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python ai and backend systems

Python AI and backend systems, built and deployed by Gaper.

Gaper builds and deploys supervised production AI agents and backend systems in Python, wired into your existing services, data, and auth. We hand over the code, evals, and runbook so your team owns and extends it.

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

Python AI and backend systems are production services written in Python, including agent workflows, APIs, data pipelines, and retrieval layers, that plan and take multi-step actions inside your stack. Gaper builds them on OpenAI, Claude, or Gemini, deploys them in your cloud, and hands over the code, evals, and runbook.

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

Most Python AI work stalls between a notebook that runs once and a service that holds up under real traffic, real data, and real edge cases. Closing that gap, with evals, observability, and an owner at launch, is the part that decides whether anything reaches production.

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.

Python agent workflows

Goal-driven agents in Python that plan and take multi-step actions across your systems, with guardrails and human approval gates on risky steps.

Backend APIs and services

FastAPI, Django, or Flask services that expose your agents and models cleanly, with auth, rate limits, and versioning built in.

Data and RAG pipelines

Retrieval grounded in your knowledge base, with embeddings, freshness, and citations, built to hold up in production rather than a demo.

Async jobs and queues

Celery, RQ, or async workers for long-running and scheduled work, so heavy tasks run reliably off the request path.

Evals and observability

Automated evals before users, plus traces, cost, and quality dashboards so you can see exactly what every run did and why.

Integration and write-backs

Connected to your databases, APIs, and MCP tools so the system reads and writes inside your stack, not beside it.

Built into your stack, not bolted on

We deploy Python services where your data already lives: your cloud, your auth, your controls. The system inherits your security posture instead of widening your attack surface.

  • Runs in your environment or ours
  • SSO, RBAC, and audit logging
  • Deployed against your databases and APIs
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the code and the runbook

A forward-deployed team works alongside yours and hands over a clean, documented Python codebase you fully control. No black box, no lock-in, no workflow trapped outside your stack.

  • Typed, tested, documented Python
  • Evals and runbook delivered with it
  • 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

Ships like the rest of your software

AI in Python should not be a science project. We deliver with CI, tests, monitoring, and rollback, with evals gating each release, so what we build stays maintainable long after launch.

  • Evals gate every release
  • Monitored with traces and dashboards
  • Rollback and escalation paths
Ship pipeline
  1. 01Scopeworkflow mappeddone
  2. 02Buildagent + toolsdone
  3. 03Evaluatesuite greendone
  4. 04Shiplive in prodlive

p95 latency 1.2s

eval pass 12/12

rollback ready

Model and stack agnostic
OpenAIClaudeGeminiLangChainMCPPythonTypeScriptPinecone
FAQ

Questions buyers ask us.

What does Gaper build in Python?+
Production AI and backend systems: agent workflows, FastAPI or Django services, data and RAG pipelines, and async job processing. We build them on OpenAI, Claude, or Gemini, deploy them in your stack, and hand over the code, evals, and runbook your team owns.
How do you deploy a Python system into our environment?+
We deploy in your cloud, against your databases, APIs, and auth, with SSO, RBAC, and audit logging. The service inherits your security posture, and for regulated workloads data never leaves your boundary.
Which models and frameworks do you use?+
We are model-agnostic across OpenAI, Claude, and Gemini, and build on standard Python frameworks like FastAPI, Django, Celery, and MCP. We choose per task, not per fashion, and wire everything into your existing services.
How long does it take to go live?+
A first working build can land in as little as 24 hours for a scoped use case. Production timelines depend on integration and governance needs, typically weeks rather than quarters, and we scope them up front.
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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