How We Build
From idea to production agent in weeks, not quarters.
Most AI projects die in the proof-of-concept graveyard. Ours ship. Here's the methodology we use to build AI agents that actually work inside your business.
AI fails differently than traditional software.
Traditional software bugs are predictable — wrong output, crash, error code. AI failures are subtle. The agent sounds confident while giving wrong answers. It works perfectly on demos and breaks on real data. It handles 95% of cases and catastrophically fails on the 5% that matters most.
This is why process matters more for AI than any technology you've shipped before. You can't just build it and hope. You need a methodology designed around how AI actually fails — gracefully, silently, and in ways you won't catch without deliberate testing.
We watch your team work. Then we find the real opportunity.
We don't send you a questionnaire. We sit with the people who do the work and observe the actual workflow — the workarounds, the copy-paste loops, the decisions that take 30 minutes but shouldn't. We're looking for where AI creates 10x value, not 10% improvement.
1-2 daysWhat makes this different
Most consultancies run a 'discovery phase' that's really just meetings about meetings. Our audit is hands-on observation by engineers who've built production AI systems — not analysts filling out frameworks.
Deliverables
- --Workflow map with time and cost breakdowns
- --AI opportunity assessment ranked by impact
- --Recommended scope for the first agent build
- --Honest 'don't automate this' list
We ship into your stack. No rip-and-replace.
We build the agent inside your existing environment — your tools, your data, your team's mental model. Nobody has to learn a new platform. The agent works where your team already works. We ship incrementally, with working functionality every week.
2-6 weeksWhat makes this different
The default consulting move is to pitch a new platform and charge for migration. We do the opposite. We integrate with what you have. When we're done, you own everything. No vendor lock-in.
Deliverables
- --Working agent deployed in your environment
- --Integration with existing tools and data
- --Technical documentation your team can read
- --Weekly progress demos
We break it before your customers do.
Production-grade testing means more than 'it works on the demo.' We test edge cases, failure modes, adversarial inputs, and the weird things real users will inevitably try. Every failure mode gets a documented response.
1-2 weeksWhat makes this different
Most teams test AI the way they test traditional software — check the happy path, ship it. That's how you end up with an agent that hallucinates a refund policy you don't have. We know where AI breaks and design around it.
Deliverables
- --Test suite covering edge cases and failure modes
- --Reliability report with accuracy metrics
- --Guardrail documentation — what the agent will and won't do
- --Escalation protocols for edge cases
We stay until the agent earns trust.
Launch is the beginning, not the end. We deploy with full monitoring and watch how real users interact with the agent in production. The agent gets better every week because we're watching the data and tuning the system.
OngoingWhat makes this different
The typical handoff is a deployed system, a PDF of docs, and 'call us if something breaks.' We don't do handoffs — we do transitions. We stay until your team is confident and the agent has proven itself.
Deliverables
- --Production deployment with zero-downtime launch
- --Real-time monitoring dashboard
- --Weekly performance reports for the first month
- --Knowledge transfer and runbook
Ready to build something that actually ships?
Skip the six-month pilot program. Tell us what your team is spending too much time on, and we'll tell you — honestly — whether AI can fix it.