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
ai agents for ruby on rails

AI agents built into your Ruby on Rails stack.

Gaper builds and deploys supervised production AI agents inside your Ruby on Rails application, wired into your models, services, jobs, and APIs. We hand over the code, evals, and runbook, and your team owns it.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · ship pipeline
✓Scope
✓Build
✓Eval
✓Deploy
●Live
prototype→production
In one sentence

A Ruby on Rails AI agent is supervised production software that plans and takes multi-step actions inside a Rails application, calling your models, service objects, jobs, and APIs. It runs in your cloud on your data and auth, with evals and human approval gates on risky steps.

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

A demo bolted beside your Rails app never survives real traffic. The hard part is an agent that reads your ActiveRecord models, calls your service objects, respects your auth, and runs under Sidekiq in production. That is the only part that matters.

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.

Rails-native integration

Agents that call your ActiveRecord models, service objects, and concerns directly, working inside your app rather than scraping it from outside.

Background jobs and queues

Agent work runs through Sidekiq, Active Job, or your existing queue, with retries, idempotency, and backpressure handled like the rest of your code.

API and tool actions

Agents take action through your existing controllers, internal APIs, and MCP tools: update records, enqueue jobs, post to services, write back results.

Retrieval over your data

Grounded answers over your Postgres, MySQL, and document stores, with pgvector or your chosen index, citations, and freshness that hold up in production.

Evals and human gates

Automated evals, policy guardrails, and approval steps on writes, refunds, submissions, and other actions that carry operational or compliance risk.

Observability and rollback

Traces, cost, and quality dashboards tied into your logging, plus a kill switch and rollback so you see exactly what every run did and why.

Built into the Rails app, not bolted on

We deploy where your application already runs: your cloud, your auth, your database. The agent calls your models and services and inherits your security posture instead of widening your attack surface.

  • Calls ActiveRecord models and service objects
  • Devise, Pundit, and your RBAC respected
  • No data retention you did not ask for
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the outcome, and the code

A forward-deployed team works alongside yours in the same Rails codebase and hands over a system you fully control. Clean Ruby, tests, and documentation, no black box and no vendor-only workflow trapped outside your stack.

  • Idiomatic Ruby with RSpec or Minitest coverage
  • Knowledge transfer built into delivery
  • 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

From pilot to production, the part most teams miss

Agent pilots are everywhere; agents that survive real Rails traffic are rare. We design for that gap from day one: evals before users, guardrails on risky writes, and a real owner the day it ships.

  • Evals that gate every release
  • Fallback and escalation paths
  • A runbook, 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 APIsPostgresAWSGCP
FAQ

Questions buyers ask us.

How does Gaper build AI agents for a Ruby on Rails app?+
We map a real workflow in your app, then build a supervised agent that calls your ActiveRecord models, service objects, and APIs, runs work through Sidekiq or Active Job, and writes back inside your database. It ships with evals, guardrails, and human approval on risky steps.
Do you work inside our existing Rails codebase and respect our auth?+
Yes. We work in your repository, follow your conventions, and add idiomatic Ruby with RSpec or Minitest coverage. The agent integrates through your existing models, controllers, and jobs behind Devise, Pundit, or your own RBAC, not as a separate black box.
Can the agent run in our own cloud?+
Yes. We deploy in your cloud on your data, with SSO, PII redaction, and full audit logging, so data never leaves your boundary and the agent only does what your policies allow.
Which models can it use, and who owns it after launch?+
We are model-agnostic: OpenAI, Claude, Gemini, or open models, integrated via your APIs and MCP, switchable without a rewrite. You own the code, evals, and runbook. We hand it to your team or run it under an SLA, and a scoped build can go live in as little as 24 hours.
See what operators from other companies think about AI Agents:
Learn more
Keep exploring
Ai Agent Development CompanyAi Development CompanyIntegrations
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