How accurate are RAG systems really?

Measured, not asserted — we build an evaluation set from your real questions during discovery and report retrieval and answer accuracy against it, release over release. Production systems typically clear 90%+ on curated evaluation suites before launch.

What happens when models improve or prices drop?

The abstraction layer means swapping or mixing models is a configuration change, not a rebuild. Your evaluation harness tells you immediately whether the new model is actually better for your workload.

AI & Intelligent Systems

LLM systems built on your knowledge, accountable to your standards

RAG platforms, copilots, and document intelligence built on your data, inside your boundaries.

Discuss this capability All AI & Intelligent Systems

The problem

Generic chatbots don't know your policies, your contracts, or your customers. The value is in AI grounded in your data — but that demands retrieval engineering, evaluation, and data-boundary design that wrapper products skip.

What you get

Answers grounded in your data, with citations your auditors can follow
Hours of reading, drafting, and checking compressed to minutes
Model and vendor flexibility behind one abstraction layer

Capabilities

What the work actually involves

RAG knowledge platforms

Retrieval over your documents, wikis, and systems of record — with citations, permissions, and freshness pipelines.

Enterprise copilots

Assistants embedded in the tools your teams already use, drafting, summarising, and answering with your context.

Document intelligence

Extraction, classification, and verification across invoices, KYC, contracts, and claims at production accuracy.

Fine-tuning & model adaptation

Domain-adapted models where prompting hits its ceiling — with training data pipelines you own.

Evaluation harnesses

Regression suites for AI behaviour: accuracy, safety, and cost tracked release over release.

Proof

Where we have done this

All case studies

AI-assisted loan origination for a fast-scaling NBFC

An AI-assisted origination platform that reads documents, flags risk, and routes applications — approval turnaround down 68% with tighter, not looser, controls.

68%Faster approval turnaround

Before you ask

Questions about custom ai & llm development

Data-boundary design comes first: private cloud deployment, zero-retention API tiers, redaction layers where needed, and full interaction logging. Confidentiality is an architecture requirement, not a hope.

Bring us the problem. We will bring the architecture.

A discovery call takes forty-five minutes. You leave with our read on the problem, the shape of the system we would propose, and a straight answer on whether we are the right team for it.

Book a discovery call Send a brief instead

No sales deck
An engineer on the call, not an account manager
NDA before you share anything