AI Command Center

Give AI Agents a Real Software Delivery Process

Individual coding agents are useful, but they do not provide the controls a software organization needs. A model can write the change, declare its own work complete, and move on without an independent check or a durable record of the decision.

The AI Command Center separates planning, implementation, evaluation, and recovery. Agents work against a written sprint contract, independent QA checks the result, and people retain approval over what enters the codebase or reaches production.

In the initial harness run, 18 of 19 sprints passed QA within two attempts. The more useful result was not the low model cost. It was a repeatable process that caught failures before they were treated as finished work.

What You Get

• Multi-agent harness configured for your repositories, stack, and delivery process
• Specialized agent roster for planning, development, QA, research, recovery, and documentation
• Repository and approval boundaries aligned to branch protections, CI, review, and release policy
• Independent evaluation framework calibrated to your tests, acceptance criteria, and quality bar
• Sprint contract system that records the definition of done before implementation starts
• Execution record and live dashboard for ownership, status, cost, retries, and review outcomes
• Pilot backlog and team training so your engineers can judge the system on real work
• Full source code running on infrastructure you control

How It Works

1. Delivery and risk review: Map repositories, environments, permissions, review policy, deployment gates, and work that remains off-limits.
2. Agent and contract design: Configure roles, domain context, acceptance criteria, retry limits, and escalation rules.
3. Evaluation setup: Connect tests, linters, security checks, and any domain-specific review needed before work can pass.
4. Controlled pilot: Run a small backlog of representative, reversible work with your engineering team reviewing every result.
5. Measure and tune: Compare cycle time, rework, review load, and defect rate against the current baseline.
6. Handoff or rollout: Transfer runbooks and ownership, then expand permissions and backlog scope only where the evidence supports it.

Most contained pilots take two to four weeks. Larger codebases, regulated environments, or several engineering teams may need a phased rollout. The harness can work with Claude Code, OpenClaw, NemoClaw, Codex, or another agent runtime that fits your environment.

The Guarantee

We agree on a delivery metric and a quality floor before the pilot. If the system does not improve the agreed metric within 30 days without lowering that quality floor, we refund the setup fee.

Your Investment

Pilot setup: from $15,000 CAD. Scope depends on repository count, delivery controls, evaluation depth, and team size. Multi-team rollouts are phased and quoted after the pilot. Optional ongoing support starts at $4,000/month.

Some implementation work may qualify for SR&ED. Eligibility depends on the work and your tax position; confirm with your adviser.

Founder-led. Independent QA. Human approval. Full source ownership.