AI Integration

AI where it helps the person using it.

Adding AI to a product, site or workflow you already have.

AI integration means adding AI to something that already exists: an application, a website, an internal tool or a workflow. The common jobs are reading documents and pulling out the details, drafting responses, summarizing activity, answering questions from a body of knowledge, and routing requests to the right person.

When a product only makes sense with AI at its core, we design it as AI-native from the start. The AI-Native Products & Agents page covers that work.

How we build it

Designed for the times it gets it wrong

Every AI feature is wrong sometimes, so we decide up front what happens when it is.

Answers from your own sources

A feature that answers questions draws only on the sources you define, shows where an answer came from, and says so when the sources don’t cover it. This site’s chat answers only from the site’s own pages.

Narrow access, approval where it counts

AI gets only the data and actions the task needs. Actions with consequences, like sending, publishing or changing a record, can be set to wait for a person’s approval.

Connected to your systems

The AI can work with any system that offers an API. Reading and changing are separate permissions, and we log what the AI does where it makes sense for the product.

Tested, and not tied to one model

Tested against real questions, and again as content changes. Models improve quickly, so a better one can be swapped in.

Where to start

Prove the AI can do the job first

We define the task and what a good result looks like, then prototype that part first, because whether the AI can do it reliably is the biggest risk. If it can’t, you find out early. If a simpler fix would do, such as a better form or one integration between two systems, we’ll recommend that instead.

For AI in how your own team works day to day, the AI Audit & Adoption and Workflow Automation pages go further.