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
custom ai development

Custom AI development, built into your stack and owned by you.

Gaper designs, builds, and deploys custom AI: agents, copilots, and pipelines, wired into your real systems on your data and auth. We hand over the code, evals, and runbook so your team owns what ships, model-agnostic across OpenAI, Claude, and Gemini.

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

Custom AI development is the end-to-end design, build, integration, and deployment of AI systems, agents, copilots, and data pipelines, built into a company's existing stack on its own data and authentication. The deliverable is production code, evals, and a runbook the client owns, not a hosted product or a one-off prototype.

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

Off-the-shelf AI rarely fits the workflow you actually run, and most custom builds stall as demos that never survive real data, real edge cases, or real users in production. The gap between a prototype and a system you can trust is where the work lives.

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.

Production AI agents

Agents scoped from your real workflows that plan and take multi-step actions: update the CRM, file the ticket, reconcile the ledger, gated by approvals on risky steps.

Copilots in your tools

Assistants embedded where work happens, your app, helpdesk, or internal portal, grounded in your data with citations so answers hold up.

Data and retrieval pipelines

Ingestion, cleaning, indexing, and RAG built to stay fresh, so the system reasons over current data instead of a stale snapshot.

Tool and API integration

The system wired into your systems of record through your APIs and MCP, so it reads and acts inside the stack you already run.

Evals and guardrails

Automated evals, confidence thresholds, and human gates on signatures, submissions, and policy changes, so quality is proven before users see it.

Observability and handover

Traces, cost, and quality dashboards, plus clean documented code and a runbook, so your team can operate and extend it without us.

Built into production, not bolted on

We deploy where your data lives: your cloud, your auth, your controls. The system inherits your security posture instead of widening your attack surface, and there is no data retention you did not ask for.

  • Runs in your environment or ours
  • SSO, RBAC, and audit logging
  • Wired into your APIs and systems of record
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the code, not a black box

A forward-deployed team works alongside yours and hands over a system you fully control: the codebase, the evals, and the runbook. No lock-in, no vendor-only workflow trapped outside your stack, and you can extend it without us.

  • Clean, documented codebase
  • Knowledge transfer built into delivery
  • Evals and runbook handed over at launch
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 prototype to production, the part most teams miss

Most custom AI dies as a demo. We design for the gap from day one: evals before users, guardrails on risky steps, fallback and escalation paths, and a named owner at go-live. A first working build can land in as little as 24 hours for a scoped use case.

  • Evals that gate every release
  • Fallback and escalation paths
  • A real owner at launch, not a hope
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
OpenAIClaudeGeminiMCPYour APIsSnowflakeSalesforcePostgres
FAQ

Questions buyers ask us.

What does custom AI development include?+
End-to-end work on AI systems built for your specific workflows: agents, copilots, and data pipelines. Gaper covers discovery, workflow mapping, the data and connector layer, evals and guardrails, sandbox testing, and a human-gated go-live, deployed in your stack on your data and auth.
Do you build and deploy it, or just advise?+
We build and deploy. Gaper designs, builds, integrates, and ships the system into your real environment, then hands over the code, evals, and runbook. You own what ships and can extend it without us. We are an implementation partner, not an advisory or a hosted product.
How is custom AI development different from buying an AI platform?+
A platform gives you tooling to build it yourself and rarely fits your exact workflow. We build the system for you, wired into your specific data and systems of record, and hand over code you own. When an off-the-shelf product genuinely fits, we will tell you; most real workflows need custom integration.
Which models and infrastructure do you work with?+
We are model- and infrastructure-agnostic: OpenAI, Claude, Gemini, and open models, deployed in your cloud and integrated through your APIs and MCP. For regulated workloads we deploy inside your boundary with SSO, RBAC, PII redaction, and full audit logging so data never leaves.
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