AI-Powered Software Factory

Your workflow can't ship.
We fix it.

Coordinated AI agents that plan, build, test, and deliver through your existing workflow. No migration. No new tools. Just faster shipping.

Works with Jira, Linear, GitHub Projects, Confluence, and Slack.
Every action is traceable on your board.

15+
Years building enterprise software
Deep
Workflow integration experience
Week 1
Delivery, not planning

Your workflow tracks work. It doesn't do the work.

Your board is full of tickets. Your docs are full of specs. But work still stalls between planning, engineering, QA, and release. Context gets lost in handoffs. Docs go stale the day they're written.

AI coding assistants help individual developers, but nobody is solving the coordination problem — where delivery actually breaks down.

Key insight: The gap isn't individual productivity. It's execution across the full ticket lifecycle.

An AI-powered Software Factory that runs on your existing workflow.

Coordinated AI agents operate through your existing workflow and knowledge base — planning, building, testing, and deploying. All visible on your board, governed by your approval gates.

Faster ticket throughput

Tickets move from To Do to Done faster, with fewer round-trips between teams.

Living knowledge base

Knowledge bases stay current because agents actively maintain them — no more document graveyards.

Traceable handoffs

Every handoff is explicit, traceable, and on your board. No more context lost between stages.

Human approvals at every gate

Your approval gates, your quality standards — enforced automatically with humans in the loop.

Multi-platform integration

Agents operate directly on Jira, Linear, GitHub Projects, or any workflow tool you use.

Full squad model

A coordinated team — PM, engineering, QA, release — that handles handoffs, not just isolated code assists.

What changes when your workflow gets an AI execution layer

Before

  • Tickets stall between planning and engineering
  • QA finds issues late because context was lost in handoffs
  • Specs are outdated by the time development starts
  • Release coordination is manual and error-prone
  • Developers context-switch between task tracker, Slack, docs, and code

After

  • Coordinated agents move tickets through each workflow stage
  • QA has full context from requirements through implementation
  • Knowledge bases are continuously updated as work progresses
  • Release management follows explicit gates and checklists
  • One execution system connects everything on your existing board

How it works

From audit to execution in weeks, not months.

01

Workflow Audit

1 week

We map your workflow, knowledge base, and handoff patterns to identify where AI agents will have the highest leverage. You get an execution plan, not a strategy deck.

02

Integration Sprint

2–6 weeks

We configure and deploy AI agents into your workflow. Role-based workflows, quality gates, knowledge base integration, and Slack notifications — all wired into your existing board structure.

03

Managed AI Execution

ongoing

We operate and optimize the system alongside your team. Weekly cycles, transparent reporting, continuous improvement. Agents get smarter as your knowledge base grows.

Built for how engineering teams actually work.

Most AI tools bolt on as separate systems. We go where your team already lives — agents work as first-class participants in your existing workflow, not external add-ons.

Multi-platform integration

Agents operate directly on Jira, Linear, GitHub Projects, or any workflow you use

Coordinated execution

A full squad model (PM, engineering, QA, release) that handles handoffs

Persistent context & memory

Knowledge bases become the living memory layer that agents read and write

Human-in-the-loop by design

Your approval gates, your quality standards, enforced automatically

Who This Is For

Built for mid-to-large engineering teams.

Best fit

  • Engineering teams of 20–200 running on task tracking tools
  • Organizations where workflow complexity has outpaced team capacity
  • Teams that have tried AI coding assistants but still struggle with end-to-end delivery
  • Engineering leaders who need faster throughput without adding headcount

Less fit

  • Teams without established workflows to build on
  • Organizations looking for a simple chatbot or coding assistant
  • Teams without existing task tracking infrastructure

Are you ready for an AI execution layer?

Book a 60-minute Workflow Audit. We'll map your current process, show you exactly where AI agents will have the highest impact, and outline a concrete integration plan.

If you don't leave with a clear, actionable plan for your workflow, we refund 100% of the consultation fee.