Forward Deployed Engineering: an Innocito team embeds with yours, brings Innoverse with it, builds the agentic workflow, proves it and hands it over.
Forward deployed engineering places the vendor's engineers inside the client's organization to build, prove and deploy an AI system on real workflows and data, then hand it over. At Innocito it means one workflow at a time, at a fixed price, built on Innoverse in your cloud.
Every engagement follows the same four stages and ends with a handover.
The FDE sits with the business owner, picks one workflow and agrees the definition of done.
The pod builds the agentic workflow on Innoverse in your cloud, with your data and the models you approve.
Evals, guardrails and human approval gates go in before any production traffic.
The workflow runs with tracing on, then moves to your team with code, evals and runbooks.
Why AI programs stall between the strategy deck and production.
Today: Vendors deliver slides and pilots; nobody owns the last mile into your systems.
With Innocito: An FDE owns the outcome on the ground, with a pod that builds, proves and ships one workflow.
Today: The roles are new, scarce and expensive, and the backlog keeps growing.
With Innocito: A pod of agent, quality and platform engineers from day one, working your hours.
Today: Harness, evals, security gates and tracing are rebuilt for each project.
With Innocito: Innoverse comes with the pod, so the first week starts with a working factory, not a plan to build one.
Today: Black-box deliverables your team cannot run or change.
With Innocito: You keep the code, evals, prompts and runbooks; the handover is part of the engagement.
What a forward deployed pod changes, measured on client engagements. Delivery ranges are consistent with McKinsey and DORA research.
Agents carry work between gates from the first sprint.
Infrastructure as code and repeatable deployments, set up by the pod.
Playbooks, templates and documentation the pod leaves behind.
Scoped with you, fixed price, delivery risk sits with us.
Code, evals, prompts and runbooks are yours when the pod leaves.
Software, AI and quality engineers across Innocito.
Two services, delivered together by the embedded team.
AI agents that do real work in your business. The pod designs the harness around the model: context, tools, memory, orchestration and the loop, so agents finish work inside your systems.
Continuous assurance for agents in production. Evals on every change, guardrails and permissions at runtime, human-in-the-loop gates and full tracing of every agent action.
A selection of the organizations where Innocito engineers have worked embedded with the client team.
How embedded Innocito teams delivered, in the client’s own stack.
500K+ users, 3.2x engagement, 94% garment detection accuracy and 99.7% uptime on an AI platform built end to end.
A cloud-native EMR with AI documentation: 50% less charting time, 30% lower admin overhead, 25% faster revenue cycles.
An embedded QE team: 85% automation, 40% faster regression, 12,000+ test cases across 12 major releases.
Tell us the one process you would hand to an agent tomorrow if you trusted it. We will scope a fixed-price engagement around it.