LLM solutions that are accurate, grounded, and production-ready.
We build LLM applications and RAG platforms that answer from your data with citations, run within your cost and latency budgets, and ship with the guardrails enterprises require.
What we deliver
Large language models are powerful but unreliable without the right architecture. We design LLM systems with retrieval, evaluation, and guardrails so they're accurate, grounded, and safe in production.
- Grounded answers with verifiable citations
- Model-agnostic, cost-aware architecture
- Private and on-prem deployment options
- Evaluation pipelines for ongoing quality
LLM & RAG Development, end to end
LLM Application Development
Custom LLM-powered apps and copilots embedded into your product and operations, with prompt pipelines and evaluation.
RAG Platforms
Retrieval-augmented generation over your private data with hybrid search, re-ranking, and cited, grounded answers.
Fine-tuning & Adaptation
Domain fine-tuning of open and frontier models for sharper, cheaper, on-brand output and proprietary model assets.
Guardrails & Evaluation
Evaluation harnesses, refusal logic, and data-boundary enforcement so quality and safety are measurable.
Capabilities that power this solution
See it in production
Private LLM / RAGPrivate Financial RAG Platform
Finance & Banking
A private, on-prem / air-gapped RAG and document-intelligence platform for a fintech: analysts query financial documents, spreadsheets and live databases in natural language and get streamed, source-cited answers, with governed, need-to-know retrieval.
AR + AI EdTechEduarise
Education & EdTech
AR educational toys with a built-in AI tutor. Kids scan a printed World Map and explore countries, flags and quizzes in 3D, with a Llama-3.3-70B "Companion AI" answering their questions.
Frequently asked questions
RAG retrieves relevant facts from your data at query time, so answers stay current and cited. Fine-tuning adapts the model's behavior and style. We often combine both: RAG for knowledge, fine-tuning for tone and task accuracy.
We ground answers in your data with retrieval and citations, add re-ranking for relevance, build evaluation harnesses to measure accuracy, and add refusal logic so the system declines when evidence is weak.
Yes. We deploy self-hosted open-weight models inside your VPC or on-premise when data can't leave your environment, with no external AI API calls required.
Let's build your AI advantage.
Book a strategy call and walk away with a clear, technical plan, whether you build custom or start from an accelerator.