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OpenAI / Claude Integration — Production LLM Applications That Actually Work

We integrate OpenAI and GPT-4 into production applications — building RAG chatbots, AI assistants, function calling workflows, and streaming interfaces that solve real business problems at scale.

20+ OpenAI integrations in production | GPT-4, Function Calling, RAG, Streaming

Projects delivered
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Projects delivered

Clients worldwide
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Clients worldwide

Client satisfaction
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Client satisfaction

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WHY CODEFLAMME

  • Production-grade architecture from day one
  • TypeScript, testing, and accessibility built in
  • Dedicated engineers — no freelancers or hand-offs
  • NDA protected | reply within 24 hours

RESPONSE TIME

< 24h

We reply to every inquiry within one business day with a structured plan.

What We Build

What We Build With OpenAI / Claude Integration

Production applications across product types — scoped to your users, stack, and growth stage.

6 product types — compare what we ship with OpenAI / Claude in production.

  • Product

    AI Chatbots & Assistants

    Domain-specific chatbots powered by GPT-4 with RAG retrieval from your knowledge base — accurate, on-brand, and hallucination-controlled.

  • Platform

    RAG (Retrieval-Augmented Generation)

    GPT-4 connected to your documents, database, or knowledge base — answers grounded in your actual data, not hallucinated.

  • SaaS

    Document Intelligence

    GPT-4-powered document analysis, summarisation, data extraction, and classification for high-volume document processing.

  • Commerce

    Function Calling & Tool Use

    GPT-4 function calling workflows connecting the LLM to your APIs, databases, and business logic for agentic task completion.

  • Internal

    AI-Powered Search

    Semantic search replacing keyword search — users find relevant results using natural language queries against your content.

  • Design

    Content Generation Workflows

    Automated content generation pipelines — product descriptions, report drafts, email responses — with human review workflows.

WHY CODEFLAMME

Not Another Offshore Vendor

We know the hesitation. Here's exactly how we're different.

You Talk to the People Building It

No account managers relaying messages. You're in direct contact with the founder and senior engineers on your project — every sprint, every decision.

No Bench Rotation

The team that scopes your project is the team that ships it. We don't swap engineers mid-project to free them up for someone else.

NDA Before We Talk Details

Your idea and IP are protected from the first real conversation — not after contracts are signed.

Full IP, Zero Strings

Every line of code, every design file, transfers to you on delivery. No licensing, no retained rights, no surprises.

Our Capabilities

Our OpenAI / Claude Integration Development Services

Core delivery areas for OpenAI / Claude — architecture, implementation, and production hardening.

  • 01

    OpenAI API Architecture

    Proper API client setup, token counting, rate limit handling, retry logic, and cost monitoring for production OpenAI usage.

  • 02

    System Prompt Engineering

    Structured system prompts with persona definition, context injection, format constraints, and safety guardrails for reliable outputs.

  • 03

    RAG Pipeline Design

    Chunking strategy, embedding model selection, vector store integration, retrieval logic, and context window management for RAG systems.

  • 04

    Streaming Responses

    Server-sent events and WebSocket streaming for real-time token-by-token response delivery in chat interfaces.

  • 05

    Function Calling Implementation

    Tool definition, parallel function calling, result injection, and multi-step agentic workflows with proper error handling.

  • 06

    Evaluation & Testing

    LLM output evaluation frameworks, golden dataset testing, hallucination detection, and quality monitoring in production.

When to Choose

When OpenAI / Claude Integration Is the Right Choice

Decision scenarios where OpenAI / Claude Integration is the strongest fit — and why it earns the recommendation.

SCENARIO 01

Primary use case

You need an AI chatbot trained on your content

GPT-4 with RAG is the current best approach — accurate responses from your specific knowledge base without fine-tuning costs.

02

Scenario

You need document intelligence at scale

GPT-4's context window and understanding make it far superior to regex or classical NLP for extracting structured data from unstructured documents.

03

Scenario

You want to automate a text-based workflow

If humans are currently reading, categorising, or responding to text at scale, GPT-4 can automate 80%+ of that work with properly designed prompts.

04

Scenario

You need AI features fast

OpenAI's API allows AI features to be shipped in weeks rather than the months required to train custom models.

Complementary Stack

The Stack We Use Alongside OpenAI / Claude Integration

The tools we pair with OpenAI / Claude Integration in production — organised by layer, not hype.

LAYERS

09

TOOLS

47

FAQ

Frequently Asked Questions

Can't find what you need? Talk directly with our team.

Book a Discovery Call

Through RAG, strong system prompts with explicit constraints, and output validation. No LLM is 100% hallucination-free — we design systems that detect and flag low-confidence responses.

Ready to build something powerful?

Tell us what you are building. We will respond within 24 hours with a clear, honest assessment — no pressure, no sales pitch.

NDA protected · Reply within 24 hours · No commitment required