AI & ML Solutions
LLM Integration Services
OpenAI, Llama & RAG — Production-Grade LLM Integration
Add large language model capabilities to your existing product or internal tools. From OpenAI API integration to private Llama deployments — production-grade, with RAG, guardrails, and cost optimisation built in.
LLM Integration Capabilities
API Integration & Prompt Engineering
Connect your product to OpenAI, Anthropic, or open-source LLM APIs with production-grade prompt templates, context management, and token cost optimisation.
RAG Pipeline Development
Retrieval-Augmented Generation: ingest your documents, PDFs, databases, and internal knowledge into a vector database, then surface the right context with every query.
Private LLM Deployment
Self-hosted open-source models (Llama 3, Mistral, Phi-3) on your AWS or Azure infrastructure. Your data never leaves your environment — mandatory for HIPAA and GDPR use cases.
Streaming & Real-Time UX
Token streaming for fast-feeling responses, structured output parsing, function calling, and tool use — integrated into your existing React or mobile frontend.
Fine-Tuning & Evaluation
Domain-specific fine-tuning on your data, systematic evaluation frameworks, and regression testing to catch prompt regressions before they reach production.
Guardrails & Safety
Input validation, output filtering, PII detection, hallucination mitigation, and audit logging — the safety layer every production LLM integration needs.
LLM Features We Integrate
Models We Work With
OpenAI
GPT-4o, GPT-4 Turbo, o1
Anthropic
Claude 3.5 Sonnet, Claude 3 Opus
Meta
Llama 3 (8B, 70B, 405B)
Mistral
Mistral 7B, Mixtral 8x7B
Gemini 1.5 Pro, Gemini Flash
Microsoft
Phi-3, Azure OpenAI
Frequently Asked Questions
Which LLMs do you integrate with?
We work with OpenAI (GPT-4o, GPT-4 Turbo), Anthropic (Claude 3.5 Sonnet, Claude 3 Opus), Meta (Llama 3), Mistral, Google (Gemini Pro), and open-source models self-hosted on your infrastructure. We are model-agnostic and select the best model for your specific use case, latency requirements, and data residency constraints.
Can you integrate an LLM without sending our data to OpenAI or Anthropic?
Yes. We set up private LLM deployments using quantized open-source models (Llama 3, Mistral, Phi-3) served via vLLM or Ollama on your own cloud infrastructure. No data leaves your environment. This approach satisfies HIPAA, GDPR, and SOC 2 data residency requirements.
How long does LLM integration take?
A basic LLM feature integration (e.g., adding AI-generated summaries or a chatbot widget to your existing product) takes 2–4 weeks. A full RAG pipeline with document ingestion, vector search, and a custom UI takes 6–10 weeks. A private LLM deployment with fine-tuning and guardrails is a 3–4 month engagement.
Ready to Add AI to Your Product?
Tell us the feature you have in mind. We'll propose the right model, architecture, and integration approach — and give you a fixed-price estimate within 48 hours.
Also see: AI & ML Solutions · AI Agent Development · Custom Software Development