The Production AI Pilot is Corinth's flagship AI engagement: pick one valuable workflow, and we design, build, integrate, evaluate, and deploy it into your real environment — with the engineering around the AI that demos always skip.
MIT's widely-cited NANDA research found that 95% of enterprise generative-AI pilots showed no measurable business impact. The pattern behind that number is consistent: the pilot proves the model can talk, then dies at the gap between a demo and a dependable system — no integration with real applications, no persistent state, no evaluation, no human decision points, no security review, no path to production.
The Production AI Pilot is built backwards from that failure mode. Production is the requirement from day one, and one working workflow beats ten impressive demos.

The process mapped and redesigned as an intelligent workflow: AI reasoning, deterministic rules, tools, and human decisions in the right places.
Connected to the applications, data, and documents the workflow actually touches — not a sandbox.
What the AI did, why, where it failed, and whether each version beats the last — measured, not vibes.
Approval and escalation designed in wherever judgment or risk matters.
Access controls, data boundaries, tool permissions, and secure model access from the start.
Controlled rollout into real usage, with monitoring and a runbook your team can own.
Classify, enrich, respond, and route incoming work with human review on exceptions.
Extract, validate, and act on business documents that people currently re-key by hand.
Retrieval over your policies, projects, and history — grounded, cited, and permission-aware.
A promising prototype that never shipped — we engineer the missing production layer around it.
A fixed-scope engagement that takes one valuable workflow from concept to production: architecture, integration with your real systems, evaluation, human-approval design, security, deployment, and observability. Not a demo, not a proof-of-concept — a workflow your team runs on real work.
Widely-cited MIT research found most enterprise AI pilots produce no measurable impact — typically because they stop at the model and skip the system: no integration, no state, no evaluation, no human workflow, no production hardening. The Production AI Pilot exists to engineer exactly those missing layers.
One workflow worth improving, access to the systems it touches, and a decision-maker who can review weekly demos. We handle the engineering. If you already have a stalled prototype, that's a common and excellent starting point.
Three common paths: expand the workflow, add adjacent workflows, or move into ongoing engineering for operation and improvement. You own everything built either way — code, accounts, and documentation.
Fixed scope, weekly demos, and a system your team runs on real work — not another demo for the graveyard.