The prototype works. Production is where the risk starts.
A demo proves the model can do the task once, watched, on curated inputs. Production means thousands of unattended requests, edge cases nobody planned for, and a cost line that either holds or doesn't. We engineer the architecture, evaluation, security, and infrastructure underneath before you ship, not after an incident.
The same stack your engineering org already runs.
No new framework to learn — the infrastructure underneath the prototype gets built with standard, boring, production-grade tools.
Recognize the symptoms
The symptoms that show up first.
A prototype rarely fails on all seven categories below — but it rarely holds up on more than one or two.
- Nothing retries a failed step or contains a failure before it takes the whole system down
- Nobody can tell whether a model or prompt change made things better or worse
- The model is exposed directly, customer data isn't kept separate, and inputs aren't checked before they reach it
- The bill tripled and nobody can explain why, because nothing was measured per request
A demo proving the model works isn't the same as production readiness.
- Seven categories, drawn from the patterns we see across engagements, account for almost everything that breaks when a prototype meets real traffic.
- None of them are about whether the model is good enough — they're about whether the system around it was built to survive load, not just prove a concept.
What usually breaks
Five phases, gated in order.
Production doesn't start until the phase before it is done.
Assess
Audit the prototype against production requirements: architecture, evaluation, security, cost, observability. Score what's there against what's missing.
Architect
Design the system that will actually run in production: components, data flow, security model, deployment and rollback strategy.
Engineer
Build against that architecture with standard engineering discipline: every change tracked, reviewed by another engineer, tested automatically, and deployed through an automated pipeline.
Validate
Test what makes AI systems different: a set of test cases with a way to score the answers, attempts to break it on purpose, load testing, and a security review.
Deploy
Ship through a controlled process: pre-flight checks, health checks, monitoring live before traffic, rollback ready if something's wrong.
What the buyer receives
Six artifacts you can inspect, not a case-study story. If you have them, the system is production-ready. If you don't, it isn't.
Architecture
A production architecture document: component diagrams, data flows, deployment and rollback strategy, and the decision records behind each choice.
Risk register
Every identified risk — security, reliability, cost — with a mitigation, an owner, and a severity rating.
Evaluation system
A test set built from your own support tickets and known failures, a scoring method calibrated to your standards, and a check that runs automatically before every change ships.
Production infrastructure
Your infrastructure defined in code — deployed, tracked, and duplicated, with a plan for handling more load and recovering from a major outage.
Monitoring
Logs you can search, a way to trace a request through every step it took, dashboards for cost and response time, and alerts tied to a step-by-step plan for handling incidents.
Handover
Architecture docs, runbooks, and training, so your team can own the system without us.
From our experts.
Writing on why pilots stall, agent failure modes, and production cost.
What happens after
Getting one system to production is rarely the end of the relationship. Most teams come back for one of three reasons.
Engineering Project
A second system needs the same treatment: architecture, build, evaluation, deployment, handover.
Platform Build
The pattern that worked for one system needs to become the default for every team: a standard way to build it, rules that get enforced automatically, and shared infrastructure everyone uses.
Managed Engineering
We stay through the first months in production, optimizing cost and reliability, handling incidents, and transferring ownership gradually.
Common questions.
Let's find out where your prototype would actually break.
Start with an assessment to understand your current state, gaps, and next steps. Then you decide whether to go deeper with a full engineering project.
NDA available · Scoped engagements · No surprise fees