LLM Solutions & Fine-tuning
AI that reasons, retrieves, and decides — reliably.
We design, fine-tune, and deploy large language model systems that go far beyond chat — domain-adapted models, citation-grounded RAG pipelines, and agentic workflows that take real actions. We work with open-weight models (Llama, Mistral, Qwen, DeepSeek) so the weights, data, and IP stay yours, on your infrastructure.
What We Deliver
Fine-tuning & domain adaptation
LoRA, QLoRA, PEFT, and full fine-tunes on Llama 3.x, Mistral, Qwen, DeepSeek for your domain and tone.
RAG pipelines
Retrieval-augmented generation with citation grounding and zero-hallucination guardrails (LangChain, LlamaIndex, Haystack).
Agentic workflows
Tool use, function calling, and multi-agent orchestration with LangGraph that take real-world actions.
Private LLM hosting
Production inference endpoints (vLLM, TGI) for your fine-tuned models — VPC-isolated or air-gapped.
Evaluation & guardrails
Output validation, hallucination reduction, red-teaming, and continuous eval harnesses.
Prompt & reasoning optimisation
DSPy-based systematic optimisation for complex, multi-step reasoning chains.
Use cases by industry
Where teams put LLM & Fine-tuning to work in production.
Clinical decision support and prescription-understanding copilots grounded in patient records.
Contract clause extraction and citation-grounded review with no hallucinated references.
Document-grounded credit memos and policy-compliant customer support agents.
Knowledge agents over SOPs, manuals, and maintenance logs for floor technicians.
Internal knowledge assistants that cite the source doc for every answer.
See it in action
Live demos and sample outputs.
Models, frameworks & tools
Frequently Asked Questions
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