Talk to an AI architectBook a free AI assessment
AgentsWorkflowsService DeskAnalytics
AI Agent DevelopmentAI Development CompanyAI Automation AgencyConversational AIGenerative AI ConsultingAnswer Engine OptimizationAI SEO AgencyAI Agents for Marketing
AI agents for businessHow to become AI-nativeBuild vs buy AI agentsAI agents vs chatbotsAI agent development costAI agent glossaryTop AI agent companiesFounders Grit podcastBlog
IntegrationsBlogCareersBook a free AI assessment
forward-deployed ai engineers

Forward-deployed AI engineering that ships in your stack.

Gaper embeds forward-deployed AI engineers with your team, builds supervised production agents directly in your stack, and hands over the code, evals, and runbook. We work model-agnostic across OpenAI, Claude, and Gemini, inside your cloud, on your data and auth.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · opportunity map
Support triage92
Invoice processing84
Lead enrichment71
Report drafting58
ranked by ROI × feasibilityship #1 first
In one sentence

Forward-deployed AI engineering is an embedded delivery model where engineers work alongside your team, build production AI agents directly in your stack, and hand over everything they ship. Gaper deploys these engineers to design, build, integrate, and launch supervised agents you own outright, not to staff a seat.

ProductionNot another demo
Model-agnostic
In your cloudYour auth, your data
You own itCode, evals, runbook
Why this matters

Most AI pilots stall because the people who built the demo never touched your real systems, data, or edge cases. The work that survives production needs engineers sitting inside your workflow, not a spec thrown over a wall.

Production filter
  • Does it touch real systems?
  • Can the outcome be measured?
  • Where does human approval stay?
  • Who owns it after launch?
Free AI assessment

Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.

Map your first production agent
How we work

From strategy to production, owned by your team.

  1. 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.

  2. 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.

  3. 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.

  4. 04

    Sandbox, verify, go live

    We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.

What we build

Agents wired into the systems you already run.

Embedded workflow discovery

Our engineers sit with your team, map the real path through your SOPs, portals, inboxes, and spreadsheets, then scope the smallest agent that moves the needle.

Build in your stack

We write code in your repos, your languages, and your conventions, wired into your APIs and MCP tools, so the agent finishes work inside your systems.

Supervised production agents

Agents with evals, guardrails, citations, and human approval gates on risky steps, built to survive real data and real users, not just a demo.

Deploy in your cloud

We deploy on your data and auth, with SSO, RBAC, PII redaction, and audit trails, so the agent inherits your security posture instead of widening it.

Full handover

We hand over the code, evals, and runbook, with knowledge transfer built into delivery, so your engineers can own, extend, and trust the system.

Live in as little as 24 hours

A first working build can land in a day for a scoped use case, then move from sandbox to a human-gated go-live with traces, rollback, and an owner.

Embedded with your team, building in your stack

Forward-deployed means our engineers work next to yours, in your tools and your codebase, not from a distance. They learn your edge cases firsthand, ship against your real data, and leave behind a system your team already understands.

  • Pairing in your repos and conventions
  • Decisions made with your engineers, not for them
  • Knowledge transfer through the whole build
Production launchWhat Gaper hands over
doneWorkflow map

Inputs, systems, owners

doneAgent build

Tools, prompts, permissions

readyEval suite

Known cases and edge cases

readyGo-live runbook

Approvals, traces, rollback

Handoff packagesource codedashboardrunbookowner training

You own everything we ship

We build and deploy the agent, then hand it over: clean code, the evals that gate it, and a runbook to operate it. No black box, no vendor-only workflow, no lock-in trapped outside your stack.

  • Clean, documented codebase in your repos
  • Evals and guardrails you control
  • Extend it without us
Handover state
handoff packageCode, runbook, evals, dashboard
owned by your team
Source repoRunbookEval suiteOwner training

Access your auth

Data your environment

Ops monitor or handoff

Deployed where your data lives

We deploy inside your cloud, on your auth and your controls, so data never crosses a boundary you did not approve. The agent runs under your security posture with full traceability from day one.

  • SSO, RBAC, and PII redaction
  • Audit logging and run-level traces
  • No data retention you didn't ask for
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud
Model and stack agnostic
OpenAIClaudeGeminiMCPYour APIsSnowflakeSalesforcePostgres
FAQ

Questions buyers ask us.

What does a forward-deployed AI engineer do at Gaper?+
They embed with your team, map a real workflow, and build a supervised production agent directly in your stack, wired into your APIs, data, and auth. They cover the full path from discovery through a human-gated go-live, then hand over the code, evals, and runbook.
Do you staff out or place engineers on our team?+
No. We do not staff, place, or supply developers for hire. Gaper builds and deploys the AI agent or system for you, embedded with your team during delivery, and hands over a working system you own outright. The engagement ends with delivered software, not a seat to fill.
Do we own what you build, or is it locked to Gaper?+
You own all of it. We build and deploy the agent in your stack and hand over the code, evals, and runbook with knowledge transfer built in. There is no black box and no lock-in. Your team can run and extend it without us, or keep us on under an SLA, your call.
Which models and infrastructure do you work in?+
We are model-agnostic and infrastructure-agnostic: OpenAI, Claude, Gemini, or the right model for the job, deployed in your cloud, on your data and auth, integrated through your APIs and MCP. A first working build can land in as little as 24 hours for a scoped use case.
See what operators from other companies think about AI Agents:
Learn more
Keep exploring
Ai Agent Development CompanyAi Agents For BusinessAi Automation Agency
Production AI agents, shipped with an owner

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.

Build, deploy, runYour cloudYou own the code