What is Botlit and who is it for?

Botlit[1] is an enterprise agentic AI platform designed to build, govern, and ship AI agents that run on your own models and answer from your organization's knowledge. Rather than acting as a standalone chatbot builder, Botlit provides a centralized control plane where user-facing bot apps route requests to specialized AI agents with built-in version control, workspace-level RBAC, and per-execution audit logging.

Key capabilities outlined across Botlit Features[2] include:

• Bring Your Own Model (BYOM): Register 11 LLM provider types (including OpenAI, Anthropic, Google, Groq, Azure OpenAI, and AWS Bedrock) using vaulted credentials.
• Knowledge Bases & RAG: Ingest documents into vector collections with semantic search validation.
• Multi-Channel Deployment: Connect bots to Slack, Microsoft Teams, Discord, WhatsApp, and webhooks.
• Observability & Tooling: Inspect token usage and spend per run via the Execution Ledger and Run Costs[3], and connect external capabilities through MCP Tool Servers[4].

Concept illustration(opens in a new tab) Illustration of the concept, not a screenshot of the actual product — Execution Ledger and Run Costs[3]

Who is Botlit for?

According to Botlit's overview[1], the platform serves five primary groups:

• Enterprises (1000+): Organizations requiring governed, auditable agent fleets with enforced RBAC, policy guardrails, and private knowledge.
• Agencies & Consultants: Teams building and operating branded AI assistants for multiple clients in isolated workspaces.
• Mid-Market Companies (100–1000): Teams automating support, IT, and HR inquiries without staffing an internal ML team.
• Startups & Scale-ups: Fast-moving engineering teams shipping in-product AI assistants via an API-first approach.
• Healthcare Organizations: Providers seeking member-facing assistants with strict content and data-retention controls.

To see real-world scenarios, explore Botlit Use Cases[5] or sign up for early access on the Botlit Waitlist[6].