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TASKINGAI

BaaS platform for building and deploying LLM-powered AI agents at scale

Apache-2.0

ABOUT

Building production-grade LLM agents requires juggling model integrations, tool management, RAG pipelines, session state, and multi-tenant deployments — each demanding custom infrastructure. TaskingAI solves this with a BaaS architecture that decouples AI logic from client development: developers manage agents, tools, and knowledge bases through a unified console and API, while client SDKs handle only the frontend. The platform supports both stateful (conversation management) and stateless (chat completion) modes, built-in multi-tenancy, and one-click deployment from prototype to production.

INSTALL
pip install taskingai

INTEGRATION GUIDE

1. Deploy multi-tenant AI agent applications where each customer needs isolated configurations, tools, and memory 2. Build RAG-powered assistants with integrated document retrieval and customizable chunking strategies 3. Manage hundreds of LLM model providers through a single unified API with automatic failover between providers 4. Create tool-augmented agents with built-in plugins for web search, code execution, and custom API integrations 5. Prototype and productionize agent workflows through an intuitive console with one-click deployment scaling

TAGS

pythonagentsllmbaasragmulti-tenantapibackendorchestrationtools
TaskingAI — AI Tool | Agentic AI For Good