How We Work
A clear engagement model designed to reduce uncertainty and ship production AI systems. Four phases from discovery to ongoing improvement.
Our Four-Phase Process
Each phase has clear inputs, outputs, and decision points. No endless discovery. No surprise scope.
Discovery + Scope
We identify the specific workflow to automate, map constraints and edge cases, and define clear success metrics before any building begins.
Prototype
Fast iteration on conversation flows, tool behaviors, and decision logic. We validate the approach with real scenarios before committing to full build.
Build + Integrate
Connect to your existing stack - CRM, helpdesk, calendars, databases. Add guardrails, logging, and human handoff paths. Production-grade from the start.
Launch + Improve
Go live with monitoring in place. Track quality metrics, identify gaps, and expand coverage safely over time. Continuous improvement, not set-and-forget.
What you'll get early
Before we write production code, you'll have a clear picture of what we're building, how we'll measure success, and what access we need.
Workflow + Edge-Case Map
Complete documentation of the workflow we're automating, including all the edge cases and exception paths.
Success Metrics + Rollout Plan
Clear definition of what success looks like and a phased approach to getting there safely.
Integration Plan
Which systems we'll connect to, what data we need, and what access/permissions are required.
Typical starting point
Most projects start with one workflow. We automate a specific, high-value process, prove the value, then expand to adjacent workflows. This keeps risk low and learning fast.
Frequently Asked Questions
How long does a typical engagement take?
Most initial deployments take 4-8 weeks from discovery to launch, depending on integration complexity. Simpler workflows can ship faster; complex multi-system integrations take longer.
What if the AI makes mistakes?
Every system we build has guardrails, confidence thresholds, and human escalation paths. We design for graceful failure - when the AI isn't confident, it hands off to a human with full context.
How do you handle data security?
Security is built in from day one. We use encrypted connections, role-based access, audit logging, and follow your existing compliance requirements. We can work within SOC 2, HIPAA, or other frameworks.
What happens after launch?
We monitor quality metrics, review edge cases, and continuously improve the system. Most clients expand to additional workflows after seeing initial results. We offer ongoing support and iteration packages.
Can we start small?
Absolutely. We recommend it. Starting with one high-value workflow lets you see results quickly, learn what works for your organization, and build confidence before expanding scope.
Ready to get started?
Tell us about a workflow that's creating friction. We'll walk you through how we'd approach it and whether we're a good fit.