AGENT STUDIO
Powered by FIT · ACE
The first move is one workflow, in production-like conditions, before you choose an existing project or a new one.
Prove one workflow in production-like conditions before you commit to a path.
Lock the use case, success criteria, systems, and data access so the evaluation starts with a clear finish line.
Architect the agent flow, build the working slice, and validate quality on real scenarios before production talk.
Ship a demo-ready outcome with results, risks, and a concrete path to production rollout.
Make AI fit your current delivery system without disrupting existing teams.
Frame the AI strategy around your current SDLC so it integrates without disrupting existing teams.
Integrate the AI in parallel to calibrate output against your security and quality benchmarks.
Transition to the proven AI, retaining traditional processes as an instant fail-safe rollback.
Build agent systems from the ground up, with evals and gates before production.
Define domain intents, entities, and type-safe tool schemas from day one.
Run quality test suites and synthetic cases, then require human approval before high-risk production.
Version code, vectors, and prompts as one artifact, with governed runtime telemetry.
AIOps is the system behind both paths, so quality, cost, and rollback stay consistent.
Build, release, and improve agent systems as one versioned loop.
Code, embeddings, prompts, tools, and policies compile as one versioned artifact—tested before promotion.
The same release can go to FIT or ACE, with checks and an instant rollback path.
Quality checks keep running after go-live, so production never freezes at the last test.
We connect the knowledge already in your systems, and we accumulate what agents learn in every cycle. The next agent starts richer than the last.
Existing agents enter this connection. The 4C loop is the cycle that connection runs.
06 · One workflow
Pick the workflow. We’ll prove it in four weeks, then map FIT, ACE, or both.