AI Model Integration into Existing Software

Connect OpenAI, Anthropic, and other AI providers to your existing applications - adding AI-powered features without rebuilding from scratch.

Book a Free Consultation

AI That Fits Your Existing Software

We integrate AI models into existing software for businesses across the UK and Isle of Man. Connecting OpenAI, Anthropic's Claude, and other AI providers to your existing applications - adding AI-powered features to the software your team and customers already use without rebuilding it from scratch.

Adding AI capability to existing software is rarely as simple as connecting an API. Prompt engineering, context management, output validation, rate limit handling, cost management, fallback logic, and security all need to be addressed for an AI integration to work reliably in production. The integration architecture around the AI model is often more important than the model itself.

Every AI integration we build is designed and delivered personally by Owen Jones, OLXR's founder and lead engineer. We use the OpenAI and Anthropic APIs extensively in our own practice and bring practical experience of integrating these models into production software - including the failure modes and limitations that are not apparent until you try to build something real with them.

Who This Is For

Businesses that want to add AI-powered features to existing software without rebuilding

Development teams that need experienced help with AI integration architecture

Organisations that have experimented with AI APIs and want production-grade integration

Companies that want to add AI capabilities to their product as a competitive differentiator

Businesses that need AI features integrated with their existing data and workflows

Businesses with data residency or compliance requirements that constrain which AI providers and regions can be used

What We Deliver

AI API Integration

Reliable connection of OpenAI, Anthropic, or other providers to your application.

Prompt Engineering

Well-designed prompts that produce reliable outputs for your specific use case.

Context Management

Handling conversation history, user context, and domain knowledge.

Output Validation

Checking and filtering AI responses before they reach users.

Cost Management

Queuing, throttling, and usage monitoring that keeps costs predictable.

Fallback Logic

Graceful degradation when the AI service is unavailable.

RAG Integration

Your specific knowledge base integrated into AI responses.

Interaction Logging

Comprehensive logging of every AI interaction for debugging, compliance, prompt improvement, and cost analysis.

Our Approach

Choose the Right Model for the Task

Different AI models have different strengths, costs, and latency characteristics. GPT-4o, Claude 3.5 Sonnet, and their equivalents are powerful but expensive and relatively slow. Smaller, faster models are appropriate for simpler tasks. We assess your specific use case and recommend the right model for the job - balancing capability, cost, and latency rather than defaulting to the most powerful available option for every task.

Engineer the Prompt Layer

The quality of an AI integration depends as much on the prompt design as on the model. We invest significant effort in prompt engineering - developing system prompts that constrain the model's behaviour appropriately, user prompt templates that provide the right context, and few-shot examples where they improve consistency. We also build the prompt management layer that makes prompts maintainable and testable rather than hardcoded strings scattered through the application.

Build for Observability

AI integrations in production need to be monitored continuously. We build logging of every AI interaction - inputs, outputs, latency, cost, and any validation failures - so that you have visibility into how the integration is performing and can identify problems before they affect users at scale. We also build the tooling to review AI interactions and identify cases where prompts or validation rules need to be updated.

Why Choose OLXR

We use the OpenAI and Anthropic APIs daily in our own practice. We know the failure modes, the cost traps, and the gap between what works in a playground and what works in production at scale.

Senior-Led

Built by someone who integrates AI APIs daily

Model Expertise

Deep experience with OpenAI, Anthropic, and alternatives

Cost-Managed

We build cost controls into every integration

Long-Term Support

We monitor and improve integrations after launch

The integration architecture around the AI model is often more important than the model itself.

OJ

Owen Jones

Founder & Lead Engineer

Technologies We Use

OpenAI

Claude

ASP.NET Core

Python

AWS

Azure

REST APIs

Vector Databases

n8n

Don't see your stack? Get in touch.

Frequently Asked Questions

Both are excellent and the right choice depends on your specific use case. OpenAI's GPT models have the largest ecosystem and the broadest range of capabilities. Anthropic's Claude models are particularly strong for tasks involving long documents, nuanced instruction-following, and contexts where safety and honesty are important. Many production integrations use both - routing different tasks to the model best suited to them. We will recommend the right approach for your specific requirements.

AI API costs can be significant at scale. We build cost management into every integration - using the smallest model that meets the quality requirements, implementing caching for repeated queries, monitoring usage against budgets with alerting, and designing the user experience to minimise unnecessary AI calls. We also provide transparency on expected costs during the design phase so there are no surprises in production.

AI API services have occasional outages and rate limit events. We build fallback logic into every integration - whether that means queuing requests to be processed when the service recovers, falling back to a rule-based alternative, or presenting a graceful degraded experience to the user. The application should never fail catastrophically because an AI service is temporarily unavailable.

Both OpenAI and Anthropic offer API configurations that do not use your data for model training. We configure integrations to use these settings as standard, and we are transparent about what data is sent to which services. For use cases where business data cannot leave your infrastructure for compliance reasons, we can implement solutions using locally-hosted open-source models.

Related Services

AI Solutions

Practical AI for business

AI Assistants

Intelligent assistants and chatbots

Integrations

Connect your systems and automate workflows

Ready to Add AI to Your Software?

Tell us what AI feature you want to build. We will give you an honest view of which model is right, what the integration involves, and what it would cost to run in production.