Control plane for AI-powered software delivery

Your agents act. You decide the rules.

AI agents push code, open PRs, and run commands. Sequenceware gives you centralized visibility, policy enforcement, and a full audit trail across every agent and every tool.

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Sequenceware — Live Dashboard

Live

Active Runs

Pending

156

Events Today

Blocked

Live Event StreamLast 5 events

fs.writeFile('/etc/config')file_system_accessBLOCKED

api.call('payments.create')payment_opsALLOWED

db.query('DROP TABLE users')destructive_opsBLOCKED

git.push('main', '--force')code_deployPENDING

http.get('internal-api/users')network_accessALLOWED

Native integrations

Claude Code

Cursor

Windsurf

GitHub

Slack

TypeScript and Python SDKs work with any agent framework — LangChain, CrewAI, OpenAI Agents, Vercel AI SDK, and more.

The Platform

AI agents are shipping code. Who's watching?

Whether you have 1 agent or 50, the risk is the same: autonomous actions without oversight on critical systems. Agents break dependencies, saturate pipelines, and generate changes with no audit trail. Sequenceware sits between your agents and your software factory — an intelligent firewall that decides which changes pass, under what conditions, and when human review is mandatory.

AI Agents

POST /events

Sequenceware

GitHub

Governance Flow

Policy Engine: Repo = "frontend"PASS

Risk: Minor UI changesPASS

HITL required: NoSKIPPED

Policies

Human-in-the-Loop

Auto-block

Audit Trail

Integration

Integrate in minutes

A few lines of SDK. Full governance. Your agents can start sending events in minutes.

import { SequencewareClient } from "@sequenceware/sdk";

const sw = new SequencewareClient({ apiKey: "sw_..." });
const run = await sw.startRun({ agent: "my-agent" });
await sw.trackToolCall(run, "create_pr", { title: "Fix auth" });

How It Works

From intent to execution, governed

A secure, structured, and auditable workflow before every action on your systems.

Agent proposes

Through the SDK or a Claude Code hook, the agent reports its intent — open a PR, modify CI, deploy — in a single API call.

Policies decide

The engine evaluates against your rules in real time. Block, approve, or escalate to a human reviewer. Strictest action wins.

Action executes (or doesn't)

Authorized changes proceed to your repository. Blocked ones don't. Every decision and its reasoning is recorded in the audit trail.

Real-time

Policy evaluation

Condition operators

0 lines

Hook-based setup

Full

Audit trail

“Every team deploying AI agents told us the same thing: we have no idea what our agents did last Tuesday.”
NC
Nacho Cortes
Founder, Sequenceware

Frequently Asked Questions

Doesn't this slow down agents?

Policy evaluations are synchronous and lightweight — they add minimal latency. The only case where there's visible latency is when the policy requires human approval — and that's exactly the point.

Do we have to change how we build agents?

A few SDK calls — startRun, trackToolCall, completeToolCall, completeRun — and you're set. For Claude Code and MCP agents, enforcement happens at the hook level with zero code changes.

What if a policy blocks something it shouldn't?

Before activating any policy you can test it in the policy simulator: run your scenario and see the exact result. And you can always switch from 'block' to 'require_approval' so a human reviews instead of blocking automatically.

Can we pass compliance audits with this platform?

Sequenceware generates an audit record of which agent executed each tool call, which policy governed that action, and which user approved or rejected it. It's the foundation you need to respond to internal or external audits.

What are your agents doing right now with no controls?

Whether you have agents in production or are planning to adopt them, Sequenceware adds visibility, guardrails, and traceability from day one.

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