🧠 IAToolkit — Open-Source Framework for Real-World AI Assistants
Build private, production-grade AI assistants that run entirely inside your environment and speak the language of your business.
IAToolkit is not a demo wrapper or a prompt playground — it is a full architecture for implementing intelligent systems that combine LLMs, SQL data, internal documents, tools, workflows, and multi-tenant business logic.
🚀 Why IAToolkit?
Modern AI development is fragmented: LangChain handles chains, LlamaIndex handles documents,
your backend handles SQL, your frontend handles chats, and your devs glue everything together.
IAToolkit brings all of this into one unified, production-ready framework.
It focuses on:
- real-world data (SQL + documents)
- real workflows (LLM tools + python services)
- real multi-tenant architecture (1 company → many companies)
- real constraints (security, reproducibility, governance)
- real deployment (your servers, your infrastructure)
IAToolkit lets you build the assistant that your organization needs — not a generic chatbot.
🧩 Architecture in a Nutshell
IAToolkit is a structured, layered framework, with a clear separation of concerns.
✔ Interfaces
Chat UI, REST API, auth, sessions, JSON/HTML responses.
✔ Intelligence Layer
Core logic: prompt rendering, SQL orchestration, RAG, LLM tool dispatching.
✔ Execution Layer
Python services that implement real workflows: querying data, generating reports, retrieving documents, executing business logic.
✔ Data Access
A clean repository pattern using SQLAlchemy.
✔ Company Modules
Each company has:
- its own
company.yaml
- its own prompts
- its own tools
- its own services
- its own vector store & SQL context
This modularity allows true multi-tenancy.
🔌 Connect to Anything
IAToolkit integrates naturally with:
- SQL databases (PostgreSQL, MySQL, SQL Server, etc.)
- Document retrieval (PDF, text, embeddings)
- External APIs
- Internal microservices
- Custom Python tools
It also includes a production-grade RAG pipeline, combining:
- embeddings
- chunking
- hybrid search
- SQL queries + document retrieval
- tool execution
Everything orchestrated through the Intelligence Layer.
🏢 Multi-Tenant Architecture
A single installation of IAToolkit can power assistants for multiple companies, departments, or customers.
companies/
company_a
company_b
company_c
Each Company is fully isolated:
- prompts
- tools
- credentials
- documents
- SQL contexts
- business rules
This makes IAToolkit ideal for SaaS products, agencies, consultancies, and organizations with multiple business units.
🆓 Community Edition vs Enterprise Edition
IAToolkit follows a modern open-core model:
🟦 Community Edition (MIT License)
- Full Open-Source Core
- SQL + Basic RAG
- One Company
- Custom Python tools
- Self-managed deployment
Perfect for developers, small teams, single-business use cases, and experimentation.
🟥 Enterprise Edition (Commercial License)
- Unlimited Companies (multi-tenant)
- Payment services integration
- Enterprise Agent Workflows
- SSO integration
- Priority support & continuous updates
- Activation via License Key
👉 Licensing information:
🧩 Who Is IAToolkit For?
- Companies building internal “ChatGPT for the business”
- SaaS products adding AI assistants for multiple customers
- AI teams that need reproducible prompts and controlled tools
- Developers who want real workflows, not toy demos
- Organizations requiring privacy, security, and self-hosting
- Teams working with SQL-heavy business logic
- Consultancies deploying AI for multiple clients
⭐ Key Differentiators
- prioritizes architecture-first design, not chains or wrappers
- supports multi-company out of the box
- integrates SQL, RAG, and tools into a single intelligence layer
- keeps business logic isolated inside Company modules
- runs entirely on your own infrastructure
- ships with a full web chat, and API.
- is built for production, not prototypes
📚 Documentation
🤝 Contributing
IAToolkit is open-source and community-friendly.
PRs, issues, ideas, and feedback are always welcome.
⭐ Support the Project
If you find IAToolkit useful, please star the GitHub repo — it helps visibility and adoption.
