Engagements
Most engagements start with a Proof Sprint: we take over one real workflow and run it on your real cases, then hand you the numbers. Working on your real cases in ten days. Live under supervision in thirty. Proven on the numbers at sixty.
Most start with a Proof Sprint: we take over one real workflow, run it on your real cases, and hand you a scorecard of accuracy and cost per outcome with a clear go or no-go. From there it becomes a supervised production pilot, then a managed workflow we run for you, expanding to the next workflow only when the numbers justify it.
Ten business days. We shadow one workflow and build a working system on your real cases. You leave with a scorecard: accuracy and cost per outcome, and a go or no-go. Low-risk internal workflows go live under supervision inside the sprint.
The workflow runs in production under human supervision on capped volume, measured every day, until the numbers hold.
We run the workflow for you: dashboards, SLAs, humans on the exceptions, and a monthly improvement loop. Expand to the next workflow only when the numbers justify it.
When you need a full system shipped, we build in phases, shipping weekly, with the same proof discipline behind every release.
Scoped audit. We map one workflow, score it for agent-fit, and give you the build plan with an honest go or no-go. Yours to keep, whoever builds it.
One role. Pick one role: research, reporting, scheduling, ops. We onboard a digital worker, run its probation, and hand you the performance numbers.
Fixed scope. Your product bet as a working system on real data. You get the prototype, the eval numbers, and an honest read on what production takes.
Scoped assessment. We measure where your AI actually fails, what it costs you, and design the human layer that closes the gap. Report plus loop design, yours to keep.
One workflow. Pick the workflow that hurts most. We automate it end to end with exception handling, and hand you the before-and-after numbers.
Fixed scope. Readiness assessment, scored use-case portfolio, and an execution roadmap grounded in reality. Useful whether or not we build a single line of it.
One bet. Proven with a working system. Not a deck.
Dedicated team. A dedicated AI team that ships and hands over clean.
Managed service. Your AI workforce, run as a managed service with SLAs.
Describe the problem in one paragraph. We will name the engagement and the number it has to beat.
