The enterprise agentic AI platform
Build, govern, and ship AI agents that run on your own models, answer from your own knowledge, and live inside your workspace's security model — with versioning, per-execution cost audit, and enforced RBAC built in.
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Everything you need to run an agent workforce
From the first bot app to governed, audited agents on your own channels
Agents with Version Control
Build agents with system prompts and model bindings, then publish versions with changelogs — and roll back when a prompt change regresses behavior.
Bring Your Own Model
Register 11 LLM provider types — OpenAI, Anthropic, Google, Groq, Azure OpenAI, AWS Bedrock, and more — with vaulted keys and connection tests.
Knowledge Bases
Ingest documents, chunk and embed them into per-KB vector collections, and validate retrieval quality with semantic search before launch.
Channel Deployment
Connect Slack, Teams, Discord, WhatsApp, and webhooks. Inbound messages acknowledge instantly while agents respond in the background.
Governance First
Enforced RBAC on every API operation, policy definitions across seven types, audit trails, and machine credentials for pipelines.
Workflow Orchestration
The embedded FluidGrids visual builder composes agents into larger automations alongside templates, the package store, and prompt templates.
Why Botlit
Problems we solve
Agentic AI projects stall on the same five bottlenecks. Botlit removes them.
Agent prompts change constantly with no way to recover
Botlit versions every agent and app. Iterate in draft, publish with a changelog, and roll back the moment a prompt tweak regresses behaviour.
Read the storyYour AI stack is locked to one model or provider
Bring your own keys across 11 provider types — OpenAI, Anthropic, Google, Groq, Azure OpenAI, AWS Bedrock, and more — with connection tests and per-model bindings.
Read the storyNo visibility into what agents actually cost or do
Every execution records status, input/output, tokens, and cost. Per-agent statistics turn "what did the bot spend?" into a query instead of a finance project.
Read the storyGovernance is a promise, not a structure
Every API operation is RBAC-governed, workspaces isolate tenants, and machine credentials give pipelines governed access.
Read the storyKnowledge lives in documents agents cannot reliably use
Managed knowledge bases with your choice of chunking strategy, per-KB vector collections, and semantic search validation before anything goes live.
Read the storyFrom idea to a governed agent — in one loop
Build, ground, deploy, govern. Each step is real in the platform today.
Build agents from templates or from scratch
A bot app is the user-facing front door; agents are the specialists behind it. Give each agent a system prompt and a model binding, link apps to agents with a routing strategy, then publish a version with a changelog.
- Start from a template or build an agent from scratch
- App → agent routing: single, round-robin, intelligent, or custom
- Publish versions with changelogs — and roll back a bad change
- Organize the fleet with buckets and visibility controls
Who runs an agent workforce on Botlit
Five teams, one governed control plane
Agencies & consultants
Build and operate branded AI assistants for many clients from one platform, each walled off in its own workspace.
Enterprises (1000+)
Governed, auditable agent deployment at scale — RBAC, policies, a multi-provider model strategy, and private knowledge.
Healthcare organizations
Member-facing assistants with strict data-retention and content policies. HIPAA posture is on the compliance roadmap.
Mid-market (100–1000)
Deflect support volume and automate internal helpdesk and HR Q&A — without standing up an ML team.
Startups & scale-ups
Ship an in-product AI assistant fast, with API-first access through the public API.
Your providers, your channels
Bring the model providers you already trust and meet people where they already are.
Trust by construction, not by faith
The unglamorous things that make agents deployable: permissions, audits, versions, and vaulted credentials — built in, not bolted on.
RBAC on every operation
Every API operation carries an RBAC rule, composed into the platform API and enforced on every request.
Per-execution audit & cost
Every run is recorded with status, input/output, token counts, and cost — plus per-agent and per-app stats.
Versioning & rollback
Agents and apps are versioned with publish and changelogs, so a regressing prompt change is one rollback away.
Credential vaulting
LLM keys resolve through the platform integrations service and are vaulted — never stored in an agent definition.
Workspace tenancy
Every agent, knowledge base, and conversation is workspace-scoped; the tenant is inferred automatically.
A2A trust model
A registry of known agents with explicit trust levels — unverified, verified-publisher, or internal.
Don't want to build it alone?
Our team helps you adopt and get more from Botlit — and delivers done-for-you outcomes powered by the platform.
Custom agent & bot development
We design your bot apps and the specialist agents behind them — versioned, routed, and ready to roll back.
Knowledge base & RAG setup
We turn your documents into a managed retrieval corpus and prove its quality before launch.
Channel integration
We connect your agents to web, Slack, Teams, WhatsApp, voice, and webhooks — end to end.
Managed agents & operations
We run your agent workforce — monitoring, tuning, and versioning — so you get outcomes without the ops load.
Editions for every stage
From a first bot app to a governed fleet across the org.
Free
Try the platform
- Capped apps & agents
- Starter execution quota
- A few knowledge bases
- Bring your own model keys
Pro
Run a real workload
- Generous app & agent caps
- High monthly token quota
- Many KBs + advanced RAG
- MCP servers & A2A collaboration
Enterprise
Govern at scale
- Unlimited apps, agents & KBs
- Multi-agent orchestration
- SSO/SAML, custom branding, SLA
- Custom quotas & support
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