT-style reranker
  • Architecture notation: ES+VS+RR_n in documentation
  • 75.33 NDCG@10 on MTEB benchmarks vs 73.16 for pure vector search
  • 96.50% Recall@20 on Anthropic Contextual Retrieval benchmark (vs 90.06% baseline)
  • Embedding models: snowflake-arctic-embed-m (MTEB leaderboard leader), bge-en-icl (open-source), voyage-2 (paid), OpenAI text-embedding-3-large
  • Rerankers: jinaai/jina-reranker-v2-base-multilingual, BAAI/bge-reranker-base (free, open-source)
  • Key finding: Open-source models match or exceed paid alternatives
N/A
N/A
Performance & Accuracy
  • 98.3% response accuracy claimed
  • 1.2-second average response time
  • Hallucination prevention: Source citation with visual PDF highlighting
  • Every response references specific passages from source documents
  • PDFs show highlighted source text for verification
  • Note: No published uptime SLA
  • 71% self-serve success rate with AI Answers feature (company data)
  • 70-76% support ticket reduction documented in case studies
  • 99.9% uptime claimed but no published SLA details or response time data
  • Note: No published latency metrics or performance benchmarks
  • Note: No real-time analytics - Flow reports update every 15 minutes
  • Hallucination controls: Strong grounding in structured content reduces off-topic responses
  • Widget lazy loading: Minimizes impact on host website performance
  • Delivers sub-second replies with an optimized pipeline—efficient vector search, smart chunking, and caching.
  • Independent tests rate median answer accuracy at 5/5—outpacing many alternatives. Benchmark Results
  • Always cites sources so users can verify facts on the spot.
  • Maintains speed and accuracy even for massive knowledge bases with tens of millions of words.
Developer Experience ( A P I & S D Ks)
  • REST API + GraphQL API with Bearer token authentication
  • Simple query pattern: JSON request with query, chatbot_id, k (passages to return)
  • Response format: Scored passages with source metadata (page_content, score, source, title, pid)
  • denser-retriever: MIT-licensed Python package for self-hosting
  • Docker Compose setup: Full stack with Elasticsearch and Milvus containers
  • Installation: Poetry or pip from GitHub
  • Additional repos: denser-chat (PDF chatbot, Python 3.11+), denser-agent (MCP-based multi-agent)
  • GitHub stats: 261 stars, 30 forks, MIT license
  • Testing: pytest, Ruff formatting, contribution guidelines
  • Note: Self-hosted setup "not suitable for production" - data persistence and secrets management require additional config
  • Documentation: Adequate but fragmented across docs.denser.ai, retriever.denser.ai, GitHub
  • Rate limits: 200 API calls/month on free retriever tier
  • REST API: Supports user provisioning, content management, widget control
  • Mobile SDKs (Enterprise only): iOS, Android, React Native, Flutter
  • Note: No Python SDK or server-side Node.js SDK
  • Note: No GraphQL API or OpenAPI/Swagger specification
  • Note: Rate limits not publicly documented
  • Note: No API Explorer, sandbox environment, or Postman collections
  • Note: REST API versioning strategy unclear
  • Widget API: Programmatic control including opening specific content, listening for events, user identification
  • CSP whitelisting: Instructions documented for Content Security Policy compliance
  • Widget versioning documented
  • Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat. API Documentation
  • Offers open-source SDKs—like the Python customgpt-client—plus Postman collections to speed integration. Open-Source SDK
  • Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
L L M Model Options
  • Supported LLMs: GPT-4o, GPT-4o mini, GPT-3.5, Claude
  • Configuration: Via environment variables
  • API keys: Users set OpenAI or Claude keys (only one required)
  • Note: No custom model fine-tuning documented
  • Note: No private model hosting documented
  • Embedding flexibility: Multiple options from open-source to paid providers
  • Reranker flexibility: Multiple free open-source options
  • Note: Undisclosed proprietary LLM - Stonly does not disclose the specific model powering AI Answers
  • Note: No model selection - users cannot choose between GPT-3.5, GPT-4, Claude, or other models
  • Note: No temperature controls, fine-tuning, or model routing
  • AI Profiles: Up to 20 per team for tone and behavior customization
  • Custom Instructions: Up to 100 per team defining boundaries and style
  • Guided AI Answers: Define specific questions that trigger predetermined answers, bypassing AI generation for sensitive scenarios
  • Automatic fallback: When AI confidence is low, system falls back to ML-powered search rather than forcing an answer
  • Knowledge-grounded approach: AI responses anchored in Stonly guides, external websites, and selected PDFs to reduce hallucinations
  • Taps into top models—OpenAI’s GPT-5.1 series, GPT-4 series, and even Anthropic’s Claude for enterprise needs (4.5 opus and sonnet, etc ).
  • Automatically balances cost and performance by picking the right model for each request. Model Selection Details
  • Uses proprietary prompt engineering and retrieval tweaks to return high-quality, citation-backed answers.
  • Handles all model management behind the scenes—no extra API keys or fine-tuning steps for you.
Integrations & Channels
  • Website deployment: JavaScript widget embed, iFrame snippet, REST API
  • Widget installation: Single line of code
  • WordPress: Official plugin with page-specific targeting
  • Telegram: Direct BotFather API integration
  • Zapier: 6,000+ apps with triggers for lead forms and processed questions
  • Website platforms: Custom sites, Shopify, Webflow, Squarespace
  • No Slack: Zapier workflow only (no native integration)
  • Note: WhatsApp: Zapier/API middleware (partial support)
  • No Microsoft Teams: Not available
  • No Discord: Not available
  • CRM sync: HubSpot, Salesforce, Zendesk via Zapier (no native direct integrations)
  • Deep help desk integrations: Zendesk, Salesforce Service Cloud, Freshdesk, ServiceNow
  • Zendesk features: Update tickets from guides, preserve guide progress in tickets, launch Zendesk Chat from widget
  • Zapier integration: Webhook triggers for form submissions and guide completions
  • Analytics integrations: Segment, Google Analytics
  • Embedding options: JavaScript widget, iframe, API deployment
  • Note: No native Slack, WhatsApp, Telegram, or Microsoft Teams integrations (confirmed by multiple user reviews)
  • Note: No omnichannel messaging support
  • Website embedding: All plans support JS widget and iframe embedding
  • Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
  • Offers ready-made hooks for Slack, Zendesk, Confluence, YouTube, Sharepoint, 100+ more. Explore API Integrations
  • Connects with 5,000+ apps via Zapier and webhooks to automate your workflows.
  • Supports secure deployments with domain allowlisting and a ChatGPT Plugin for private use cases.
  • Hosted CustomGPT.ai offers hosted MCP Server with support for Claude Web, Claude Desktop, Cursor, ChatGPT, Windsurf, Trae, etc. Read more here.
  • Supports OpenAI API Endpoint compatibility. Read more here.
Customization & Branding
  • Visual customization: Drag-and-drop builder for theme colors, logos, button sizing
  • Message bubble styling, welcome messages, suggested questions
  • Custom domains: Available on paid tiers for white-labeling
  • Domain restrictions: Limit chatbot deployment to specific pages via page IDs
  • Full palette color selection
  • Logo upload and positioning controls
  • Visual editor: Intuitive no-code interface for creating guides, decision trees, checklists, forms
  • CSS customization: Available on all paid plans
  • White-labeling: Enterprise plan only - complete branding removal
  • Pre-built templates: Common support scenarios covered
  • Role-based access control: Advanced permissions on Enterprise plan
  • Learning curve: Described as "small" - users can create guides in under 30 minutes
  • Note: No formal content approval workflows documented
  • Note: Cannot edit guides on mobile devices
  • Note: Angular framework compatibility issues reported - "Stonly onboarding will work randomly" with dynamic code
  • Fully white-labels the widget—colors, logos, icons, CSS, everything can match your brand. White-label Options
  • Provides a no-code dashboard to set welcome messages, bot names, and visual themes.
  • Lets you shape the AI’s persona and tone using pre-prompts and system instructions.
  • Uses domain allowlisting to ensure the chatbot appears only on approved sites.
No- Code Interface & Usability
  • Visual builder: Drag-and-drop builder for theme customization, logo uploads, button sizing without coding requirements; visual interface for chatbot configuration and deployment
  • Setup complexity: Single line of code JavaScript widget embed for website deployment; WordPress official plugin with page-specific targeting for no-code installation; iFrame snippet option for simplified embedding
  • Learning curve: Technical documentation requires developer familiarity with REST/GraphQL APIs, Docker Compose for self-hosting; docs.denser.ai, retriever.denser.ai, GitHub READMEs provide adequate but fragmented documentation across multiple sites
  • Pre-built templates: GitHub template repository (denser-retriever) provides MIT-licensed starting point; Docker Compose setup with Elasticsearch and Milvus containers for full stack deployment; no visual flow builder or conversation templates documented
  • No-code workflows: Zapier integration (6,000+ apps) with triggers for lead forms and processed questions; Telegram BotFather API integration for messaging deployment; CRM sync (HubSpot, Salesforce, Zendesk) via Zapier workflows only (no native integrations)
  • User experience: Focus on technical users and developers prioritizing retrieval accuracy and open-source validation; ~4-person team impacts enterprise support capacity; priority support on Business plan and above, dedicated support on Enterprise plan
  • Target audience: Developers and technical teams building AI chatbots without strict compliance requirements vs non-technical business users; open-source transparency appeals to teams requiring validation of RAG architecture claims
  • LIMITATION: Self-hosted setup "not suitable for production" - data persistence and secrets management require additional configuration; Denser recommends managed SaaS for production deployments despite MIT-licensed open-source components
  • 4.8/5 ease of use rating on G2
  • "Ease of use" mentioned 32 times in G2 reviews
  • Visual drag-and-drop editor requires no coding
  • Small learning curve - non-technical teams productive quickly
  • Guide creation in under 30 minutes reported by users
  • Pre-built templates for common scenarios
  • Intuitive interface for support teams
  • Note: Some navigation confusion reported in admin interface
  • Note: Cannot edit on mobile devices
  • Offers a wizard-style web dashboard so non-devs can upload content, brand the widget, and monitor performance.
  • Supports drag-and-drop uploads, visual theme editing, and in-browser chatbot testing. User Experience Review
  • Uses role-based access so business users and devs can collaborate smoothly.
Lead Capture & Marketing
  • Deeply integrated lead capture with configurable form fields
  • Form fields: Name, email, company, role, phone
  • Conversation-triggered forms
  • AI qualification follow-ups
  • Automatic CRM sync (via Zapier)
  • Analytics dashboard: Lead quality, satisfaction scores, conversion trends
  • 24.8% conversion rate claimed on homepage
N/A
N/A
Multi- Language & Localization
  • 80+ languages supported
  • Automatic language detection for global deployments
  • Multilingual rerankers available (jinaai/jina-reranker-v2-base-multilingual)
N/A
N/A
Conversation Management
  • Conversation history retention: 30 days (Starter), 90 days (Standard), 360 days (Business)
  • Human handoff: Triggers when chatbot detects query complexity beyond scope
  • Escalation workflows
  • Zendesk ticket creation for human handoff
N/A
N/A
Observability & Monitoring
  • Conversation logs: Configurable retention by tier
  • User engagement tracking: Common queries, conversation length, drop-off points
  • Response accuracy metrics
  • Lead management dashboard
  • Customizable date ranges
  • Aggregated FAQ analysis for knowledge base optimization
  • Note: No A/B testing capability
  • Note: No third-party BI integration (Tableau, PowerBI)
  • Note: No real-time alerting
  • Note: No documented response time SLA tracking
  • Insights Dashboard: Guide views, unique visitors, bounce rates, step-by-step progression, drop-off analysis
  • NPS surveys: All plans
  • CSAT and CES surveys: Enterprise only
  • Flow reports: Update every 15 minutes (not real-time)
  • Data export: Integration with Segment, Zapier, Google Analytics
  • Note: No real-time visitor tracking
  • Note: No predictive analytics
  • Note: Basic compared to dedicated product analytics tools
  • Note: No heatmaps or A/B testing capabilities
  • Agent performance tracking: Relies on external help desk platform integration rather than native dashboards
  • Comes with a real-time analytics dashboard tracking query volumes, token usage, and indexing status.
  • Lets you export logs and metrics via API to plug into third-party monitoring or BI tools. Analytics API
  • Provides detailed insights for troubleshooting and ongoing optimization.
S Q L Database Chat ( Unique Feature)
  • Direct SQL database connectivity for conversational business intelligence
  • Supported databases: MySQL, PostgreSQL, Oracle, SQL Server
  • Cloud databases: AWS RDS, Azure SQL Database, Google Cloud SQL
  • Natural language to SQL queries
  • Ask questions, receive answers from database queries
  • AES-256 encryption for database connections
  • Read-only database access requirements for security
N/A
N/A
Pricing & Scalability
  • Free: $0 - 1 chatbot, 20 queries/month, 5MB file limit, 200 API calls/month (retriever)
  • Starter: $19-29/month - 2 chatbots, 1,500 queries/month, REST API, 30-day logs
  • Standard: $89-119/month - 4 chatbots, 7,500 queries/month, 2,000 documents, 90-day logs, custom domain
  • Business: $399-799/month - 8 chatbots, 15,000 queries/month, extended storage, 360-day logs, priority support
  • Enterprise: Custom - Private cloud, dedicated support, custom SLAs, AWS Marketplace available
  • Annual billing: 20% discount
  • Note: User reviews note: "Plans are quite restrictive, credit limits reached quite sooner for easier tasks"
  • Pricing inconsistency across sources suggests recent changes or regional variations
  • Basic (Free): 5 guides, 400 views/month, 1 seat, single language
  • Small Business ($249/mo, $199/mo annual): Unlimited guides, 4,000 views/month, 5 seats, 3 knowledge bases, CSS customization, Zapier, NPS surveys
  • Enterprise (Custom, ~$39K/year avg): Custom views, unlimited seats, AI Answers add-on, Mobile SDKs, SAML SSO, white-label, auto-translation, CSAT/CES surveys
  • Overage pricing escalates quickly: +15K views = $200/month, +30K views = $400/month
  • Automatic tier upgrades: Exceeding limits for 2 consecutive months triggers upgrade
  • Note: AI Answers, Mobile SDK, SAML SSO, white-labeling all Enterprise-gated
  • Average enterprise contract: ~$39,000 annually according to Vendr procurement data
  • Runs on straightforward subscriptions: Standard (~$99/mo), Premium (~$449/mo), and customizable Enterprise plans.
  • Gives generous limits—Standard covers up to 60 million words per bot, Premium up to 300 million—all at flat monthly rates. View Pricing
  • Handles scaling for you: the managed cloud infra auto-scales with demand, keeping things fast and available.
Security & Privacy
  • Note: NO SOC 2 certification
  • Note: NO HIPAA certification
  • Note: NO ISO 27001 certification
  • Note: NO GDPR documentation
  • Private cloud deployments for enterprise customers
  • AES-256 encryption for database connections
  • Read-only database access requirements for SQL integrations
  • Role-based access controls (mentioned but not detailed)
  • Data deletion capability under user control
  • AWS infrastructure for data storage
  • Carahsoft partnership: Government sector outreach with "Secure, Compliant, and Verifiable AI Chatbots" webinar
  • Note: Certification efforts may be underway (suggested by government webinar)
  • Yes SOC 2 Type 2
  • Yes GDPR compliant
  • Yes HIPAA compliant
  • Yes ISO 27001
  • Yes PCI compliant
  • Yes CSA Star Level 1
  • Trust Center: trust.stonly.com with security documentation, subprocessor lists, controls information
  • SAML 2.0 SSO: Enterprise plan
  • IP allowlisting: Enterprise plan
  • Advanced RBAC: Enterprise plan
  • Two-factor authentication: SMS, email, hardware tokens, TOTP, U2F
  • Note: Data residency options not documented
  • Note: No explicit documentation on customer data usage for AI model training
  • International data transfers: Standard Contractual Clauses for EU compliance
  • Protects data in transit with SSL/TLS and at rest with 256-bit AES encryption.
  • Holds SOC 2 Type II certification and complies with GDPR, so your data stays isolated and private. Security Certifications
  • Offers fine-grained access controls—RBAC, two-factor auth, and SSO integration—so only the right people get in.
Open- Source Components
  • denser-retriever: MIT-licensed, 261 GitHub stars, 30 forks
  • Full transparency into RAG architecture vs commercial black-box competitors
  • Docker Compose deployment for local experimentation
  • Test different embedding and reranker models
  • Validate benchmark claims against own data
  • Customize chunking strategies and retrieval parameters
  • pytest testing, Ruff formatting, contribution guidelines
  • Note: Self-hosted setup "not suitable for production" - data persistence and secrets management issues
  • Denser recommends managed SaaS for production deployments
N/A
N/A
Support & Ecosystem
  • Documentation: docs.denser.ai, retriever.denser.ai, GitHub READMEs
  • Note: Documentation fragmented across multiple sites
  • ~4-person team impacts enterprise support capacity
  • Priority support: Business plan and above
  • Dedicated support: Enterprise plan
  • AWS Marketplace: Available for procurement through existing cloud contracts
  • 4.8/5 G2 rating (132 reviews)
  • Ease of use praised in 32 G2 reviews
  • Help Center documentation
  • Email and chat support
  • Dedicated support: Enterprise plan
  • Learning resources: Pre-built templates, tutorials
  • Quick onboarding: Users report creating guides in under 30 minutes
  • Supplies rich docs, tutorials, cookbooks, and FAQs to get you started fast. Developer Docs
  • Offers quick email and in-app chat support—Premium and Enterprise plans add dedicated managers and faster SLAs. Enterprise Solutions
  • Benefits from an active user community plus integrations through Zapier and GitHub resources.
Company Background
  • Founded 2023 in Silicon Valley
  • ~4 employees (small team)
  • Appears bootstrapped - no disclosed VC funding
  • Founder Zhiheng Huang: Former Amazon Kendra principal scientist
  • Amazon Q development lead at AWS
  • 70+ research papers, 14,000+ citations
  • BLSTM-CRF paper: 5,400+ citations alone
  • Deep expertise in neural information retrieval
N/A
N/A
R A G-as-a- Service Assessment
  • Yes TRUE RAG PLATFORM - sophisticated hybrid retrieval with open-source transparency
  • Data source flexibility: Good (documents, websites, Google Drive, SQL databases)
  • LLM model options: Good (GPT-4o, Claude, multiple embeddings/rerankers)
  • API-first architecture: Good (REST + GraphQL APIs)
  • Open-source transparency: Excellent (MIT-licensed core components)
  • Performance benchmarks: Excellent (published MTEB, Anthropic benchmarks)
  • Compliance & certifications: Poor (no SOC 2, HIPAA, ISO 27001)
  • Native integrations: Weak (heavy Zapier dependency)
  • Best for: Technical teams prioritizing retrieval accuracy and open-source validation
  • Not ideal for: Regulated industries, enterprises requiring certifications, teams needing native Teams/Slack
  • Note: NOT a RAG-as-a-Service platform - fundamentally a knowledge base tool with embedded AI
  • Data source flexibility: Limited (PDF, public web, Zendesk only) vs comprehensive RAG platforms
  • LLM model options: None (undisclosed proprietary model, no user selection)
  • API-first architecture: Weak (widget-focused, limited SDKs, no server-side SDKs)
  • Performance benchmarks: Not published
  • Self-service AI pricing: Not available (Enterprise-gated, ~$39K/year)
  • Help desk integration depth: Excellent (best-in-class Zendesk, Salesforce, Freshdesk)
  • Hallucination controls: Strong (grounded in structured content)
  • Best for: Customer support ticket deflection, not flexible RAG backends
  • Not ideal for: Developers seeking pure RAG API, multi-tenant SaaS RAG backends, use cases needing model selection/fine-tuning
  • Platform Type: TRUE RAG-AS-A-SERVICE PLATFORM - all-in-one managed solution combining developer APIs with no-code deployment capabilities
  • Core Architecture: Serverless RAG infrastructure with automatic embedding generation, vector search optimization, and LLM orchestration fully managed behind API endpoints
  • API-First Design: Comprehensive REST API with well-documented endpoints for creating agents, managing projects, ingesting data (1,400+ formats), and querying chat API Documentation
  • Developer Experience: Open-source Python SDK (customgpt-client), Postman collections, OpenAI API endpoint compatibility, and extensive cookbooks for rapid integration
  • No-Code Alternative: Wizard-style web dashboard enables non-developers to upload content, brand widgets, and deploy chatbots without touching code
  • Hybrid Target Market: Serves both developer teams wanting robust APIs AND business users seeking no-code RAG deployment - unique positioning vs pure API platforms (Cohere) or pure no-code tools (Jotform)
  • RAG Technology Leadership: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, proprietary anti-hallucination mechanisms, and citation-backed responses Benchmark Details
  • Deployment Flexibility: Cloud-hosted SaaS with auto-scaling, API integrations, embedded chat widgets, ChatGPT Plugin support, and hosted MCP Server for Claude/Cursor/ChatGPT
  • Enterprise Readiness: SOC 2 Type II + GDPR compliance, full white-labeling, domain allowlisting, RBAC with 2FA/SSO, and flat-rate pricing without per-query charges
  • Use Case Fit: Ideal for organizations needing both rapid no-code deployment AND robust API capabilities, teams handling diverse content types (1,400+ formats, multimedia transcription), and businesses requiring production-ready RAG without building ML infrastructure from scratch
  • Competitive Positioning: Bridges the gap between developer-first platforms (Cohere, Deepset) requiring heavy coding and no-code chatbot builders (Jotform, Kommunicate) lacking API depth - offers best of both worlds
Competitive Positioning
  • vs CustomGPT: Superior retrieval architecture transparency, SQL database chat; gaps in compliance, native integrations
  • vs Glean: Open-source vs proprietary, lower cost, but lacks permissions-aware AI and enterprise support
  • vs Zendesk: Pure RAG platform vs customer service platform
  • Unique strengths: Hybrid retrieval benchmarks, open-source validation, SQL chat, founder pedigree
  • Key trade-offs: Technical sophistication vs enterprise certifications, innovation vs scaling constraints
  • ~4-person team: Agility in technical innovation, potential scaling constraints for enterprise SLAs
  • Target audience: Developers and technical teams building AI chatbots without strict compliance requirements
  • Unique strength: Interactive guide format for structured support content
  • vs CustomGPT: Not comparable - different product categories (knowledge base vs RAG-as-a-Service)
  • vs Zendesk: Lighter-weight alternative focused on self-service guides vs full customer service platform
  • vs traditional chatbots: Interactive guides provide structured paths vs free-form conversation
  • Target audience: Support teams using Zendesk/Salesforce, not developers building RAG applications
  • 70-76% ticket reduction documented in case studies
  • 71% self-serve success rate with AI Answers
  • Enterprise compliance suitable for regulated industries
  • Market position: Leading all-in-one RAG platform balancing enterprise-grade accuracy with developer-friendly APIs and no-code usability for rapid deployment
  • Target customers: Mid-market to enterprise organizations needing production-ready AI assistants, development teams wanting robust APIs without building RAG infrastructure, and businesses requiring 1,400+ file format support with auto-transcription (YouTube, podcasts)
  • Key competitors: OpenAI Assistants API, Botsonic, Chatbase.co, Azure AI, and custom RAG implementations using LangChain
  • Competitive advantages: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, SOC 2 Type II + GDPR compliance, full white-labeling included, OpenAI API endpoint compatibility, hosted MCP Server support (Claude, Cursor, ChatGPT), generous data limits (60M words Standard, 300M Premium), and flat monthly pricing without per-query charges
  • Pricing advantage: Transparent flat-rate pricing at $99/month (Standard) and $449/month (Premium) with generous included limits; no hidden costs for API access, branding removal, or basic features; best value for teams needing both no-code dashboard and developer APIs in one platform
  • Use case fit: Ideal for businesses needing both rapid no-code deployment and robust API capabilities, organizations handling diverse content types (1,400+ formats, multimedia transcription), teams requiring white-label chatbots with source citations for customer-facing or internal knowledge projects, and companies wanting all-in-one RAG without managing ML infrastructure
A I Models
  • Supported LLMs: GPT-4o, GPT-4o mini, GPT-3.5 Turbo, and Claude (version unspecified)
  • Embedding models: snowflake-arctic-embed-m (MTEB leaderboard leader), bge-en-icl (open-source), voyage-2 (paid), OpenAI text-embedding-3-large
  • User-provided API keys: Users configure OpenAI or Claude API keys via environment variables (only one required)
  • No model switching UI: Configuration via environment variables, not runtime switching interface
  • Embedding flexibility: Multiple embedding options from open-source (bge-en-icl) to proprietary (OpenAI, Cohere, Voyage)
  • Key finding: Benchmarks demonstrate open-source models (snowflake-arctic-embed-m) match or exceed paid alternatives in accuracy
  • Undisclosed Proprietary LLM: Stonly does not publicly disclose the specific model powering AI Answers feature
  • No Model Selection: Users cannot choose between GPT-3.5, GPT-4, Claude, Gemini, or other LLM providers
  • No Temperature Controls: No user-facing controls for adjusting response creativity, randomness, or formatting
  • No Fine-Tuning or Model Routing: Cannot customize model behavior beyond predefined AI Profiles and Custom Instructions
  • AI Profiles (Up to 20): Define tone, boundaries, and behavior for different use cases or audiences
  • Custom Instructions (Up to 100): Set specific rules and style guidelines for AI response generation
  • Guided AI Answers: Predefined responses for specific questions bypassing AI generation for sensitive scenarios
  • Automatic Fallback: Low-confidence scenarios trigger fallback to ML-powered search rather than forcing unreliable AI answer
  • Knowledge-Grounded Approach: AI responses anchored in Stonly guides, external websites, and PDFs to reduce hallucinations
  • Primary models: GPT-5.1 and 4 series from OpenAI, and Anthropic's Claude 4.5 (opus and sonnet) for enterprise needs
  • Automatic model selection: Balances cost and performance by automatically selecting the appropriate model for each request Model Selection Details
  • Proprietary optimizations: Custom prompt engineering and retrieval enhancements for high-quality, citation-backed answers
  • Managed infrastructure: All model management handled behind the scenes - no API keys or fine-tuning required from users
  • Anti-hallucination technology: Advanced mechanisms ensure chatbot only answers based on provided content, improving trust and factual accuracy
R A G Capabilities
  • Hybrid retrieval architecture: Elasticsearch (keyword search) + Milvus (vector/semantic search) + XGBoost ML reranking for superior accuracy
  • Three-component system notation: ES+VS+RR_n (Elasticsearch + Vector Search + Reranker)
  • 75.33 NDCG@10 on MTEB benchmarks: vs 73.16 for pure vector search (3% improvement)
  • 96.50% Recall@20: On Anthropic Contextual Retrieval benchmark (vs 90.06% baseline)
  • Reranker options: jinaai/jina-reranker-v2-base-multilingual (80+ languages), BAAI/bge-reranker-base (free, open-source)
  • Source citation: Visual PDF highlighting with page-level references and passage scoring
  • Hallucination prevention: Every response references specific passages from source documents with visual verification
  • 98.3% response accuracy claimed: 1.2-second average response time
  • AI Answers (Enterprise Add-On): Generative AI responses grounded in Stonly guides, external websites, and selected PDFs
  • Knowledge-Grounding: Responses anchored to structured content (interactive guides, decision trees, checklists) reducing hallucinations vs generic chatbots
  • Confidence-Based Fallback: Automatic switch to ML-powered search when AI confidence is low preventing unreliable answers
  • Multi-Source Ingestion: PDF uploads, public website crawling, Zendesk help center content indexing
  • Interactive Guide Format: Proprietary content model combining structured workflows with AI-generated answers
  • Limited Data Sources: No Google Drive, Dropbox, Notion, SharePoint, or YouTube transcript extraction
  • Manual Content Updates: Updates through Stonly's visual editor—no automatic syncing from external sources
  • 71% Self-Serve Success Rate: Documented effectiveness of AI Answers in reducing support escalations
  • Hallucination Controls: Strong grounding in structured content vs open-ended conversational AI
  • Core architecture: GPT-4 combined with Retrieval-Augmented Generation (RAG) technology, outperforming OpenAI in RAG benchmarks RAG Performance
  • Anti-hallucination technology: Advanced mechanisms reduce hallucinations and ensure responses are grounded in provided content Benchmark Details
  • Automatic citations: Each response includes clickable citations pointing to original source documents for transparency and verification
  • Optimized pipeline: Efficient vector search, smart chunking, and caching for sub-second reply times
  • Scalability: Maintains speed and accuracy for massive knowledge bases with tens of millions of words
  • Context-aware conversations: Multi-turn conversations with persistent history and comprehensive conversation management
  • Source verification: Always cites sources so users can verify facts on the spot
Use Cases
  • Customer support chatbots: Website deployment with lead capture and CRM integration for 24.8% conversion rates
  • SQL database chat (unique): Natural language queries against MySQL, PostgreSQL, Oracle, SQL Server, AWS RDS, Azure SQL, Google Cloud SQL
  • Technical documentation: "Hundreds of thousands of web pages" indexed in under 5 minutes for comprehensive knowledge bases
  • Multilingual support: 80+ languages with automatic language detection for global deployments
  • Developer-focused RAG: MIT-licensed denser-retriever for open-source validation and self-hosting experiments
  • Lead generation: Deeply integrated lead capture with AI qualification follow-ups and automatic CRM sync
  • Enterprise knowledge retrieval: Hybrid retrieval for technical teams prioritizing accuracy over enterprise certifications
  • Customer Support Ticket Deflection: 70-76% ticket reduction through interactive self-service guides and AI Answers
  • Help Desk Integration: Deep Zendesk, Salesforce Service Cloud, Freshdesk, ServiceNow integration for unified support workflows
  • Interactive Onboarding: Step-by-step guides, decision trees, and checklists for product onboarding and user education
  • Knowledge Base Enhancement: Augment traditional help centers with interactive guides and AI-powered search
  • Agent Assistance: Provide support agents with guided workflows and AI answers during live interactions
  • Multi-Language Support: Auto-translation on Enterprise plan for global support teams and multilingual customers
  • Complex Troubleshooting: Decision tree logic guides users through multi-step troubleshooting processes
  • Compliance & Training: Structured guides ensuring consistent information delivery for regulated industries
  • Customer support automation: AI assistants handling common queries, reducing support ticket volume, providing 24/7 instant responses with source citations
  • Internal knowledge management: Employee self-service for HR policies, technical documentation, onboarding materials, company procedures across 1,400+ file formats
  • Sales enablement: Product information chatbots, lead qualification, customer education with white-labeled widgets on websites and apps
  • Documentation assistance: Technical docs, help centers, FAQs with automatic website crawling and sitemap indexing
  • Educational platforms: Course materials, research assistance, student support with multimedia content (YouTube transcriptions, podcasts)
  • Healthcare information: Patient education, medical knowledge bases (SOC 2 Type II compliant for sensitive data)
  • Financial services: Product guides, compliance documentation, customer education with GDPR compliance
  • E-commerce: Product recommendations, order assistance, customer inquiries with API integration to 5,000+ apps via Zapier
  • SaaS onboarding: User guides, feature explanations, troubleshooting with multi-agent support for different teams
Security & Compliance
  • NO SOC 2 certification documented
  • NO HIPAA certification documented
  • NO ISO 27001 certification documented
  • NO GDPR documentation published
  • AES-256 encryption: Database connections for SQL chat integrations
  • Read-only database access required: Security requirement for SQL integrations
  • Private cloud deployments: Available on Enterprise plan for data sovereignty
  • Data deletion capability: Users can delete data anytime
  • AWS infrastructure: Hosted on AWS for data storage and processing
  • Role-based access controls: Mentioned but implementation details not documented
  • Government webinar partnership: Carahsoft webinar on "Secure, Compliant, and Verifiable AI Chatbots" suggests certification efforts underway
  • Best for: Non-regulated industries without strict compliance requirements
  • SOC 2 Type 2: Service Organization Control certification for security, availability, and confidentiality
  • GDPR Compliant: European data protection regulation compliance with data processing agreements
  • HIPAA Compliant: Healthcare data protection requirements for medical organizations and patient information
  • ISO 27001: International information security management system standard
  • PCI Compliant: Payment Card Industry Data Security Standard for handling payment information
  • CSA Star Level 1: Cloud Security Alliance STAR self-assessment certification
  • Trust Center: Public trust.stonly.com with security documentation, subprocessor lists, and controls information
  • SAML 2.0 SSO (Enterprise): Single sign-on integration with enterprise identity providers
  • IP Allowlisting (Enterprise): Restrict access to specific IP ranges for enhanced security
  • Advanced RBAC (Enterprise): Role-based access control with granular permissions and activity tracking
  • Two-Factor Authentication: SMS, email, hardware tokens, TOTP, U2F for account security
  • International Data Transfers: Standard Contractual Clauses for EU compliance and data protection
  • Data Residency: Options not publicly documented—may limit deployment in certain jurisdictions
  • Encryption: SSL/TLS for data in transit, 256-bit AES encryption for data at rest
  • SOC 2 Type II certification: Industry-leading security standards with regular third-party audits Security Certifications
  • GDPR compliance: Full compliance with European data protection regulations, ensuring data privacy and user rights
  • Access controls: Role-based access control (RBAC), two-factor authentication (2FA), SSO integration for enterprise security
  • Data isolation: Customer data stays isolated and private - platform never trains on user data
  • Domain allowlisting: Ensures chatbot appears only on approved sites for security and brand protection
  • Secure deployments: ChatGPT Plugin support for private use cases with controlled access
Pricing & Plans
  • Free: $0 - 1 chatbot, 20 queries/month, 5MB file limit, 200 API calls/month (retriever tier)
  • Starter: $19-29/month - 2 chatbots, 1,500 queries/month, REST API, 30-day conversation logs
  • Standard: $89-119/month - 4 chatbots, 7,500 queries/month, 2,000 documents, 90-day logs, custom domain
  • Business: $399-799/month - 8 chatbots, 15,000 queries/month, extended storage, 360-day logs, priority support
  • Enterprise: Custom pricing - Private cloud, dedicated support, custom SLAs, AWS Marketplace available
  • Annual billing discount: 20% off with annual payment commitment
  • Pricing inconsistency: Variations across sources suggest recent price changes or regional differences
  • User feedback: "Plans are quite restrictive, credit limits reached quite sooner for easier tasks" (G2 review)
  • Basic (Free): 5 guides, 400 views/month, 1 seat, single language, Stonly branding
  • Small Business ($249/mo or $199/mo annual): Unlimited guides, 4,000 views/month, 5 seats, 3 knowledge bases, CSS customization, Zapier, NPS surveys
  • Enterprise (Custom, ~$39K/year avg): Custom views, unlimited seats, white-label, SAML SSO, auto-translation, CSAT/CES surveys, Mobile SDKs
  • AI Answers (Enterprise Add-On): Available only as paid add-on to Enterprise plan—not included in Small Business tier
  • Overage Pricing: +15K views = $200/month, +30K views = $400/month (escalates quickly)
  • Automatic Tier Upgrades: Exceeding limits for 2 consecutive months triggers automatic upgrade and billing adjustment
  • Enterprise-Gated Features: AI Answers, Mobile SDKs, SAML SSO, white-labeling all require Enterprise plan
  • Average Enterprise Contract: ~$39,000 annually according to Vendr procurement data
  • Standard Plan: $99/month or $89/month annual - 10 custom chatbots, 5,000 items per chatbot, 60 million words per bot, basic helpdesk support, standard security View Pricing
  • Premium Plan: $499/month or $449/month annual - 100 custom chatbots, 20,000 items per chatbot, 300 million words per bot, advanced support, enhanced security, additional customization
  • Enterprise Plan: Custom pricing - Comprehensive AI solutions, highest security and compliance, dedicated account managers, custom SSO, token authentication, priority support with faster SLAs Enterprise Solutions
  • 7-Day Free Trial: Full access to Standard features without charges - available to all users
  • Annual billing discount: Save 10% by paying upfront annually ($89/mo Standard, $449/mo Premium)
  • Flat monthly rates: No per-query charges, no hidden costs for API access or white-labeling (included in all plans)
  • Managed infrastructure: Auto-scaling cloud infrastructure included - no additional hosting or scaling fees
Support & Documentation
  • Documentation: docs.denser.ai, retriever.denser.ai, GitHub READMEs across multiple repositories
  • Documentation fragmentation: Information scattered across multiple sites (docs, retriever docs, GitHub)
  • ~4-person team size: Impacts enterprise support capacity and response times
  • Priority support: Business plan ($399-799/month) and above
  • Dedicated support: Enterprise plan with custom SLAs
  • Open-source community: GitHub repositories (denser-retriever: 261 stars, 30 forks, MIT license)
  • AWS Marketplace: Available for procurement through existing AWS contracts
  • Best for: Technical teams comfortable with fragmented documentation and self-service troubleshooting
  • 4.8/5 G2 Rating: 132 reviews with consistently high satisfaction scores
  • Ease of Use Praised: "Ease of use" mentioned 32 times in G2 reviews indicating intuitive platform
  • Help Center Documentation: Comprehensive guides and tutorials for platform features
  • Email and Chat Support: Standard support channels for all paid plans
  • Dedicated Support (Enterprise): Priority support with dedicated account team and faster response times
  • Pre-Built Templates: Common support scenario templates accelerating guide creation
  • Quick Onboarding: Users report creating guides in under 30 minutes with small learning curve
  • REST API Documentation: API reference for user provisioning, content management, and widget control
  • Mobile SDKs (Enterprise): iOS, Android, React Native, Flutter for native app integration
  • Limited Developer Resources: No Python/Node.js SDKs, GraphQL, OpenAPI specs, or API Explorer/sandbox
  • Documentation hub: Rich docs, tutorials, cookbooks, FAQs, API references for rapid onboarding Developer Docs
  • Email and in-app support: Quick support via email and in-app chat for all users
  • Premium support: Premium and Enterprise plans include dedicated account managers and faster SLAs
  • Code samples: Cookbooks, step-by-step guides, and examples for every skill level API Documentation
  • Open-source resources: Python SDK (customgpt-client), Postman collections, GitHub integrations Open-Source SDK
  • Active community: User community plus 5,000+ app integrations through Zapier ecosystem
  • Regular updates: Platform stays current with ongoing GPT and retrieval improvements automatically
Limitations & Considerations
  • No compliance certifications: Missing SOC 2, HIPAA, ISO 27001, GDPR documentation - unsuitable for regulated industries
  • Small team size (~4 people): Potential scaling constraints for enterprise SLAs and support capacity
  • Heavy Zapier dependency: No native Slack, WhatsApp, Microsoft Teams integrations - requires Zapier middleware
  • Fragmented documentation: Information scattered across docs.denser.ai, retriever.denser.ai, GitHub READMEs
  • Self-hosted setup limitations: "Not suitable for production" - data persistence and secrets management require additional configuration
  • Pricing feedback: User reviews note "plans are quite restrictive, credit limits reached quite sooner"
  • No native cloud storage integrations: No Google Drive, Dropbox, Notion, OneDrive sync - requires manual export
  • CRM integrations via Zapier only: HubSpot, Salesforce, Zendesk lack native direct integration
  • Best for: Technical teams prioritizing retrieval accuracy and open-source transparency over enterprise certifications
  • NOT a RAG-as-a-Service Platform: Fundamentally a knowledge base tool with embedded AI—not a flexible RAG backend
  • AI Answers Enterprise-Gated: Core AI capabilities require expensive Enterprise plan (~$39K/year)—not available on $249/month Small Business tier
  • Undisclosed AI Model: No transparency on LLM provider—users cannot select or customize models
  • Limited Data Source Flexibility: PDF, public web, Zendesk only—missing Google Drive, Dropbox, Notion, SharePoint, YouTube
  • No Automatic Content Syncing: Manual updates through visual editor—no real-time integration with external knowledge sources
  • Missing Consumer Messaging: No Slack, WhatsApp, Telegram, Microsoft Teams native integrations (confirmed by user reviews)
  • No Omnichannel Messaging: Primarily website embedding and help desk integration—limited multi-channel support
  • Cannot Edit on Mobile: Guide creation and editing restricted to desktop—mobile limitation for on-the-go teams
  • Angular Compatibility Issues: Reported "random" behavior with Angular framework dynamic code
  • No Real-Time Analytics: Flow reports update every 15 minutes—not true real-time monitoring
  • Limited Developer API: No Python/Node.js SDKs, GraphQL, Swagger specs, or API sandbox for testing
  • Overage Pricing Escalation: View limits can trigger expensive automatic upgrades after 2 consecutive months
  • Not Ideal For: Developers seeking pure RAG API, multi-tenant SaaS RAG backends, use cases needing model selection/fine-tuning, or flexible data source integration
  • Managed service approach: Less control over underlying RAG pipeline configuration compared to build-your-own solutions like LangChain
  • Vendor lock-in: Proprietary platform - migration to alternative RAG solutions requires rebuilding knowledge bases
  • Model selection: Limited to OpenAI (GPT-5.1 and 4 series) and Anthropic (Claude, opus and sonnet 4.5) - no support for other LLM providers (Cohere, AI21, open-source models)
  • Pricing at scale: Flat-rate pricing may become expensive for very high-volume use cases (millions of queries/month) compared to pay-per-use models
  • Customization limits: While highly configurable, some advanced RAG techniques (custom reranking, hybrid search strategies) may not be exposed
  • Language support: Supports 90+ languages but performance may vary for less common languages or specialized domains
  • Real-time data: Knowledge bases require re-indexing for updates - not ideal for real-time data requirements (stock prices, live inventory)
  • Enterprise features: Some advanced features (custom SSO, token authentication) only available on Enterprise plan with custom pricing
Core Agent Features
  • AI agent capabilities: Process and organize data for optimal intelligent automation with workflow customization using intuitive builder
  • Multi-platform deployment: Launch AI chat across websites and messaging platforms with single line of code integration
  • Conversational AI: Natural-sounding chatbot powered by RAG that sounds natural and provides personalized interactions based on business data
  • Adaptive learning: Chatbot learns over time using data analysis to get smarter after every conversation
  • Unlike simpler rule-based systems: Denser's chatbots operate more like AI agents capable of adapting to complex workflows and providing actionable insights
  • Data integration: Import content from websites, documents, or Google Drive for comprehensive knowledge base
  • 24/7 availability: Build smart AI support that knows your business for instant answers around the clock
  • Natural language database chat: Converse with database in natural language with SQL query generation
  • Verified sources: Get verified sources with every answer for transparency and trust
  • No coding expertise required: Enterprise-grade security without technical implementation complexity
  • Conversational AI Bot: Delivers confident answers backed by verified structured knowledge unlike generic LLMs that can hallucinate or invent answers
  • Knowledge-grounded responses: Provides answers backed by verified structured knowledge from guides you create preventing fabricated information
  • AI Agent Assist: Automatically summarizes tickets, suggests right path to resolution, and generates responses for support agents
  • Three core automation functions: Automatically analyzes and summarizes support ticket content, recommends most relevant Stonly guide/knowledge path to resolve issues, drafts complete responses for agents to review/edit/send
  • Process automation: Define processes to be followed and link them to different back-office tools to resolve customer requests before they reach support
  • Personalized knowledge: AI-powered solutions and process automation allow creation of guides, walkthroughs, checklists, knowledge bases adapting to each customer's needs
  • 71% self-serve success rate: With AI Answers feature documented in company data
  • Hallucination reduction: Knowledge-grounding approach vs generic chatbots reduces off-topic responses
  • Custom AI Agents: Build autonomous agents powered by GPT-4 and Claude that can perform tasks independently and make real-time decisions based on business knowledge
  • Decision-Support Capabilities: AI agents analyze proprietary data to provide insights, recommendations, and actionable responses specific to your business domain
  • Multi-Agent Systems: Deploy multiple specialized AI agents that can collaborate and optimize workflows in areas like customer support, sales, and internal knowledge management
  • Memory & Context Management: Agents maintain conversation history and persistent context for coherent multi-turn interactions View Agent Documentation
  • Tool Integration: Agents can trigger actions, integrate with external APIs via webhooks, and connect to 5,000+ apps through Zapier for automated workflows
  • Hyper-Accurate Responses: Leverages advanced RAG technology and retrieval mechanisms to deliver context-aware, citation-backed responses grounded in your knowledge base
  • Continuous Learning: Agents improve over time through automatic re-indexing of knowledge sources and integration of new data without manual retraining
Additional Considerations
  • Initial setup time investment: Training AI models takes time on first implementation but provides long-term business value
  • Integration requirements: Tool choices impact functionality, scalability, and ease of use - poor choices can lead to integration challenges or subpar performance
  • Continuous monitoring essential: Once live, ongoing monitoring ensures system performs as expected and adapts to organizational changes
  • Data flow verification: During deployment, double-check integration with existing tools (databases, CRMs, knowledge bases) to ensure smooth data flow and accurate information retrieval
  • Dependency risk consideration: Users report finding themselves over-reliant on Denser AI which could impact business operations if service disrupted
  • Network dependency: Some users report inability to access chatbot due to network issues - consider offline backup plans
  • Transparency concerns: Potential for bias amplification and lack of transparency leading to black-box decision-making requires careful monitoring
  • Balance strengths: Denser.ai balances ease of use with flexibility through customization options without requiring deep technical expertise
  • Best deployment practices: Verify integrations before going live, monitor performance continuously, and ensure data sources remain current
  • Limited UI customization: Limited ability to customize user interface and workflows to match specific brand requirements is primary user concern
  • Basic collaboration tools: Without real-time editing or advanced team management features can hinder team productivity when multiple people need to work together
  • No offline access: Guides unavailable without internet connectivity reducing usability in areas with unreliable internet
  • Performance degradation: Can degrade with very large or complex guides causing slower responsiveness indicating scalability concerns
  • Restricted language options: Limit efficient creation of multilingual content which may be barrier for global organizations
  • Mixed media support missing: Users find missing features wishing for mixed media support and enhanced reporting tools
  • Step ordering difficulties: Users report limitations in feature usability and difficulties with step ordering though support offers helpful workarounds
  • Requires coding knowledge: Unlike most competitors, doesn't advertise as no-code platform - need coding knowledge to track events, target users, stream data, and style content
  • Image workflow limitations: Inability to use images in base offering limits utility in some workflows with some advanced features requiring extra costs
  • View-based pricing: Charges additional fees based on guide views - customers exceeding 4,000 guide views/month pay extra $250-500 monthly depending on volume
  • Integration reliability: Users find lack of integrations limits ability to fully connect Stonly with other tools - Stonly/Zendesk integration isn't as reliable as desired (stops working every few weeks)
  • Slashes engineering overhead with an all-in-one RAG platform—no in-house ML team required.
  • Gets you to value quickly: launch a functional AI assistant in minutes.
  • Stays current with ongoing GPT and retrieval improvements, so you’re always on the latest tech.
  • Balances top-tier accuracy with ease of use, perfect for customer-facing or internal knowledge projects.
Core Chatbot Features
  • Conversational interface: Chat directly with customers in friendly conversational manner to quickly respond to questions
  • Business knowledge integration: Chatbot knows everything about your business from uploaded documents, websites, and Google Drive content
  • Multi-language support: 80+ languages with automatic language detection for global deployments
  • Lead capture capabilities: Deeply integrated lead capture with configurable form fields (name, email, company, role, phone)
  • AI qualification follow-ups: Automatic CRM sync with intelligent lead qualification
  • Conversation-triggered forms: Dynamic form deployment based on conversation context
  • Human handoff: Triggers when chatbot detects query complexity beyond scope with escalation workflows
  • Zendesk ticket creation: Automatic ticket generation for human handoff scenarios
  • Visual customization: Drag-and-drop builder for theme colors, logos, button sizing, message bubble styling
  • Custom domains: Available on paid tiers for white-labeling with domain restrictions for specific page deployment
  • 24.8% conversion rate claimed: Documented on homepage demonstrating lead generation effectiveness
  • Interactive step-by-step guides: Visual flow builder for creating structured content paths
  • Decision trees and branching logic: Guide users through complex troubleshooting with intelligent path selection
  • Checklists and task management: Help users complete multi-step processes with progress tracking
  • Contact forms and lead capture: Integrated forms for collecting customer information during interactions
  • Content versioning: Side-by-side comparison and instant restore on Business and Enterprise plans for content management
  • Multi-language support: Auto-translation on Enterprise plan for global deployments
  • Knowledge bases: 3 on Small Business plan, unlimited on Enterprise for organizing content
  • Guide views tracking: 400 (Free), 4,000 (Small Business), custom (Enterprise) for monitoring usage
  • NPS surveys: Available on all plans for measuring customer satisfaction
  • CSAT and CES surveys: Enterprise only for comprehensive satisfaction and effort measurement
  • Reduces hallucinations by grounding replies in your data and adding source citations for transparency. Benchmark Details
  • Handles multi-turn, context-aware chats with persistent history and solid conversation management.
  • Speaks 90+ languages, making global rollouts straightforward.
  • Includes extras like lead capture (email collection) and smooth handoff to a human when needed.
Customization & Flexibility ( Behavior & Knowledge)
  • Highly customizable: Align chatbot with brand and specific needs including responses and behavior customization
  • Appearance personalization: Customize chatbot appearance, responses, behavior, and knowledge base to match requirements
  • Tone of voice configuration: Define name, choose tone of voice, and set behavior preferences guiding how bot interprets and responds to queries
  • Comprehensive file support: Upload and manage PDF, DOCX, XLSX, PPTX, TXT, HTML, CSV, TSV, and XML files for knowledge base
  • Website crawling: Train bot by crawling website URLs to build comprehensive knowledge base
  • Easy knowledge updates: Add new documents, re-crawl website, or update existing files in Denser dashboard with automatic knowledge base updates without rebuild
  • Flexible deployment: Embed knowledge base across internal systems through web widget, integrate within company dashboard, or use API for custom tools
  • Extensive integrations: Platform integrations with Shopify, Wix, Slack, and Zapier plus RESTful API with comprehensive documentation
  • Advanced custom applications: API and documentation support for building advanced custom integrations and workflows
  • Real-time updates: Knowledge base automatically reflects new information when documents added or website re-crawled
  • CSS and HTML customization: Change layout and look of knowledge base with custom code capabilities
  • Intuitive customization tools: Easy-to-use tools that don't require code for basic customization
  • Layout customization: Decide how content is structured and presented with flexible options
  • Design controls: Manage visual components like colors, logo, or cover image for brand alignment
  • Personalized content: Use customer data to show personalized content from knowledge base for targeted experiences
  • Data-driven personalization: Customers see what they need right away when first accessing knowledge base
  • Analytics insights: Guide usage analytics provide insight into customer behavior for continuous improvement
  • Highly flexible platform: Users appreciate ability to use Stonly for knowledge bases and guided tours with target properties based on specific user needs
  • Rich media support: Add images, GIFs, videos, and annotations to bring knowledge base content to life
  • Third-party scripts: Install scripts from other tools like Google Analytics for extended functionality
  • Lets you add, remove, or tweak content on the fly—automatic re-indexing keeps everything current.
  • Shapes agent behavior through system prompts and sample Q&A, ensuring a consistent voice and focus. Learn How to Update Sources
  • Supports multiple agents per account, so different teams can have their own bots.
  • Balances hands-on control with smart defaults—no deep ML expertise required to get tailored behavior.
Core Knowledge Base Features
N/A
  • Interactive step-by-step guides with visual flow builder
  • Decision trees and branching logic
  • Checklists and task management
  • Contact forms and lead capture
  • Content versioning: Side-by-side comparison, instant restore
  • Multi-language support: Auto-translation on Enterprise plan
  • Knowledge bases: 3 on Small Business, unlimited on Enterprise
  • Guide views tracking: 400 (Free), 4,000 (Small Business), custom (Enterprise)
  • NPS surveys: All plans
  • CSAT and CES surveys: Enterprise only
N/A
A I Answers Feature ( Enterprise Only)
N/A
  • Note: Available only as paid Enterprise add-on - not included in Small Business plan
  • Generative AI responses grounded in Stonly guides, external websites, and selected PDFs
  • 20 AI Profiles per team: Define tone, boundaries, and behavior
  • 100 Custom Instructions per team: Detailed response rules
  • Guided AI Answers: Predefined responses for specific questions
  • Confidence-based fallback: Automatically switches to ML-powered search when AI confidence is low
  • 71% self-serve success rate achieved with AI Answers
  • Hallucination reduction: Knowledge-grounding approach vs generic chatbots
N/A

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Final Thoughts

Final Verdict: Denser.ai vs Stonly

After analyzing features, pricing, performance, and user feedback, both Denser.ai and Stonly are capable platforms that serve different market segments and use cases effectively.

When to Choose Denser.ai

  • You value state-of-the-art hybrid retrieval (75.33 ndcg@10) outperforms pure vector search with published benchmarks
  • Open-source MIT-licensed core (denser-retriever) enables transparency, validation, and self-hosting
  • SQL database chat capability unique differentiator for business intelligence use cases

Best For: State-of-the-art hybrid retrieval (75.33 NDCG@10) outperforms pure vector search with published benchmarks

When to Choose Stonly

  • You value exceptional ease of use - 4.8/5 g2 rating with intuitive visual editor praised in 32 reviews
  • Deep help desk integrations - bidirectional Zendesk, Salesforce, Freshdesk, ServiceNow connections
  • Strong compliance - SOC 2 Type 2, GDPR, HIPAA, ISO 27001, PCI, CSA Star Level 1

Best For: Exceptional ease of use - 4.8/5 G2 rating with intuitive visual editor praised in 32 reviews

Migration & Switching Considerations

Switching between Denser.ai and Stonly requires careful planning. Consider data export capabilities, API compatibility, and integration complexity. Both platforms offer migration support, but expect 2-4 weeks for complete transition including testing and team training.

Pricing Comparison Summary

Denser.ai starts at $19/month, while Stonly begins at $249/month. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.

Our Recommendation Process

  1. Start with a free trial - Both platforms offer trial periods to test with your actual data
  2. Define success metrics - Response accuracy, latency, user satisfaction, cost per query
  3. Test with real use cases - Don't rely on generic demos; use your production data
  4. Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
  5. Check vendor stability - Review roadmap transparency, update frequency, and support quality

For most organizations, the decision between Denser.ai and Stonly comes down to specific requirements rather than overall superiority. Evaluate both platforms with your actual data during trial periods, focusing on accuracy, latency, ease of integration, and total cost of ownership.

📚 Next Steps

Ready to make your decision? We recommend starting with a hands-on evaluation of both platforms using your specific use case and data.

  • • Review: Check the detailed feature comparison table above
  • • Test: Sign up for free trials and test with real queries
  • • Calculate: Estimate your monthly costs based on expected usage
  • • Decide: Choose the platform that best aligns with your requirements

Last updated: December 12, 2025 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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Priyansh Khodiyar's avatar

Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.

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