Preparing experience

Core stack — production applications on OpenAI

OpenAI Development

OpenAI is one of WLC's six core technologies. We build production copilots, assistants, RAG systems and agentic workflows on OpenAI APIs, served through Python FastAPI backends with evaluation and human review designed in from the first release.

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Capabilities included

What this type of engagement typically covers.

  • OpenAI APIs
  • Assistants & agents
  • RAG pipelines
  • Evaluation & guardrails
Why WLC

Built for buyers who need clarity, speed and accountability.

Three principles that shape how we scope, build and deliver every engagement.

01

Ship OpenAI features connected to your data, APIs and approval chains—not an isolated demo chat.

02

Choose models against cost, latency and quality for the specific task rather than defaulting to the newest release.

03

Build evaluation, guardrails and observability into the first production version.

04

Serve OpenAI applications through FastAPI backends with the same engineering standard as the rest of our stack.

05

Route across OpenAI and Claude where a second model improves reliability or cost.

06

Explain model behaviour in plain language to product and operations stakeholders.

Engineering team delivering software products
Delivery model

A clean path from idea to launch.

Talk to delivery team
Step 1

Discovery

Step 2

Architecture

Step 3

Sprint build

Step 4

QA

Step 5

Launch support

Questions buyers ask

Common questions before starting a project.

Yes—OpenAI is one of our six core technologies, alongside React.js, Node.js, Python, React Native and Claude.

Production systems—assistants, RAG and agents wired to your APIs, with evaluation and logging treated as part of the deliverable.

Yes—multi-model routing is common when one provider is stronger for a given task, or as a fallback under load.

Python with FastAPI is the default serving layer for our OpenAI and Claude application work.

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Ready to move

Tell us what you are building — we will map a practical route.

Share the outcome, timeline and constraints you are working with. We will respond with useful next questions and a clear way to start.