Automation & AI · AI / language models
OpenAI
integration & API.
OpenAI integrations engineered for production — not demo-ware that breaks at the second edge case.
What is OpenAI?
OpenAI in plain English.
OpenAI is the company behind GPT, ChatGPT, Codex, and DALL-E — among the most capable AI language and image models in the world. Their API powers AI features in thousands of business applications.
What businesses use it for
Common OpenAI
use cases.
- 01 AI-powered chatbots and customer support
- 02 Content generation and summarisation
- 03 Document and data extraction
- 04 Retrieval-augmented generation (RAG) over your own documents
- 05 Code generation and developer tooling
- 06 Image generation through DALL-E
- 07 Speech transcription through Whisper
Why custom?
Beyond the default OpenAI integrations.
OpenAI's GPT and other models can do remarkable things. Building reliable production AI on top of them takes engineering: prompt versioning, evaluation suites, structured outputs, fallbacks, and cost observability. We build OpenAI integrations you can trust to run unattended.
What we build with OpenAI
Common OpenAI integrations.
GPT-powered chatbots, support routing, content generation
Structured outputs and function calling
RAG over your own knowledge base with source citations
Evaluation suites and prompt versioning
Cost monitoring and rate-limit handling
Commonly paired with
OpenAI works with the rest of your stack.
How we build
Production-grade.
Not Zapier in a trench coat.
Every OpenAI integration we ship handles failure properly: idempotent jobs, retry logic, dead-letter queues for unrecoverable cases, and observability so you can see exactly where data is at any moment.
Tested
Real test suite, real edge cases. Not just "it worked once."
Observable
You see what is happening — events logged, errors surfaced.
Maintainable
Documented, version-controlled, handed over properly.
More Automation & AI
Other automation & ai platforms we connect.
Z Zapier
Zapier integrations and the moments when custom code is the cheaper answer.
M Make
Make (Integromat) integrations and migrations to more reliable architectures.
N n8n
n8n integrations and self-hosted automation for businesses that want control over their data.
A Anthropic
Anthropic Claude integrations for AI workloads where reliability and reasoning matter.
FAQ
Common questions about OpenAI integration.
How much does OpenAI integration cost to run?
Depends on usage — typically a few cents to a few dollars per workflow, depending on the model and prompt length. We design integrations with cost visibility so you see exactly what each automation costs. We wrote up the real numbers in what AI actually costs in production.
OpenAI vs Anthropic vs Gemini — which should we use?
All three are excellent, and the honest answer is it depends on the task. OpenAI has the broadest ecosystem and tooling; Anthropic's Claude often performs better on long context, careful reasoning and lower hallucination rates; Gemini fits businesses already deep in Google Cloud. We pick per use case rather than picking sides — and often use more than one model in the same system.
Can OpenAI integrate with WordPress?
Yes — we build AI features (chatbots, content generation, customer support routing) into WordPress sites using the OpenAI API. Often without needing to rebuild the underlying site.
Is it safe to put OpenAI in front of customers?
Only if it's engineered for it. A demo that works once is not the same as a system you can leave running unattended. We build in guardrails, structured outputs, fallbacks and human-in-the-loop checkpoints where the cost of a wrong answer is high — that's the difference between a prototype and something you can trust in production.
Related reading
Thinking we’ve published on this kind of work.
Claude vs GPT vs Gemini for business automation in 2026
Where each frontier model genuinely shines and where it falls short. A practical comparison for business owners commissioning AI work in 2026.
What AI actually costs to run in production
AI demos are cheap. Production is not. Where the money actually goes when you ship an AI feature, and how to size the engineering investment around the model.
AI automations that actually ship — not demo-ware
AI demos are easy. AI in production is hard. The real engineering between a slick demo and an automation you can trust to run unattended.
Get started
Ready to wire up
OpenAI?
A 30-minute scoping call — no pitch deck, no hard sell. Tell us what you're trying to connect and we'll tell you straight whether it's a fit.