Wiring an API key into a prototype is easy. Making ChatGPT reliable, secure, and cost-controlled inside a production application your customers depend on is a different job. We integrate the OpenAI API directly into your existing product — with proper auth, usage limits, and monitoring from day one.
A raw API call works in a demo. Production traffic exposes what a demo doesn't.
No rebuild — ChatGPT becomes a feature inside the product you already have.
Token limits, caching, and model selection tuned so usage doesn't spiral unpredictably.
Retries, fallbacks, and rate-limit handling so a provider hiccup doesn't break your app.
Requests structured to avoid leaking sensitive customer data into prompts unnecessarily.
A dashboard showing exactly what's being spent and where, instead of a surprise invoice.
Built so you can switch models or add a second provider later without a rewrite.
Everything between an API key and a feature customers can rely on.
Server-side key management and request handling so credentials never touch the client.
Structured prompts using your product's actual data, not generic instructions.
Per-user and per-org limits to prevent abuse and control cost exposure.
Real-time visibility into token usage, request volume, and spend by feature.
Graceful degradation when the API is slow, rate-limited, or unavailable.
A test suite for prompt outputs so changes don't silently degrade quality.
No-code automation tools work well for simple, low-volume automations between existing apps. Once you need custom prompt logic, cost controls at scale, or the AI feature to live natively inside your own product's UI, a direct integration gives you control a generic workflow-automation model doesn't.
We set token limits, cache repeated queries, choose the right model tier for each task, and build a usage dashboard so you can see cost trends before they become a problem.
Yes. Integration is designed to sit inside your current architecture and stack — it's an added capability, not a platform migration.
We build with fallback handling and a model-agnostic layer, so switching models or adding a backup provider doesn't require rearchitecting the integration.
Tell us what you want ChatGPT to do inside your product — we'll scope an integration built for production, not a demo.