Retrieval, prompting and evaluation engineered as one system.
Generative AI features are easy to demo and hard to trust. The gap is closed by engineering: grounded retrieval, prompt versioning, structured outputs, evaluation datasets and cost controls that hold under real traffic.
We build LLM applications end to end, from document ingestion and vector search through to the user-facing assistant, with an evaluation harness that tells you when a change makes answers worse.
How this differs from AI Agents & Automation Solutions: Generative AI Engineering builds assistants that answer and summarise; AI Agents & Automation builds systems that take actions across your tools.
Natural-language access to policies, contracts and wikis with source citations and access control.
Score and summarise thousands of calls or tickets per cycle against a rubric.
Extract structured fields from forms, claims and reports, with a human review loop.
Live voice assistants built on realtime APIs for coaching, support or field use.
Chosen per project. We are vendor-neutral and will recommend what fits your constraints.
What data exists, who can see it, and which questions the system must answer well.
Measure retrieval quality first; most answer failures are retrieval failures.
Prompt design, tool use, structured outputs, UI, and the evaluation harness.
Latency, caching, cost caps, observability and a rollout plan with human oversight.
A retrieval audit on your real corpus: measured recall and answer faithfulness, followed by a prototype assistant with an evaluation harness.
The evaluation structure we use on every retrieval-augmented system. Copy it, fill in your numbers, and you wi…
Yes. We have deployed self-hosted vector databases and open models inside client VPCs where data residency requires it.
Grounded retrieval with citations, constrained output schemas, refusal paths when evidence is thin, and evaluation sets that track faithfulness over time.
We model token and infrastructure costs during design and build caching and routing so the cheapest capable model handles each request.
Blueprints for AI systems that survive production.
Agentic workflows and cross-system automation, with and without code.
Neural networks for sequences, perception and control.
Document OCR, image evaluation and visual inspection pipelines.
Send a three-line brief. We reply within one business day.
A retrieval audit on your real corpus: measured recall and answer faithfulness, followed by a prototype assistant with an evaluation harness.
