Data Ingestion & Knowledge Sources
Document formats – PDF, DOCX, PPTX, CSV, TXT, HTML; 5MB free tier limit
Website crawling – Hundreds of thousands of pages indexed under 5 minutes
Google Drive – Native integration with real-time sync for cloud content
SQL databases – MySQL, PostgreSQL, Oracle, SQL Server, AWS/Azure/Google Cloud SQL
⚠️ YouTube, Dropbox, Notion, OneDrive – Zapier middleware required (no native integration)
✅ Auto-Indexing – Points at files, indexes unstructured data automatically without manual setup
✅ Auto-Sync – Connected repositories sync automatically, document changes reflected almost instantly
File Formats – Supports PDF, DOCX, PPT, TXT and common enterprise formats
⚠️ Limited Scope – No website crawling or YouTube ingestion, narrower than CustomGPT
Enterprise Scale – Handles large corporate data sets, exact limits not published
1,400+ file formats – PDF, DOCX, Excel, PowerPoint, Markdown, HTML + auto-extraction from ZIP/RAR/7Z archives
Website crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public content
Multimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-in
Cloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-sync
Knowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectors
Massive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation
Hybrid Retrieval Architecture ( Core Differentiator)
✅ Three-component system – Elasticsearch + Milvus vectors + XGBoost ML reranking
75.33 NDCG@10 – MTEB vs 73.16 pure vector (3% improvement)
96.50% Recall@20 – Anthropic benchmark vs 90.06% baseline
Models – snowflake-arctic-embed-m, bge-en-icl, voyage-2, OpenAI text-embedding-3-large
✅ Key finding – Open-source models match/exceed paid alternatives in benchmarks
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98.3% response accuracy – Claimed with 1.2-second average response
Source citation – Visual PDF highlighting with page-level references
⚠️ No published uptime SLA – Service reliability not documented
Real-Time Answers – Serves accurate responses from internal documents, sparse public benchmarks
Auto-Sync Freshness – Connected repositories keep retrieval context always current automatically
⚠️ Limited Transparency – No anti-hallucination metrics or advanced re-ranking details published
Competitive RAG – Likely comparable to standard GPT-based systems on relevance control
Sub-second responses – Optimized RAG with vector search and multi-layer caching
Benchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants API
Anti-hallucination tech – Responses grounded only in your provided content
OpenGraph citations – Rich visual cards with titles, descriptions, images
99.9% uptime – Auto-scaling infrastructure handles traffic spikes
Developer Experience ( A P I & S D Ks)
REST API + GraphQL – Bearer token auth with scored passage responses
denser-retriever – MIT-licensed Python package (261 stars, 30 forks)
Docker Compose – Full stack with Elasticsearch and Milvus containers
⚠️ Self-hosted "not production suitable" – Requires additional persistence and secrets config
Rate limits – 200 API calls/month on free tier
⚠️ No API – No open API or SDKs, everything through Pyx interface
⚠️ No Embedding – Cannot integrate into other apps or call programmatically
Closed Ecosystem – No GitHub examples, community plug-ins, or extensibility options
Turnkey Only – Great for ready-made tool, limits deep customization or extensions
REST API – Full-featured for agents, projects, data ingestion, chat queries
Python SDK – Open-source customgpt-client with full API coverage
Postman collections – Pre-built requests for rapid prototyping
Webhooks – Real-time event notifications for conversations and leads
OpenAI compatible – Use existing OpenAI SDK code with minimal changes
Supported LLMs – GPT-4o, GPT-4o mini, GPT-3.5, Claude (version unspecified)
API keys – Users provide OpenAI or Claude keys via environment
⚠️ No custom fine-tuning – No private model hosting documented
⚠️ Undisclosed Model – Likely GPT-3.5/GPT-4 but exact model not publicly documented
⚠️ No Model Selection – Cannot switch LLMs or configure speed vs accuracy tradeoffs
⚠️ Single Configuration – Every query uses same model, no toggles or fine-tuning
Closed Architecture – Model details, context window, capabilities hidden from users intentionally
GPT-5.1 models – Latest thinking models (Optimal & Smart variants)
GPT-4 series – GPT-4, GPT-4 Turbo, GPT-4o available
Claude 4.5 – Anthropic's Opus available for Enterprise
Auto model routing – Balances cost/performance automatically
Zero API key management – All models managed behind the scenes
Website deployment – JavaScript widget (single line), iFrame, REST API
WordPress – Official plugin with page-specific targeting for no-code install
Zapier – 6,000+ apps with lead form triggers and events
⚠️ No native Slack, Teams, Discord – WhatsApp via Zapier only
⚠️ CRM via Zapier only – HubSpot, Salesforce, Zendesk not native
⚠️ Standalone Only – Own chat/search interface, not a "deploy everywhere" platform
⚠️ No External Channels – No Slack bot, Zapier connector, or public API
Web/Desktop UI – Users interact through Pyx's interface, minimal third-party chat synergy
Custom Integration – Deeper integrations require custom dev work or future updates
Website embedding – Lightweight JS widget or iframe with customizable positioning
CMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support
5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce tools
MCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, Windsurf
OpenAI SDK compatible – Drop-in replacement for OpenAI API endpoints
LiveChat + Slack – Native chat widgets with human handoff capabilities
Drag-and-drop builder – Theme colors, logos, button sizing, bubbles
Custom domains – Available on paid tiers for white-labeling
Welcome messages – Configure suggested questions and greetings
⚠️ Minimal Branding – Logo/color tweaks only, designed as internal tool not white-label
⚠️ No Embedding – Standalone interface, no domain-embed or widget options available
Pyx UI Only – Look stays "Pyx AI" by design, public branding not supported
Security Focus – Emphasis on user management and access controls over theming
Full white-labeling included – Colors, logos, CSS, custom domains at no extra cost
2-minute setup – No-code wizard with drag-and-drop interface
Persona customization – Control AI personality, tone, response style via pre-prompts
Visual theme editor – Real-time preview of branding changes
Domain allowlisting – Restrict embedding to approved sites only
No- Code Interface & Usability
Visual builder – Drag-and-drop theme customization without coding
Setup – Single line JavaScript; WordPress plugin for no-code
⚠️ Learning curve – Documentation fragmented across multiple sites
⚠️ ~4-person team – Impacts enterprise support capacity
✅ Straightforward UI – Users log in, ask questions, get answers without coding
✅ No-Code Admin – Admins connect data sources, Pyx indexes automatically
Minimal Customization – UI stays consistent and uncluttered by design
Internal Q&A Hub – Perfect for employee use, not external embedding or branding
2-minute deployment – Fastest time-to-value in the industry
Wizard interface – Step-by-step with visual previews
Drag-and-drop – Upload files, paste URLs, connect cloud storage
In-browser testing – Test before deploying to production
Zero learning curve – Productive on day one
Integrated lead capture – Configurable fields (name, email, company, role, phone)
Conversation-triggered forms – Dynamic deployment based on conversation context
Analytics dashboard – Lead quality, satisfaction scores, conversion trends
✅ 24.8% conversion rate – Claimed on homepage demonstrating effectiveness
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Multi- Language & Localization
80+ languages – Automatic language detection for global deployments
Multilingual rerankers – jinaai/jina-reranker-v2-base-multilingual support
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Conversation history – 30-360 days retention by tier
Human handoff – Triggers when complexity exceeds scope
Escalation workflows – Zendesk ticket creation for handoffs
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Observability & Monitoring
Conversation logs – Retention by tier (30-360 days)
User engagement tracking – Common queries, conversation length, drop-off points
⚠️ No A/B testing – No third-party BI integration (Tableau, PowerBI)
⚠️ No real-time alerting – No documented SLA tracking
Basic Stats – User activity, query counts, top-referenced documents for admins
⚠️ No Deep Analytics – No conversation analytics dashboards or real-time logging
Adoption Tracking – Useful for usage monitoring, lighter insights than full suites
Set-and-Forget – Minimal monitoring overhead, contact support for issues
Real-time dashboard – Query volumes, token usage, response times
Customer Intelligence – User behavior patterns, popular queries, knowledge gaps
Conversation analytics – Full transcripts, resolution rates, common questions
Export capabilities – API export to BI tools and data warehouses
S Q L Database Chat ( Unique Feature)
✅ Direct SQL connectivity – Conversational BI across major databases
Supported databases – MySQL, PostgreSQL, Oracle, SQL Server, AWS/Azure/Google Cloud SQL
Natural language to SQL – Ask questions, receive database query results
AES-256 encryption – Secure connections with read-only access requirement
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Free – $0: 1 chatbot, 20 queries/month, 5MB limit
Starter – $19-29/month: 2 chatbots, 1,500 queries/month, 30-day logs
Standard – $89-119/month: 4 chatbots, 7,500 queries/month, custom domain
Business – $399-799/month: 8 chatbots, 15,000 queries/month, priority support
Enterprise – Custom: Private cloud, dedicated support, AWS Marketplace
⚠️ User feedback – "Plans quite restrictive, credit limits reached sooner"
Seat-Based Pricing – ~$30 per user per month, predictable monthly costs
✅ Cost-Effective Small Teams – Affordable for teams under 50 users
⚠️ Large Team Costs – 100 users = $3,000/month, can scale expensively
Unlimited Content – Document/token limits not published, gated only by user seats
Free Trial + Enterprise – Hands-on trial available, custom pricing for large deployments
Standard: $99/mo – 60M words, 10 bots
Premium: $449/mo – 300M words, 100 bots
Auto-scaling – Managed cloud scales with demand
Flat rates – No per-query charges
⚠️ NO SOC 2, HIPAA, ISO 27001, GDPR certifications – Not for regulated industries
Private cloud deployments – Enterprise tier for data sovereignty
AES-256 encryption – Database connections with read-only access
AWS infrastructure – Data storage and processing on AWS
✅ GDPR Compliance – Germany-based, implicit EU data protection and regional sovereignty
✅ Enterprise Privacy – Data isolated per customer, encrypted in transit and rest
✅ No Model Training – Customer data not used for external LLM training
✅ Role-Based Access – Built-in controls, admins set document visibility per role
⚠️ Limited Certifications – On-prem or SOC 2/ISO 27001/HIPAA not publicly documented
SOC 2 Type II + GDPR – Third-party audited compliance
Encryption – 256-bit AES at rest, SSL/TLS in transit
Access controls – RBAC, 2FA, SSO, domain allowlisting
Data isolation – Never trains on your data
✅ denser-retriever – MIT-licensed, 261 GitHub stars, full RAG transparency
Docker Compose deployment – Local experimentation with Elasticsearch and Milvus
Validate benchmarks – Test embeddings, rerankers, chunking on own data
⚠️ Self-hosted "not production suitable" – Denser recommends managed SaaS
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Founded 2023 – Silicon Valley startup, ~4 employees (bootstrapped)
✅ Founder Zhiheng Huang – Former Amazon Kendra scientist, Amazon Q lead
70+ research papers – 14,000+ citations; BLSTM-CRF 5,400+ citations
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R A G-as-a- Service Assessment
✅ TRUE RAG PLATFORM – Hybrid retrieval with open-source transparency
Data source flexibility – Good (documents, websites, Google Drive, SQL)
LLM model options – Good (GPT-4o, Claude, multiple embeddings/rerankers)
✅ Open-source transparency – Excellent (MIT-licensed core, published benchmarks)
⚠️ Compliance & certifications – Poor (no SOC 2, HIPAA, ISO 27001)
Best for – Technical teams prioritizing retrieval accuracy and validation
⚠️ NOT TRUE RAG-AS-A-SERVICE – Standalone internal app, not API-accessible RAG platform
Turnkey Application – Self-contained Q&A tool vs developer-accessible RAG infrastructure
⚠️ No API Access – No REST API, SDKs, programmatic access unlike CustomGPT/Vectara
Closed Application – Web/desktop interface only, cannot build custom applications on top
SaaS vs RaaS – Software-as-a-Service (standalone app) NOT Retrieval-as-a-Service (API infrastructure)
Best Comparison Category – Internal search tools (Glean, Guru), not developer RAG platforms
Platform type – TRUE RAG-AS-A-SERVICE with managed infrastructure
API-first – REST API, Python SDK, OpenAI compatibility, MCP Server
No-code option – 2-minute wizard deployment for non-developers
Hybrid positioning – Serves both dev teams (APIs) and business users (no-code)
Enterprise ready – SOC 2 Type II, GDPR, WCAG 2.0, flat-rate pricing
vs CustomGPT – Superior retrieval transparency, SQL chat; gaps in compliance
vs Glean – Open-source vs proprietary, lower cost; lacks permissions-aware AI
✅ Unique strengths – Hybrid retrieval benchmarks, founder pedigree, SQL chat
Target audience – Developers building AI chatbots without strict compliance
Market Position – Turnkey internal knowledge search (Germany), not embeddable chatbot platform
Target Customers – Small-mid European teams needing GDPR compliance and simple deployment
Key Competitors – Glean, Guru, Notion AI; not customer-facing chatbots like CustomGPT
✅ Advantages – Simple scope, auto-sync, GDPR compliance, ~$30/user/month predictable pricing
⚠️ Use Case Fit – Perfect for <50 user teams, not API integrations or public chatbots
Market position – Leading RAG platform balancing enterprise accuracy with no-code usability. Trusted by 6,000+ orgs including Adobe, MIT, Dropbox.
Key differentiators – #1 benchmarked accuracy • 1,400+ formats • Full white-labeling included • Flat-rate pricing
vs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% faster
vs Botsonic/Chatbase – More file formats, source citations, no hidden costs
vs LangChain – Production-ready in 2 min vs weeks of development
✅ Hybrid retrieval – ES + Milvus vectors + XGBoost reranking
75.33 NDCG@10 on MTEB – vs 73.16 pure vector (3% improvement)
96.50% Recall@20 – Anthropic benchmark vs 90.06% baseline
Source citation – Visual PDF highlighting with page references
98.3% accuracy claimed – 1.2-second average response time
Conversational RAG – Context-aware search over enterprise documents with follow-up support
✅ Auto-Sync – Repositories sync automatically, changes reflected almost instantly
Document Formats – PDF, DOCX, PPT, TXT and common enterprise formats supported
⚠️ No Advanced Controls – Chunking, embedding models, similarity thresholds not exposed
⚠️ Limited Transparency – No citation metrics or anti-hallucination details published
Closed System – Optimized for internal Q&A, limited visibility into retrieval architecture
GPT-4 + RAG – Outperforms OpenAI in independent benchmarks
Anti-hallucination – Responses grounded in your content only
Automatic citations – Clickable source links in every response
Sub-second latency – Optimized vector search and caching
Scale to 300M words – No performance degradation at scale
Customer support chatbots – Website deployment with 24.8% conversion rate
✅ SQL database chat (unique) – Natural language queries against major databases
Technical documentation – Hundreds of thousands of pages indexed under 5 minutes
Multilingual support – 80+ languages with automatic detection
Developer-focused RAG – MIT-licensed denser-retriever for validation
✅ Internal Knowledge Search – Employees asking questions about company documents and policies
✅ Team Onboarding – New hires finding information without bothering colleagues
✅ Policy Lookup – HR, compliance, operational procedure retrieval for staff
✅ Small European Teams – GDPR-compliant internal search with EU data residency
⚠️ NOT SUITABLE FOR – Public chatbots, customer support, API integrations, multi-channel deployment
Customer support – 24/7 AI handling common queries with citations
Internal knowledge – HR policies, onboarding, technical docs
Sales enablement – Product info, lead qualification, education
Documentation – Help centers, FAQs with auto-crawling
E-commerce – Product recommendations, order assistance
Documentation – docs.denser.ai, retriever.denser.ai, GitHub READMEs
⚠️ Documentation fragmented – Information scattered across multiple sites
~4-person team – Impacts enterprise support capacity
Open-source community – 261 GitHub stars, 30 forks, MIT license
✅ Direct Support – Email, phone, chat with hands-on onboarding approach
✅ Quick Deployment – Minimal admin overhead, connect sources and start asking questions
⚠️ No Open Community – Closed solution, no plug-ins or user extensions
⚠️ No Developer Docs – No API documentation or programmatic access guides
Internal Roadmap – Updates from Pyx only, no user-contributed features
Documentation hub – Docs, tutorials, API references
Support channels – Email, in-app chat, dedicated managers (Premium+)
Open-source – Python SDK, Postman, GitHub examples
Community – User community + 5,000 Zapier integrations
Limitations & Considerations
⚠️ No compliance certifications – Missing SOC 2, HIPAA, ISO 27001, GDPR
⚠️ Small team (~4 people) – Potential scaling constraints for enterprise
⚠️ Heavy Zapier dependency – No native Slack, Teams, CRM integrations
⚠️ Fragmented documentation – Scattered across docs, retriever docs, GitHub
⚠️ User feedback – "Plans restrictive, credit limits reached sooner"
⚠️ No Public API – Cannot embed or call programmatically, standalone UI only
⚠️ No Messaging Integrations – No Slack, Teams, WhatsApp or chat platform connectors
⚠️ Limited Branding – Minimal customization, not white-label solution for public deployment
⚠️ No Advanced Controls – Cannot configure RAG parameters, model selection, retrieval strategies
⚠️ Seat-Based Scaling – Expensive for large orgs vs usage-based pricing models
✅ Best For – Small European teams (<50 users) prioritizing simplicity and GDPR over flexibility
Managed service – Less control over RAG pipeline vs build-your-own
Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source
Real-time data – Requires re-indexing; not ideal for live inventory/prices
Enterprise features – Custom SSO only on Enterprise plan
AI agent capabilities – Process data for intelligent automation with customization
Multi-platform deployment – Launch across websites and messaging with single line
Adaptive learning – Chatbot learns over time using conversation analysis
24/7 availability – Smart AI support with instant answers
⚠️ NO Agent Capabilities – No autonomous agents, tool calling, or multi-agent orchestration
Conversational Search Only – Context-aware dialogue for Q&A, not agentic or autonomous behavior
Basic RAG Architecture – Standard retrieval without function calling, tool use, or workflows
⚠️ No External Actions – Cannot invoke APIs, execute code, query databases, or interact externally
Internal Knowledge Focus – Employee Q&A about documents, not task automation or workflows
Custom AI Agents – Autonomous GPT-4/Claude agents for business tasks
Multi-Agent Systems – Specialized agents for support, sales, knowledge
Memory & Context – Persistent conversation history across sessions
Tool Integration – Webhooks + 5,000 Zapier apps for automation
Continuous Learning – Auto re-indexing without manual retraining
Conversational interface – Chat with customers in friendly manner
Business knowledge integration – Trained on documents, websites, Google Drive
Multi-language support – 80+ languages with automatic detection
Lead capture – Integrated forms (name, email, company, role)
Human handoff – Triggers on complexity with Zendesk tickets
Conversational Search – Context-aware Q&A over enterprise documents with follow-up questions
⚠️ Internal Focus – Designed for knowledge management, no lead capture or human handoff
Multi-Language – Likely supports multiple languages, though not a headline feature
⚠️ Basic Analytics – Stores chat history, fewer business insights than customer-facing tools
✅ #1 accuracy – Median 5/5 in independent benchmarks, 10% lower hallucination than OpenAI
✅ Source citations – Every response includes clickable links to original documents
✅ 93% resolution rate – Handles queries autonomously, reducing human workload
✅ 92 languages – Native multilingual support without per-language config
✅ Lead capture – Built-in email collection, custom forms, real-time notifications
✅ Human handoff – Escalation with full conversation context preserved
Customization & Flexibility ( Behavior & Knowledge)
Behavior customization – Define name, tone, response preferences
File support – PDF, DOCX, XLSX, PPTX, TXT, HTML, CSV, XML
Website crawling – Train bot by crawling URLs for knowledge base
Easy knowledge updates – Add documents, re-crawl, update without rebuild
Flexible deployment – Web widget, dashboard, or API integration
✅ Auto-Sync Updates – Knowledge base updated without manual uploads or scheduling
⚠️ No Persona Controls – AI voice stays neutral, no tone or behavior customization
✅ Access Controls – Strong role-based permissions, admins set document visibility per user
Closed Environment – Great for content updates, limited for AI behavior or deployment
Live content updates – Add/remove content with automatic re-indexing
System prompts – Shape agent behavior and voice through instructions
Multi-agent support – Different bots for different teams
Smart defaults – No ML expertise required for custom behavior
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✅ Direct Support – Email, phone, chat with hands-on onboarding approach
⚠️ No Open Community – Closed solution, no plug-ins or user-built extensions
Internal Roadmap – Product updates from Pyx only, no community marketplace
Quick Setup Focus – Emphasizes minimal admin overhead for internal knowledge search
Comprehensive docs – Tutorials, cookbooks, API references
Email + in-app support – Under 24hr response time
Premium support – Dedicated account managers for Premium/Enterprise
Open-source SDK – Python SDK, Postman, GitHub examples
5,000+ Zapier apps – CRMs, e-commerce, marketing integrations
Additional Considerations N/A
✅ No-Fuss Internal Search – Employees use without coding, simple deployment for teams
⚠️ Not Public-Facing – Not ideal for customer chatbots or developer-heavy customization
Siloed Environment – Single AI search environment, not broad extensible platform
Simpler Scope – Less flexible than CustomGPT, but faster setup for internal use
Time-to-value – 2-minute deployment vs weeks with DIY
Always current – Auto-updates to latest GPT models
Proven scale – 6,000+ organizations, millions of queries
Multi-LLM – OpenAI + Claude reduces vendor lock-in
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⚠️ Undisclosed LLM – Likely GPT-3.5/GPT-4 but model details not publicly documented
⚠️ No Model Selection – Cannot switch LLMs or choose speed vs accuracy configurations
⚠️ Opaque Architecture – Context window size and capabilities not exposed to users
Simplicity Focus – Hides technical complexity, users ask questions and get answers
⚠️ No Fine-Tuning – Cannot customize model on domain data for specialized responses
OpenAI – GPT-5.1 (Optimal/Smart), GPT-4 series
Anthropic – Claude 4.5 Opus/Sonnet (Enterprise)
Auto-routing – Intelligent model selection for cost/performance
Managed – No API keys or fine-tuning required
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✅ GDPR Compliance – Germany-based with implicit EU data protection compliance
✅ German Data Residency – EU storage location for regional data sovereignty requirements
✅ Enterprise Privacy – Customer data isolated, encrypted in transit and at rest
✅ Role-Based Access – Built-in controls, admins set document visibility per user
⚠️ Limited Certifications – SOC 2, ISO 27001, HIPAA not publicly documented
SOC 2 Type II + GDPR – Regular third-party audits, full EU compliance
256-bit AES encryption – Data at rest; SSL/TLS in transit
SSO + 2FA + RBAC – Enterprise access controls with role-based permissions
Data isolation – Never trains on customer data
Domain allowlisting – Restrict chatbot to approved domains
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Seat-Based Pricing – ~$30 per user per month
✅ Small Team Value – Affordable for teams under 50 users, predictable costs
⚠️ Scalability Cost – 100 users = $3,000/month, expensive for large organizations
Unlimited Content – No published document limits, gated only by user seats
Free Trial + Enterprise – Evaluation available, custom pricing for volume discounts
Standard: $99/mo – 10 chatbots, 60M words, 5K items/bot
Premium: $449/mo – 100 chatbots, 300M words, 20K items/bot
Enterprise: Custom – SSO, dedicated support, custom SLAs
7-day free trial – Full Standard access, no charges
Flat-rate pricing – No per-query charges, no hidden costs
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