Skip to content
Sequenceware
Control plane for AI-powered software delivery

Your agents act. You decide what they're allowed to do.

You have AI agents pushing code, opening PRs, and running commands. Today you have no centralized way to know what they did, why, or who approved it. Sequenceware is the layer that answers those questions — across every agent and every tool.

For Platform Engineers and Engineering Managers operating AI agents in production

Pre-merge policies
Automatic blocking
Full traceability
Human-in-the-loop
Sequenceware — Live Dashboard
Live
24
Active Runs
3
Pending
156
Events Today
7
Blocked
Live Event StreamLast 5 events
fs.writeFile('/etc/config')BLOCKED
api.call('payments.create')ALLOWED
db.query('DROP TABLE users')BLOCKED
git.push('main', '--force')PENDING
http.get('internal-api/users')ALLOWED

Works with the tools you already use

LangChainCrewAIOpenAI AgentsAnthropicVercel AI SDK

Your agents already know how to code. The challenge is governing them.

Whether you have 1 agent or 50, the risk is the same: autonomous actions without oversight on critical systems. The bottleneck is no longer generating changes — it's validating them.

Shadow AI in your repos

Agents operating without oversight. They break dependencies, ignore architecture policies, and generate tech debt that's hard to trace back.

Noise in PRs and CI/CD

Your pipelines get saturated validating low-quality auto-generated code, blocking your human team's releases.

Compliance risk

Without an immutable record of which agent did what and who authorized it, you can't respond to an audit or guarantee security.

We're not another agent. We're the layer that governs them.

Your pipelines weren't designed for autonomous agents. Sequenceware closes the gap between AI-generated code and your existing infrastructure.

Coding Agents

Copilots and autonomous agents (Devin, Sweep, etc.) that decide and execute technical work at machine speed.

FOCUS: Execution & Generation

Sequenceware

Governs, limits, records, and decides which autonomous actions can reach repositories under configurable governance policies.

FOCUS: Control Plane & Governance

GitHub & CI/CD

The traditional software factory. Designed to version, validate, and deploy human work.

FOCUS: Versioning & Deployment

We don't replace your CI/CD. We make it governable for agents.

Sequenceware sits between your autonomous agents and your software factory. It acts as an intelligent firewall that decides which changes pass, under what conditions, and when human review is mandatory. For Claude Code and MCP agents, Sequenceware enforces policies at the hook level — the agent doesn't need to know it's being governed. For custom agents, three lines of SDK give you full observability and policy enforcement.

  • Granular Policies

    Define rules by action type, tool, or agent. Block destructive operations, allow low-risk ones.

  • Policy Simulator

    Test any policy before activating it: run a scenario and see the exact result without affecting production.

  • Human Approvals (HITL)

    Sensitive changes are automatically paused, waiting for human review before reaching production.

AI
AI Agents
POST /events
Sequenceware
GitHub

Governance Flow

Policy Engine: Repo = "frontend"PASS
Risk: Minor UI changesPASS
HITL required: NoSKIPPED
Core Capabilities

Visibility and guardrails for agentic infrastructure

Policies active from day one

Recommended policies for any team with agents in production are already active. No configuration needed.

Human-in-the-Loop (HITL)

Intercepts sensitive tool calls. Pauses autonomous execution and requires human approval from the Dashboard before continuing.

Automatic blocking in milliseconds

When an agent tries to execute a prohibited action, the policy blocks it automatically — no human intervention, no manual configuration.

Universal Audit

Immutable records ready for operational compliance: which agent executed the action, under which policy, and who approved it.

A controlled execution layer for autonomous work

The secure, structured, and auditable workflow that sits before every action on your systems.

01

The agent proposes

Through the Sequenceware SDK, the autonomous agent notifies its technical intent (open PR, modify CI, deploy).

02

Context evaluation

The platform identifies the agent, gathers context about the proposed action, and prepares the evaluation against active policies.

03

Policy decision

The Policy Engine applies business rules and strictly determines what level of action is permitted.

04

Audit record

Every decision and its reasoning is immutably recorded. Perfect traceability at all times.

05

CI/CD protection

The change reaches the repository only if authorized. Your software factory stays free from agentic chaos.

Built for teams scaling AI

From isolated experiments to systematic use. Each team gets the tools they need.

Platform Engineering

Platform Engineers & DevOps

Build the safe rails for agents. Authorize optimizations on CI/CD infrastructure without fear of breaking production by enforcing blast radius limits.

Security & Compliance

SecOps & Auditors

Generate full traceability for every autonomous action: which agent, which policy, who approved. Intercept and block massive refactors that could introduce vulnerabilities, requiring mandatory review.

Delivery Autonomy

Engineering Managers

Isolate lower-impact agentic PRs (tests, docs) for automatic merge, while enforcing strict approval workflows for core business code.

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?
Three lines of SDK. startRun, trackToolCall, completeRun. Nothing else. You can have your agents sending events in under an hour.
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.
Do agents have to opt in to be governed?
For Claude Code and MCP-compatible agents, enforcement happens at the hook level — no agent code changes required. The hook intercepts every tool call before execution. For custom agents, the SDK provides observability and governance with three lines of code.
From agent experiments to real operations

What agents do you have running today with no controls over what they can do?

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