pip install conduct-cli
conduct login
conduct sync

Every Claude Code, Cursor, Copilot, and Codex session on that machine is now governed. Blocks, warnings, and a hash-chained audit trail show up at conductai.ai.

Prefer to self-host?

git clone https://github.com/sseshachala/conductai && cd conductai && docker compose up
# API: localhost:8000  ·  Canvas UI: localhost:3000

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What Conduct is

A control plane for AI agents. One policy decides block / warn / audit / inject for every LLM call, every shell tool, every MCP invocation, before the action runs. Same policy applies to a scheduled agent, a developer running Cursor, and a chat session on the platform.

Three surfaces, one policy:

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Ask Lens

Lens is the chat surface for the whole platform. One input covers Guard activity, workflow state, compliance status, agent spend. Answers come from your workspace data, not a general model. Ask "who got blocked today" and get a table with per-row drilldown links. Lens itself runs through Guard, so the assistant is bound by the same rules as the agents it reports on.

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Governance, not observability

Runtime firewalls like Straiker and Lakera tell you what an agent did. Conduct decides what it can do.

Three properties make the audit trail hold up in a room with an auditor:

1. Signed config. Every workspace signs its active policy set. Every Guard check verifies the signature before enforcing. A tampered pack is rejected before it can decide anything.
2. Hash-chained audit. Every decision appends to a SHA-256 chain rooted at workspace genesis. Missing or altered entries break the chain. Verifiable in one click.
3. Policy-first, not detection-first. Rules decide before the action runs, with structured reasons. Not anomaly scoring after the fact.

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Start free with Discovery

Discovery mode is read-only visibility into every AI action your team takes for 14 days. No policy to author, no upstream install, no cost. When you see something worth blocking, promote a rule from what Discovery already saw.

→ conductai.ai/sign-up

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Router — one endpoint for any SDK

curl https://api.conductai.ai/proxy/anthropic/v1/messages \
  -H "Authorization: Bearer cond_agt_..." \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-sonnet-4-6","max_tokens":1024,"messages":[{"role":"user","content":"Hello"}]}'

Every request runs through Guard (policy, budget, audit) before it reaches the upstream provider. Works with any SDK that speaks the provider's HTTP API.

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What ships in this repo

20+ compliance packs out of the box: OWASP, SOC 2 CC7.3, HIPAA §164.312, PCI DSS 4.0, EU AI Act Art. 15/16, NIST AI RMF, ISO 42001, plus Python, Node, and Terraform.

22 pre-built playbooks: issue-to-PR, code review, incident response, prod deploy gate, CI/CD triage, security scanner triage, Slack digest. One YAML file each. Edit and run.

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Architecture at a glance

   Developer / agent                     Guard control plane
   ─────────────────                     ───────────────────
   Claude Code   ──┐                     ┌── Canvas UI (Next.js)
   Cursor        ──┤   CLI hook  ────►   ├── FastAPI + policy engine
   Copilot       ──┤   (cond_cli)        ├── Postgres (state, audit)
   Codex         ──┘                     ├── Redis (workers, queues)
                     ┌──── MCP  ────►    └── Hash chain (SHA-256)
   Any SDK       ────┤
   (Anthropic,       └── Router ────►    Upstream provider (Anthropic,
    OpenAI,             /proxy/*         OpenAI, Perplexity, ...)
    Perplexity)

Guard checks fire at three chokepoints:

• CLI hook — every Claude Code / Cursor / Copilot / Codex tool call.
• MCP layer — every MCP tool invocation.
• Router — every LLM call by any SDK.

One policy, three enforcement surfaces.

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Deployment

• Self-host with docker compose — the command above. Runs everything locally.
• Self-host on Kubernetes — deployment templates ship in issue #1149.
• Hosted — conductai.ai. Free tier includes Discovery; paid tiers unlock enforcement + Router + hash-chain verification API.

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Security & Trust

• SECURITY.md — vulnerability reporting policy, scope, coordinated disclosure, and safe harbor.
• Threat model — system context, trust boundaries, attacker goals, mitigations, and residual risks.
• Policy decision contract — guard_check decision semantics and fail-mode behavior.
• Audit log verification — independent prev_hash/entry_hash chain verification procedure and example script.
• API versioning — proxy/MCP compatibility, deprecation windows, and OpenAPI publication guidance.

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License

Apache License 2.0 — the entire repository, including the CLI, Guard, Router, Agent Booster, playbooks, and packs.

• Free for commercial and non-commercial use, modification, and redistribution.
• Includes an explicit patent grant from all contributors (Apache 2.0 §3).
• Trademark rights are not granted; see NOTICE — "Conduct", "Conduct AI", and "Conduct Guard" remain trademarks of Conduct AI.
• Redistribution must preserve the LICENSE and NOTICE files.

The hosted control plane at conductai.ai (canvas UI, team RBAC, marketplace, managed Guard) is a commercial offering built on top of this repository.

For enterprise support, indemnification, or licensing questions, email hello@conductai.ai.

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Contributing

We accept bug reports, docs fixes, new playbooks, new packs, tests, and code. Read CONTRIBUTING.md first.

• Everyone participating agrees to the Code of Conduct.
• Security vulnerabilities: don't open a public issue. See SECURITY.md.
• Anything else: GitHub Discussions or SUPPORT.md.

Links

• Product: conductai.ai
• Guard landing: conductai.ai/guard
• Router landing: conductai.ai/router
• Docs: conductai.ai/docs
• Discussions: github.com/sseshachala/conductai/discussions
• Changelog: CHANGELOG.md + Releases
• Book a demo: cal.com/sudhi-seshachala-pks7pd

⭐ If Conduct saves your team time, star it — it helps other teams find it.