Large Language Models
LLM Development Services
We design and ship applications powered by large language models - choosing the right model, grounding it in your data with RAG, fine-tuning where it pays off, and adding evaluation and private deployment so your LLM features are accurate, secure and cost-efficient.
Our LLM capabilities
- Model selection (Claude, GPT, open-source)
- Retrieval-augmented generation (RAG)
- Fine-tuning & instruction tuning
- Prompt engineering & orchestration
- Evaluation, observability & cost control
- Private, on-prem & VPC deployment
What we deliver
Custom LLM apps
Domain-specific assistants and tools built on the best-fit model.
Enterprise search
Natural-language answers grounded in your internal knowledge.
Document intelligence
Extract, classify and summarise contracts, tickets and reports.
Private deployments
Run models in your own cloud or VPC for data control and compliance.
Explore related services
Build your LLM application
Tell us about your goals and we'll get back to you within 24 hours.
Frequently asked questions
Which LLM should I use?
It depends on your accuracy, cost, latency and privacy needs. We benchmark candidates - including Claude, GPT and open-source models - on your actual tasks and recommend the best fit, often mixing models per use case.
Should I fine-tune or use RAG?
Start with RAG - it grounds answers in your data, is cheaper and easier to update. Fine-tune only when you need a specific format, tone or task that prompting plus retrieval can't achieve.
Can we run an LLM on our own infrastructure?
Yes. We deploy open-source or licensed models inside your cloud, VPC or on-prem environment when data residency, privacy or compliance requires it.
How do you measure LLM quality?
We build evaluation sets from real examples and score accuracy, relevance and safety, then monitor those metrics in production so quality doesn't quietly regress.