Deepset 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 Deepset 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 Deepset 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 Deepset if: you value mature open-source framework (since 2020)
  • Choose Stonly if: you value exceptional ease of use - 4.8/5 g2 rating with intuitive visual editor praised in 32 reviews

About Deepset

Deepset Landing Page Screenshot

Deepset is open-source framework and enterprise platform for llm orchestration. Deepset is the creator of Haystack, the leading open-source framework for building production-ready LLM applications, and offers an enterprise AI platform for developing and deploying custom AI agents and applications. Founded in 2018, headquartered in Berlin, Germany, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
83/100
Starting Price
Custom

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, Deepset starts at a lower price point. The platforms also differ in their primary focus: AI Development 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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Deepset
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Stonly
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CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
  • Gives developers a flexible framework to wire up connectors and process nearly any file type or data source with libraries like Unstructured.
  • Lets you push content into vector stores such as OpenSearch, Pinecone, Weaviate, or Snowflake—pick the backend that fits best. Learn more
  • Setup is hands-on, but the payoff is deep, domain-specific customization of your ingestion pipelines.
  • 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.
Integrations & Channels
  • API-first approach—drop the RAG system into your own app through REST endpoints or the Haystack SDK.
  • Shareable pipeline prototypes are great for demos, but production channels (Slack bots, web chat, etc.) need a bit of custom code. See prototype feature
  • 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.
Core Chatbot Features
  • Builds RAG agents as modular pipelines—retriever + reader, plus optional rerankers or multi-step logic.
  • Multi-turn chat? Source attributions? Fine-grained retrieval tweaks? All possible with the right config. Pipeline overview
  • Advanced users can layer in tool use and external API calls for richer agent behavior.
  • 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 & Branding
  • No drag-and-drop theming here—you’ll craft your own front end if you need branded UI.
  • That also means full freedom to shape the visuals and conversational tone any way you like. Custom components
  • 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.
L L M Model Options
  • Model-agnostic: plug in GPT-4, Llama 2, Claude, Cohere, and more—whatever works for you.
  • Switch models or embeddings through the “Connections” UI with just a few clicks. View supported models
  • 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.
Developer Experience ( A P I & S D Ks)
  • Comprehensive REST API plus the open-source Haystack SDK for building, running, and querying pipelines.
  • Deepset Studio’s visual editor lets you drag-and-drop components, then export YAML for version control. Studio overview
  • 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.
Performance & Accuracy
  • Tune for max accuracy with multi-step retrieval, hybrid search, and custom rerankers.
  • Mix and match components to hit your latency targets—even at large scale. Benchmark insights
  • 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.
Customization & Flexibility ( Behavior & Knowledge)
  • Build anything: multi-hop retrieval, custom logic, bespoke prompts—your pipeline, your rules.
  • Create multiple datastores, add role-based filters, or pipe in external APIs as extra tools. Component templates
  • 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.
Pricing & Scalability
  • Start free in Deepset Studio, then move to usage-based Enterprise plans as you scale.
  • Deploy in cloud, hybrid, or on-prem setups to handle huge corpora and heavy traffic. Pricing overview
  • 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
  • SOC 2 Type II, ISO 27001, GDPR, HIPAA—you’re covered for enterprise compliance.
  • Choose cloud, VPC, or on-prem to keep data exactly where you need it. Security compliance
  • 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.
Observability & Monitoring
  • Deepset Studio dashboard shows latency, error rates, resource use—everything you’d expect.
  • Detailed logs integrate with Prometheus, Splunk, and more for deep observability. Monitoring features
  • 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.
Support & Ecosystem
  • Lean on the Haystack open-source community (Discord, GitHub) or paid enterprise support. Community insights
  • Wide ecosystem of vector DBs, model providers, and ML tools means plenty of plug-ins and extensions.
  • 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.
Additional Considerations
  • Perfect for teams that need heavily customized, domain-specific RAG solutions.
  • Full control and future portability—but expect a steeper learning curve and more dev effort. More details
  • 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.
No- Code Interface & Usability
  • Deepset Studio offers low-code drag-and-drop, yet it's still aimed at developers and ML engineers.
  • Non-tech users may need help, and production UIs will be custom-built.
  • 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.
Competitive Positioning
  • Market position: Developer-first RAG framework (Haystack) with enterprise cloud offering (Deepset Cloud) for heavily customized, domain-specific RAG solutions
  • Target customers: ML engineers and development teams needing deep RAG customization, enterprises requiring domain-specific solutions with modular pipeline architecture, and organizations wanting future portability with open-source foundation
  • Key competitors: LangChain/LangSmith, Contextual.ai, Dataworkz, Vectara.ai, and custom implementations using Pinecone/Weaviate
  • Competitive advantages: Open-source Haystack framework for full portability, model-agnostic with easy model switching via Connections UI, Deepset Studio visual pipeline editor with YAML export for version control, modular components (retriever, reader, reranker) for maximum flexibility, wide ecosystem of vector DB integrations (OpenSearch, Pinecone, Weaviate, Snowflake), and SOC 2/ISO 27001/GDPR/HIPAA compliance with cloud/VPC/on-prem deployment
  • Pricing advantage: Free Deepset Studio for development, then usage-based Enterprise plans; competitive for teams wanting deep customization without vendor lock-in; best value comes from open-source foundation enabling future migration if needed
  • Use case fit: Perfect for teams needing heavily customized, domain-specific RAG with multi-hop retrieval and custom rerankers, organizations requiring modular pipeline architecture for complex workflows, and ML engineers wanting developer-friendly APIs with future portability through open-source Haystack foundation
  • 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
  • Model-agnostic architecture: Supports GPT-4, GPT-3.5, Claude (Anthropic), Llama 2, Cohere, and 80+ model providers through unified interface
  • Easy model switching: Change models via Connections UI with just a few clicks without code changes
  • Embedding models: OpenAI, Cohere, Sentence Transformers, and custom embedding models supported
  • Multiple LLMs per pipeline: Use different models for different pipeline components (retrieval vs generation)
  • Custom model fine-tuning: Fine-tune on proprietary data for domain-specific terminology and accuracy
  • Baseline models available: Pre-configured with common models for quick prototyping
  • 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
  • Advanced RAG architecture: Multi-step retrieval, hybrid search (semantic + keyword), and custom rerankers for maximum accuracy
  • Modular pipeline design: Flexible retriever + reader + optional reranker components for customized workflows
  • Multi-hop retrieval: Chain multiple retrieval steps for complex queries requiring deep context
  • Vector database flexibility: OpenSearch, Pinecone, Weaviate, Snowflake, Qdrant, and more - choose your preferred backend
  • Benchmark-proven performance: Published performance metrics on MTEB and domain-specific benchmarks
  • Source attribution: Full citation tracking with document references and confidence scores
  • Haystack framework: Open-source foundation enables complete RAG customization and future portability
  • 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
  • Domain-specific Q&A: Enterprise knowledge bases with specialized terminology requiring fine-tuned models
  • Research and analysis: Multi-hop retrieval for complex research questions across large document corpora
  • Technical documentation: Developer-focused RAG for code documentation, API references, and technical guides
  • Compliance and legal: HIPAA/GDPR-compliant RAG systems for regulated industries requiring on-prem deployment
  • Custom AI agents: Build specialized agents with external API calls, tool use, and multi-step reasoning
  • Enterprise search: Large-scale search across millions of documents with hybrid retrieval and reranking
  • Future-proof AI: Migrate between LLM providers, vector databases, and hosting options without vendor lock-in
  • 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
  • SOC 2 Type II certification: Annual audits ensuring enterprise security standards
  • ISO 27001 certification: International information security management compliance
  • GDPR compliance: European data protection regulation adherence with data sovereignty options
  • HIPAA compliance: Healthcare data protection standards for sensitive medical information
  • Flexible deployment: Cloud, hybrid, VPC, or on-premises deployment for complete data control
  • Data residency options: Choose where data is stored and processed (US, EU, on-prem)
  • No model training on customer data: Customer data never used to train third-party models
  • Audit trails: Comprehensive logging of all queries, retrievals, and system access
  • 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
  • Deepset Studio (Free): Development environment with unlimited files and core features for prototyping
  • Enterprise pricing: Custom usage-based pricing based on queries, documents indexed, and compute resources
  • Deployment options pricing: Cloud (managed SaaS), hybrid, or on-premises with separate pricing tiers
  • No per-seat charges: Usage-based model scales with actual platform usage, not team size
  • Professional services: Optional consulting, integration support, and custom pipeline development available
  • Scaling flexibility: Enterprise plans handle huge corpora (millions of documents) and heavy traffic loads
  • Open-source advantage: Haystack framework free forever - only pay for managed cloud services if needed
  • 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
  • Haystack community: Active Discord server and GitHub community (14,000+ stars) with responsive maintainers
  • Enterprise support tiers: Email, Slack Connect channels, and dedicated support engineers for paid customers
  • Comprehensive documentation: docs.cloud.deepset.ai with tutorials, API references, and integration guides
  • Video tutorials: YouTube channel with pipeline building guides and best practices
  • GitHub examples: Open-source example projects and starter templates for common use cases
  • Integration ecosystem: Wide community of vector DB providers, model vendors, and tool developers
  • Professional services: Custom development, architecture consulting, and hands-on implementation support available
  • 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
  • Steeper learning curve: Developer-first platform requires ML/engineering skills - not ideal for non-technical users
  • Custom UI required: No drag-and-drop chat widget - must build production interfaces from scratch
  • Hands-on setup: More initial configuration effort compared to plug-and-play SaaS platforms
  • Deepset Studio limitations: Visual editor still aimed at technical users - requires understanding of RAG concepts
  • Production readiness: Moving from Studio prototype to production deployment requires additional DevOps work
  • Enterprise costs: Usage-based pricing can become expensive at high query volumes without careful optimization
  • Best for technical teams: Maximum value requires ML engineers and developers - not suited for business users seeking no-code solutions
  • Integration effort: Native integrations like Slack bots require custom code vs turnkey options from competitors
  • 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 Agents with Haystack: Build LLM-powered autonomous agents that can reason, reflect, and act using tools, data, and critical introspection into their own decision-making processes Building Agents
  • Spectrum Approach: Combines structured workflows with autonomous capabilities - AI systems exist on a spectrum between linearity and autonomy based on decision-making capability needs Agentic Spectrum
  • Planning Mechanisms: Agents break tasks into steps using chain-of-thought or tree-of-thought planning, enabling complex multi-step reasoning and execution
  • Dynamic Routing: LLMs serve as "brains" of decision systems, using reasoning capabilities to evaluate and choose among multiple tools, courses of action, databases, and resources based on context and goals
  • Reflection & Self-Correction: Agents analyze intermediate results through reflection mechanisms, improving accuracy and adapting strategies based on outcomes
  • Tool Integration: Modular pipeline design allows agents to use retriever, reader, reranker components, external API calls, and custom tools for richer autonomous behavior
  • Agentic RAG Enhancement: Build agentic RAG pipelines in Deepset Studio that combine graphs, agentic properties, multimodal capabilities, and innovations to significantly reduce inaccurate or misleading information Agentic RAG Guide
  • Custom Workflows: Create anything from multi-hop retrieval to custom logic to bespoke prompts - modular components enable building specialized agents for domain-specific autonomous workflows
  • 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
R A G-as-a- Service Assessment
  • Platform Type: HYBRID RAG FRAMEWORK + CLOUD SERVICE - open-source Haystack foundation with enterprise Deepset Cloud offering for heavily customized, domain-specific RAG solutions
  • Core Architecture: Modular pipeline architecture with retriever + reader + optional reranker components, full control over embedding models, vector databases (OpenSearch, Pinecone, Weaviate, Snowflake), and chunking strategies
  • Agentic Capabilities: Build autonomous AI agents with planning, routing, reflection mechanisms using Haystack framework - supports agentic RAG pipelines with graphs and multimodal capabilities Agent Development
  • Developer Experience: Comprehensive REST API, open-source Haystack SDK, Deepset Studio visual pipeline editor with YAML export for version control - targets ML engineers and development teams Studio Overview
  • No-Code Capabilities: Deepset Studio offers drag-and-drop visual editor for pipeline building, but still aimed at developers and ML engineers - not accessible to non-technical users
  • Target Market: ML engineers and development teams needing deep RAG customization, enterprises requiring domain-specific solutions with modular pipeline architecture, organizations wanting future portability with open-source foundation
  • RAG Technology Leadership: Advanced RAG with multi-step retrieval, hybrid search (semantic + keyword), custom rerankers for maximum accuracy, model-agnostic support (GPT-4, Llama 2, Claude, Cohere, 80+ providers), and benchmark-proven performance on MTEB Benchmark Insights
  • Deployment Flexibility: Free Deepset Studio for development, usage-based Enterprise plans, cloud/VPC/on-prem deployment options, and SOC 2/ISO 27001/GDPR/HIPAA compliance with flexible data residency
  • Enterprise Readiness: SOC 2 Type II, ISO 27001, GDPR, HIPAA compliance, cloud/hybrid/on-prem deployment, no model training on customer data, and comprehensive audit trails
  • Use Case Fit: Perfect for teams needing heavily customized domain-specific RAG with multi-hop retrieval and custom rerankers, organizations requiring modular pipeline architecture for complex workflows, ML engineers wanting developer-friendly APIs with future portability
  • Open-Source Advantage: Haystack framework (14,000+ GitHub stars) free forever with full portability - only pay for managed Deepset Cloud services if needed, avoiding vendor lock-in
  • NOT Suitable For: Non-technical teams seeking turnkey chatbots, business users wanting no-code deployment, organizations needing pre-built chat widgets or Slack/WhatsApp integrations
  • Competitive Positioning: Competes with LangChain/LangSmith, Contextual.ai, Dataworkz - differentiates through open-source Haystack foundation, model-agnostic flexibility, visual pipeline editor, and wide vector DB ecosystem
  • 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
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: Deepset vs Stonly

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

When to Choose Deepset

  • You value mature open-source framework (since 2020)
  • Production-ready from day one
  • Highly modular and customizable

Best For: Mature open-source framework (since 2020)

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 Deepset 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

Deepset starts at custom pricing, 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 Deepset 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 15, 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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