Terraform-style control for AI agents

AI agents, shipped like infrastructure.

Bandito AI is a declarative control plane for AI systems. Define agents as code, diff changes, promote dev to prod, and stay audit-ready.

Reproducibility

Pin models, tools, prompts

Diffable changes

git diff for AI behavior

Durable state

Resume, replay, and audit runs

Observability

Trace every run, tool call, outcome

Portability

Swap models and runtimes cleanly

Governance

Policies, audit trails, rollbacks

bandito.yaml plan
version: 1
project: bandito-demo
providers:
  openai:
    type: openai
    model: gpt-4.1
agents:
  support_bot:
    provider: openai
    model: gpt-4.1
    temperature: 0.2
    system_prompt: "You are a helpful support agent."
    guardrails:
      pii: true
      jailbreak_protection: true
    deployment:
      environment: prod
Bandito AI mark

AI Agents as Code, done with discipline.

The problem

AI systems are shipped like demos.

Teams hack together agents with prompt glue, hidden configs, and ad-hoc scripts. When behavior changes, nobody can explain why.

Drift and chaos

Same agent behaves differently across environments.

No diff, no rollback

Changes land without review or traceability.

Shadow AI

Tools and data paths are scattered and ungoverned.

Compliance pressure

Audit questions arrive after production incidents.

The solution

Bandito makes AI behave like infrastructure.

Define agents declaratively, compile to your runtime, and ship with the same rigor you use for Terraform, Helm, or GitOps.

  • Declarative agent specs
  • Environment promotion: dev -> staging -> prod
  • Provider-neutral control plane with policy + audit
  • Durable agent state for recovery + replay
  • Bandito Cloud for Agents-as-a-Service (AaaS)

Plan

Preview changes before they hit production.

Apply

Write state, lock versions, and deploy safely.

Run

Execute agents with reproducible configs.

Govern

Guardrails, PII policy, and audit trails.

How it works

Three steps to infra-grade agents.

01

Define

Write bandito.yaml with model, tools, memory, and policy.

02

Plan

See a diff of what changes and why.

03

Apply and run

Promote environments and execute safely.

bandito init bandito validate bandito plan bandito apply bandito run

Stack

Bring your runtime. Bandito stays neutral.

Compile into LangChain or LangGraph, plug in your vector DBs and data sources, keep policy centralized, or run on Bandito Cloud.

OpenAI LangChain LangGraph Bandito Cloud Pinecone Weaviate Snowflake Postgres Custom tools

Ideal users

Built for platform and AI infra teams.

If your org has more than one agent in production, Bandito keeps them aligned, auditable, and repeatable.

Platform teams

Standardize deployment, guardrails, and ownership.

AI architects

Define the control plane before sprawl sets in.

Security and compliance

Audit-ready logs and policy enforcement.

Bandito AI is seeking design partners.

Join the first cohort to shape the spec, influence integrations, and lock in early access.