Generative AI, grounded in your business.
Large language models can draft, summarize, search and reason — but enterprise value comes from grounding them in your own knowledge, securing them properly and measuring the results. That is what we build.
Overview
We design and deliver generative-AI applications on leading foundation models, connected to your documents, databases and business systems through retrieval-augmented generation (RAG). Answers cite their sources, respect user permissions and stay inside your security boundary.
Every solution ships with evaluation: test sets, quality and safety metrics, cost tracking and human feedback loops, so you can prove accuracy before rollout and keep improving after it.
What you get with us.
AI assistants & copilots
Internal and customer-facing assistants for support, sales, HR and IT.
RAG & enterprise search
Ask questions across policies, contracts and knowledge bases with cited answers.
Document automation
Extraction, summarization and drafting for invoices, claims, contracts and reports.
Prompt & model engineering
Prompt design, fine-tuning and model selection balanced for quality, speed and cost.
Evaluation & guardrails
Automated evals, hallucination checks, PII filtering and content safety.
Secure deployment
Private networking, data residency, access control and audit logging.
Model & platform options
We choose the right model for each task and avoid lock-in.
- Amazon Bedrock
- Azure OpenAI Service
- Google Vertex AI (Gemini)
- Anthropic Claude & OpenAI models
- Open-weight models (Llama, Mistral)
- Vector databases & search (pgvector, OpenSearch, Azure AI Search)
Related articles
Agentic AI in the Enterprise: A Practical Guide
What agentic AI is, where AI agents deliver value first, how to design them safely with guardrails and human oversight, and how to move from pilot to production.
RAG vs Fine-Tuning: How to Ground Generative AI in Your Business Data
Retrieval-augmented generation and fine-tuning solve different problems. Learn when to use each, how they combine, and what it takes to run them in production.
Enterprise AI Governance: A Practical Framework
A practical AI governance framework for enterprises: policies, risk tiers, model inventories and controls, aligned with the EU AI Act, ISO/IEC 42001 and the NIST AI RMF.
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Learn moreReady to build what’s next?
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