We embed in your stack, build the agents, and hand them over.
Forward-deployed AI engineering means we work inside your systems, learn your domain, and build production agents on your data and auth. You get the code, the evals, and the runbook, and your team owns what we ship.
Forward-deployed AI engineering is a delivery model where Gaper builds production AI agents directly inside a client's existing systems, on their cloud, data, and auth. We design, build, and deploy supervised agents on OpenAI, Claude, or Gemini, then hand over the code, evals, and runbook so the client owns the result.
OpenAI
Claude
GeminiModel-agnosticMost AI work stalls in the gap between a demo and production. Generic builds never touch your real data, auth, or workflows, so the agent that looked great in a sandbox breaks the moment it meets your stack.
- Does it touch real systems?
- Can the outcome be measured?
- Where does human approval stay?
- Who owns it after launch?
Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.
From strategy to production, owned by your team.
- 01
Map the workflow
We start from the documents, SOPs, portals, inboxes, and spreadsheets your team already uses, then turn the repeatable path into an agent workflow map.
- 02
Build the supervised agent
We build on OpenAI, Claude, Gemini, or the right model for the job, with evals, guardrails, citations, and human approval gates where risk matters.
- 03
Connect the stack
The agent gets the data layer, APIs, MCP tools, auth, and write-backs it needs to finish work inside your systems, not beside them.
- 04
Sandbox, verify, go live
We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.
Agents wired into the systems you already run.
Build in your stack
We work inside your repos, cloud, data, and auth, so what we ship reflects how your systems actually run, not a sandbox approximation.
Production agents, supervised
Agents ship with guardrails, retries, and human-in-the-loop checks where they matter, built to run real workloads, not just demos.
Model-agnostic
OpenAI, Claude, or Gemini, chosen per task on quality, latency, and cost. We are not locked to one provider.
Evals before deploy
Every agent ships with evals and regression tests so quality is measured and held, not assumed from a one-off demo.
Full handover
You receive the code, evals, and a runbook. Your team can operate, extend, and audit everything we deploy.
Live in 24 hours
We scope the first agent and stand it up in your environment fast, with a working deployment in as little as a day.
Design: we learn your stack before we build
We start inside your systems, mapping the real workflow, the data the agent will touch, and the auth and constraints it has to respect. The design reflects production from the first day, so nothing has to be re-architected when it meets your stack.
- We map the target workflow, data sources, and auth boundaries with your team.
- We pick the model per task on quality, latency, and cost across OpenAI, Claude, and Gemini.
- We define the evals that decide what good looks like before any code ships.
- 01Scopeworkflow mappeddone
- 02Buildagent + toolsdone
- 03Evaluatesuite greendone
- 04Shiplive in prodlive
p95 latency 1.2s
eval pass 12/12
rollback ready
Build: production agents in your environment
We build the agent directly in your repos and run it on your cloud against your data and auth. It ships with guardrails, retries, and supervision so it behaves under real conditions, and with evals that catch regressions before they reach users.
- Agents run in your own cloud on your data, never a separate black box.
- Guardrails and human-in-the-loop checks are built in where the work is sensitive.
- Evals and regression tests gate every change so quality holds over time.
Inputs, systems, owners
Tools, prompts, permissions
Known cases and edge cases
Approvals, traces, rollback
Deploy and own: we hand over what we ship
We deploy the agent into your systems with observability wired in, then hand over the code, evals, and runbook. Your team can operate, extend, and audit it without depending on us. Live in as little as 24 hours.
- You get the full code, evals, and a runbook your team can act on.
- Observability and logging ship with the agent so you can see what it does.
- Ownership transfers to your team, with no lock-in to Gaper to keep it running.
Access your auth
Data your environment
Ops monitor or handoff
Questions buyers ask us.
What does Gaper actually deliver?+
Which AI models do you build on?+
Who owns the code after deployment?+
How fast can an agent go live?+
Ready to deploy your first agent?
Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.