General AI Development

Generative AI & Language Models

Assistants, drafting tools and search that work from your own documents, with sources shown and a person approving what goes out.

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The challenge

Why this matters

General-purpose chat tools know a lot about the world and nothing about your policies, products or past decisions. They also invent answers when they are unsure.

Woman holding a tablet with an assistant panel beside a wall screen with a drafted document — Generative AI & Language Models

What it is

Generative AI & Language Models in plain words

We build systems around large language models and image models that answer from material you provide: manuals, contracts, policies, knowledge bases and media libraries. Answers cite the passages they came from so staff can check them.

We compare models for the task, including hosted and self-hosted options, and set up testing so you can see how answers change when the model or the data changes.

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Benefits

What you get

Grounded in your material

Answers draw on your documents and point back to them.

Model choice

We compare options for quality, cost and data-handling needs.

Guardrails

Topic limits, review steps and refusal rules are designed in.

Measured quality

Test questions with expected answers track quality over time.

How it works

From first call to first result

Step 1

Collect

Gather and clean the documents the system will use.

Step 2

Blueprint

Pick the model, the retrieval approach and the guardrails.

Step 3

Trial

Run your real questions and review the answers with your experts.

Step 4

Release

Launch to a small group, then widen with monitoring.

Details

What is included

Capabilities

Question answering over documents
Drafting and summarizing
Classification and tagging
Image generation workflows

Controls

Source citations
Content filters
Human approval steps

Operations

Evaluation test sets
Usage and cost tracking
Prompt and model versioning

Illustrative scenario

A city clerk's office gives staff a search box that answers ordinance questions with a link to the exact section, so nobody has to page through long documents.

Professional beside a stack of forms, with a scanned page and extracted fields on a monitor

Answers you can check

Every answer can show the passage behind it, so reviewers spend their time confirming rather than hunting.

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Questions

Common questions

Will our data be used to train public models?

We design to your data-handling rules and agree in writing which services may see your material before we start.

Can it run without an internet connection?

Some designs can run inside your own environment. We review what is feasible in the Blueprint step.

How do you deal with wrong answers?

We cannot promise there will be none. We reduce them with source grounding, testing and review steps, and we measure what remains. See AI Security & Governance.