LLM integration
Add language models to your product, safely.
GPT, Claude, Gemini or open-weight models integrated into your applications with cost control, fallbacks and monitoring.
Why teams call us
Problems this solves
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01
Costs that grow without warning
Model usage billed per request can climb fast without limits and caching.
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02
One provider, one point of failure
An outage or a model change at the provider breaks your feature.
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03
Prompt injection and data leaks
User input can trick a model into ignoring instructions or revealing data.
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04
No idea if quality is slipping
Without evaluation, model updates can quietly change answers.
Our approach
We integrate language models into your web, mobile or backend systems through a small, well-tested layer that handles prompts, model selection, retries, fallbacks, caching, rate limits and logging. That layer keeps you able to change providers without rewriting your product.
Security is designed in: input and output filtering, protection against prompt injection, and strict control over which data reaches the model.
What is included
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Model selection
Commercial or open-weight models chosen per task on accuracy, cost and latency.
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Integration layer
One internal API for prompts, models, retries and fallbacks.
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Cost control
Caching, token limits, budgets and usage reporting.
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Security
Prompt-injection defences, output filtering and data minimisation.
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Structured outputs
Reliable JSON outputs validated against schemas.
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Evaluation and monitoring
Quality checks and alerts when behaviour changes.
What you receive
- Integration layer in your codebase
- Prompt and model configuration
- Evaluation suite
- Cost and usage dashboard
- Security review of the integration
- Developer documentation
Technology we work with
- OpenAI API
- Anthropic API
- Google Gemini API
- Azure OpenAI
- Amazon Bedrock
- Ollama
- Laravel
- Node.js
- Python
Industries
How an engagement runs
Every engagement starts with a signed agreement and an advance payment as set out in your proposal. Work begins once both are complete.
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01
Design
Use cases, models, data flows and limits agreed.
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02
Integrate
The integration layer built into your application.
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03
Evaluate
Quality, latency and cost measured against targets.
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04
Launch
Monitored release with alerts and reporting.
Ready to start? Talk to us directly.
Tell us what you need in a few lines. A specialist replies with next steps and a written proposal before any work begins.
Frequently asked questions
Can't find your answer? Ask us
Which model should we use?
Can we switch providers later?
Can we run models on our own servers?
Start with a conversation.
Share a few details. A specialist replies with next steps, usually starting with a short call.