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AI & data

Generative AI solutions

A general-purpose model knows a great deal about the world and nothing at all about your business. Everything useful happens in the layer between the two.

RAG pipelinesCopilots & agentsEvaluation harnessesGuardrails

We build retrieval-grounded assistants, copilots and automation on top of foundation models — with the retrieval, evaluation and guardrails that turn an impressive demonstration into something a regulated business can put in front of staff and customers.

What we build

Six shapes generative AI takes inside a business

Knowledge Assistants

Retrieval-augmented question answering across policies, contracts, manuals and tickets — answers with citations, so a reader can check them.

Workflow Copilots

Drafting, summarizing and triage embedded in the CRM, service desk or back-office screen your team already works in.

Agentic Automation

Multi-step processes where the model calls your own tools and APIs under an approval policy, with every action logged and reversible.

Document Generation

Proposals, responses, summaries and reports produced from structured data and templates, with a person approving before anything leaves the building.

Customer-Facing Chat

Support and self-service conversations with a strict scope, a defined escalation path and a tone that matches the rest of your brand.

Analytics Assistance

Internal tooling that lets a non-technical team query data, generate a report and reach an answer without a ticket in the analytics queue.

Delivery

How a generative AI engagement runs

  1. Scope

    Pick a use case with a countable baseline — handling time, deflection rate, cost per document.

  2. Ground

    Ingest, chunk and index the source material, with permissions carried all the way through to retrieval.

  3. Build

    Prompt design, tool calling, orchestration and the interface the people doing the work will actually use.

  4. Evaluate

    A scored test set of real questions, re-run on every change — accuracy, refusals, latency and cost tracked together.

  5. Ship and watch

    A staged rollout with feedback capture, so the evaluation set grows out of live usage rather than guesswork.

Guardrails

What makes it safe to put in front of people

These are not optional extras further down the roadmap. They are part of the first release, or the first release does not happen.

A word on pilots

The demonstration is the easy fifth of the work

A convincing generative AI prototype takes days. What takes the rest of the quarter is retrieval quality, permissions, evaluation, cost control, and the change management around a tool that is confidently wrong every so often.

We plan for that from the first week, which is why our engagements start with an evaluation set and a baseline number rather than with a model choice. The model is the part of this stack that is easiest to swap later.

Grow faster than you imagined

Tell us which service you are weighing up and what is behind it. We will come back with a route and a realistic sequence — not a sales deck.

Talk to our expertsCall the team
+1-562-916-3390 · Los Angeles, CA