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ForwardCraft runs every engagement through five disciplined phases — built so AI reaches governed production, not a pilot graveyard.
Most AI projects die in the gap between a promising demo and a system the business can actually depend on. We close that gap by treating production as the goal from day one, not a phase we get to later.
That means we design backwards from the workflow as it really runs: the approvals, the exceptions, the auditors, the people who own the outcome. Agents handle the routine work inside guardrails. A network of domain experts handles the judgment calls. And evaluation — not optimism — decides what ships.
The result is a system your team owns and operates, with every action governed and traceable. Below is the path we run, and the controls that make it safe in regulated environments.
Each phase has clear exit criteria. We don't advance until the prior one is met.
Not the model. We scope the slice of work that pays for itself and design the whole system around it — approvals, fallbacks, and all.
11,000+ vetted domain experts handle the judgment calls in minutes. Their decisions flow back into evaluation, so the system keeps learning.
Nothing ships on a vibe. Every release clears measurable acceptance criteria, and regressions block the gate automatically.
We deliver systems your engineers can read, run, and extend. No black boxes, no dependency on us to keep the lights on.
The guardrails are part of the product, not a checklist we attach at the end.
Agents act under least-privilege identities. They only touch the systems and records a given task requires.
High-impact actions pause for human sign-off. Thresholds are configurable per workflow and per role.
Every action — inputs, decision, output, reviewer — is logged immutably and exportable for compliance.
Offline and online evaluations run on every change, catching drift and regressions before they reach users.
Outcomes we hold ourselves to
A short working session is enough to scope the first slice and the evaluations that gate it.