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ai engineering

AI engineering delivered as a supervised production agent your team owns.

Gaper does the AI engineering and ships the result: a supervised production agent built from your real workflow, wired into your systems, and handed over with code, evals, and a runbook. We design, build, and deploy it on OpenAI, Claude, or Gemini, running in 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 · agent runtime
$ gaper deploy agent --to production
✓ plan ……………… 4 steps
✓ retrieve …… 1,240 docs grounded
✓ tool ………… salesforce.update_record
✓ eval ………… 12/12 checks passed
● live · p95 1.2s · 0 errors
● in productionowned by your team
In one sentence

AI engineering is the practice of designing, building, integrating, and operating production AI agents inside a company's existing systems. Gaper delivers it as a supervised agent: scoped from a real workflow, deployed on OpenAI, Claude, or Gemini in your cloud, and handed over with code, evals, and a runbook your team owns.

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

Most AI engineering stalls between a working demo and a system that survives real data, real edge cases, and real users in production. Closing that gap, with evals, guardrails, and a real owner at launch, is the entire job.

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.

Agent architecture

We design the workflow map, the planning loop, the tool calls, and the human approval gates before a line of agent code ships.

Retrieval and grounding

Answers grounded in your documents and data, with citations and freshness, RAG engineered to hold up under production load.

Tool and API actions

Agents that take real action: update the CRM, file the ticket, reconcile the ledger, wired in through your APIs and MCP.

Evals and guardrails

Automated evals that gate every release, policy guardrails, and approvals on signatures, submissions, and other risky steps.

Observability and tracing

Traces, cost, and quality dashboards so your team can see exactly what every run did and why.

Secure deployment

Deployed in your cloud with SSO, RBAC, PII redaction, and audit trails, so data stays inside your boundary.

Engineered into production, not bolted on

We deploy where your data lives: your cloud, your auth, your controls. The agent inherits your security posture instead of widening your attack surface, and every consequential action is logged.

  • Runs in your environment or ours
  • SSO, RBAC, and full audit logging
  • No data retention you did not ask for
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the code, evals, and runbook

A forward-deployed team builds alongside yours and hands over a system you fully control. Clean codebase, the eval suite that gates releases, and a runbook your team can extend without us.

  • Clean, documented codebase
  • Eval suite handed over with it
  • Extend and operate it yourself
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

From pilot to production, the part most teams miss

Demos are easy; production AI is where initiatives quietly die. We engineer for that gap from day one: evals before users, guardrails on risky steps, sandbox verification, and a named owner at go-live.

  • Evals that gate every release
  • Sandbox-verified before launch
  • Fallback and escalation paths
Release gate
  1. 01Eval suiteknown + edge casespass
  2. 02Policy checkguardrails enforcedpass
  3. 03Human fallbacklow-confidence routedhold
  4. 04Releaseshipped to prodlive

p95 latency 1.2s

eval pass 12/12

rollback ready

Model and stack agnostic
OpenAIClaudeGeminiLangChainMCPPythonTypeScriptPinecone
FAQ

Questions buyers ask us.

What does Gaper actually build?+
A supervised production AI agent scoped from one of your real workflows: the workflow map, the data and connector layer, the planning and tool-call logic, evals, guardrails, and a human-gated go-live. You receive the code, the eval suite, and a runbook.
How does the agent get deployed?+
We launch in a sandbox, verify every run against the evals, then move into supervised production with traces, rollback, and a named owner. It runs in your cloud on your data and auth, or in ours if you prefer.
Who owns the system after launch?+
You do. We hand over a clean, documented codebase, the eval suite, and the runbook so your team can operate and extend it. You can also keep us on under an SLA for monitoring and ongoing improvement.
Which models and stacks do you build on?+
We are model- and infrastructure-agnostic: OpenAI, Claude, Gemini, or open models, chosen per task, deployed in your cloud and integrated through your APIs and MCP.
See what operators from other companies think about AI Agents:
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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