LLM Integration Services for Production Business Systems
We integrate large language models into your products and workflows — with proper cost controls, reliability engineering, and observability built in from the start.
[ WHAT WE BUILD ]
AI capabilities your product actually needs.
Integrating an LLM is easy. Making it reliable, cost-controlled, and production-grade requires engineering discipline — which is where most implementations fail.
Product AI Feature Integration
Add AI-powered features to your SaaS product — smart search, content generation, summarisation, or classification.
Internal AI Assistants
Build internal tools that use your company's data to answer questions, draft communications, and surface insights.
Document Intelligence
LLM pipelines that read, classify, extract, and act on unstructured documents — contracts, reports, emails, transcripts.
Content Automation Pipelines
Generate, edit, and publish content programmatically — SEO briefs, product descriptions, support articles, and reports.
Semantic Search Systems
Replace keyword search with vector-based semantic search powered by LLM embeddings across your data.
Multi-Model Orchestration
Route queries to the right model based on complexity, cost, and latency requirements — GPT-4o for complex reasoning, lighter models for classification.
[ MODELS & STACK ]
What we integrate.
[ PROCESS ]
How we build production LLM integrations.
Requirements & Model Selection
Define the use case, accuracy requirements, latency constraints, and cost budget. Select the right model(s) for each task.
Prompt Engineering
Develop and test prompts systematically. Establish an evaluation framework before writing a line of integration code.
Architecture Design
Design the full integration — API calls, retry logic, streaming, caching, fallbacks, and monitoring hooks.
Integration Build
Build the production integration with proper error handling, rate limit management, and token cost controls.
Evaluation & QA
Run the integration against a real test set. Measure accuracy, latency, and cost. Tune until production-ready.
Deployment & Monitoring
Deploy with observability — log every LLM call, track token spend, monitor for regressions, and alert on errors.
[ FAQ ]
Common questions.
READY TO BUILD?
Let's engineer the system.
Most enquiries receive a response within 24 hours.
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