Key Features
AI & LLM Support
- Multi-Provider LLM Support - Azure AI, OpenAI, Anthropic, Google Gemini, xAI (Grok), DeepSeek, Perplexity, Mistral, Cohere, Groq, AWS Bedrock, Ollama, Fireworks AI, Together AI, DeepInfra, Prem AI
- LangChain Integration - Advanced orchestration with visual flow designer
- Model Context Protocol (MCP) - Extensible tool integration framework
- Streaming Responses - Real-time SSE streaming for all providers
- Memory System - Persistent conversation memory with Mem0 integration
Enterprise Platform
- AI-Powered Intranet - Organize managed and personal AI chats into navigable pages and sections, creating a structured knowledge hub for your organization
- Categorized Chats & Prompts - Scalable system of secure, role-gated chats and prompt templates organized by department, function, or topic
- Microsoft Entra ID Authentication - SSO with Azure AD groups and individual user principals
- Role-Based Access Control - Owners, contributors, and users with ACL inheritance at app, page, and entity levels
- Personal & Shared Workspaces - Private chats alongside collaborative shared chats with fine-grained permissions
- Audit Logging - Comprehensive chat logging, feedback tracking, and user activity monitoring
- Data Isolation - Scoped data with Cosmos DB partitioning and per-user storage containers
- Embedded Agent Mode - Embed any chat as a standalone agent widget via iframe in external apps or portals
Data Connections
- Natural Language SQL - Query live databases conversationally across PostgreSQL, SQL Server, MySQL, MariaDB, Oracle, IBM DB2, SQLite, SAP HANA, DuckDB, Supabase, Snowflake, Databricks, BigQuery, Athena, ClickHouse, Trino, Azure Data Explorer, Cosmos DB, MongoDB, DynamoDB, Cassandra, CouchDB, and Firebase (Firestore)
- Query Result Caching - 5-minute cache for frequently asked questions
- Query Explanation Mode - Explain how a query works without executing it
- Multi-turn Context - Follow-up questions reference previous queries (session-based)
- SharePoint Integration - Index and search SharePoint document libraries with optional document-level ACL
- Azure AI Search - Full-text, vector, and semantic hybrid search with managed identity support
- Vector Stores - Pinecone, Qdrant, Weaviate, Chroma, OpenSearch, Elasticsearch, Redis, pgvector, Milvus, MongoDB Atlas Vector Search, Vertex AI Vector Search, Amazon Kendra, Oracle Vector Search (23ai), Vespa, LanceDB, and Marqo
- Web Search RAG - Ground chat responses in real-time web results from Tavily, Perplexity, Brave, Exa, or SerpAPI with domain filtering and pinned reference pages
- Flow Retriever - Use headless Flow Designer flows as virtual data sources in the RAG pipeline — query databases, APIs, or any custom logic and merge results alongside traditional search
Flow Orchestrator
- Visual Flow Designer - Build complex multi-step AI agent workflows with a drag-and-drop visual editor
- Human-in-the-Loop - Agents can pause execution and request input from specific users or groups, with responses collected via the app, email, Microsoft Teams, or Slack
- Assignments - Push configured chats and flows to individuals or groups, track completion with configurable criteria, enforce deadlines, and support delegation and retry budgets
- Multi-Channel Notifications - Reach users through email (SendGrid, Azure Communication Services), Microsoft Teams, and Slack with actionable links back to pending tasks
- Ephemeral Forms - Agents dynamically generate structured input forms at runtime, collecting validated user data mid-flow
- ReAct Agents - Autonomous reasoning-and-acting agents with tool calling, web search, and MCP server integration
- Streaming Execution - Real-time SSE streaming of agent reasoning steps and tool outputs
User Experience
- Prompt Library - Personal and organizational prompt templates with variables, system sources, and conditional logic
- Rich Content Rendering - Markdown, code syntax highlighting, LaTeX math (KaTeX), Mermaid diagrams, Recharts visualizations
- File Upload - Azure Blob storage with automatic document indexing
- Favorites & Navigation - Customizable pages and sections with drag-and-drop ordering
- Feedback System - Thumbs up/down with detailed feedback forms and admin review
Tech Stack
Backend
- Runtime: Node.js 24+
- Framework: Express.js
- Language: TypeScript
- AI/ML: LangChain, MCP SDK
- Database: Azure Cosmos DB
- Search: Azure AI Search
- Storage: Azure Blob Storage
- Auth: MSAL, Microsoft Graph
Frontend
- Framework: React 18
- Build Tool: Vite
- UI Library: Material-UI (MUI)
- State: Redux Toolkit
- Forms: React Hook Form + Zod
- Rendering: Markdown, KaTeX, Mermaid, Recharts
Infrastructure
- Hosting: Azure App Service
- Auth: Microsoft Entra ID
- CI/CD: GitHub Actions
Internationalization
The UI supports 8 languages out of the box, selectable per user:
Administrators can manage translations via Admin → Translations ([
#/admin/translations], setting key translations).
Scripts
Testing
Findable uses Vitest for unit, component, and server-integration tests, organized as three projects in a single workspace.vitest.workspace.ts defines three projects so each test runs under the right environment:
The
@findable/shared import alias resolves to shared/src during tests (not the built shared/dist), so tests don’t require a pre-build step. Vitest’s esbuild compiles TS on the fly.