Make your company AI-native

Move past chatbots for everyday work to AI that transforms how your organization runs.

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How a company becomes AI-native

Most companies meet AI the way they met every tool before it. Licenses go out, a few people use them well, and the rest of the organization keeps working the way it did. The software sits beside the work.

An AI-native company runs its repeat work on autonomous agents. Tickets are triaged, invoices matched and reports drafted before anyone opens them. A person stays in control of anything that writes or sends, and the next process is already queued for deployment.

Companies get there one process at a time. The first workflow runs on real work, with your team approving what goes out. The skills and connectors from that first workflow carry the second, so each process is quicker to deploy than the one before.

The phases of a successful rollout

  1. Establish a strategy

    We work with your team to find the most critical workflows, agree what good looks like, and pick the first one.

    Harriet leads

  2. Build alongside your team

    We build with the people who do the work every day and solve the edge cases together, so the operational knowledge stays inside your business.

    Built together

  3. Your team takes ownership

    We document the setup and configure security policies. Your team runs and expands the system from there.

    Your team owns it

  4. Work compounds, adoption spreads

    One person builds a skill and everyone who should have it gets it. Every workflow in production shows what sits beside it, so picking the next one is quick.

    Your team expands it

Engineers who work with your team

  1. 01

    Map the process with the people who run it

    We sit with your process experts, document the steps and exceptions, and define what good looks like.

  2. 02

    Connect systems and build the skills

    We configure connectors and skills on live data in week one. We solve edge cases together instead of filing them away.

  3. 03

    Validate on real tasks with human approval

    Your team reviews every output until reliability is proven. Any action that writes or sends waits for human approval until you decide otherwise.

  4. 04

    Govern, document, and hand over

    We establish security policies, assign internal owners, and document the playbook. Each new workflow builds on the foundation of the last and work compounds.

Two colleagues working through a plan on a whiteboard

Reduce the risk of adopting AI

Fact An enterprise license A consultancy Harriet
What you buy Seats and admin controls A project team on a stack they do not control The team and the stack, from one place
The first workflow in production Yours to build Built for you, on their timeline Built with the people who do the work
Who owns it at the end Whoever picked it up The consultancy, until the contract ends Your team, with the setup documented
When something is missing A ticket on the vendor’s roadmap A change request We build it in
Cost basis Per seat, often with an annual commitment and a seat minimum Day rates or a project fee, plus the license Quoted per organization, no seat minimum, no annual commitment
The second workflow Starts from zero A second project Reuses the skills and connectors from the first

Questions we get asked

How does a company become AI-native?
A company becomes AI-native by putting one real process on an AI workflow and then repeating it. The fastest route for a mid-size company is an implementation partner that also runs the platform. Harriet is that partner: our team builds the first workflow with the people who do the work, puts it into production, and hands it over with the next one already queued.
What does an AI implementation partner do, and how is it different from an AI consultancy?
An implementation partner puts your processes on AI and leaves them running, owned by your team. A consultancy advises, and if it builds, it builds on a platform someone else controls, so when something is missing it becomes a change request. Harriet does the implementation on a platform we build ourselves, so a gap gets built in rather than written up.
Which companies help a mid-sized business become AI-native rather than just selling it software?
Three kinds. Consultancies that deploy on another vendor’s stack, software vendors with a services team attached, and Harriet, where the team and the stack come from the same place. For a mid-size company the difference shows up at the first hard case: who fixes it, and whether your own team owns the result.
How do we get the first AI agent into production in a mid-size company?
Pick one process that takes too much time, in one team, with one person who knows it best. We map it with them, connect the systems it touches, build the workflow and put it into production with a human approving anything that writes or sends. Then we document it and pick the next one. The rollout plan on this site walks through the phases.
How much does a Claude Enterprise implementation project cost?
Anthropic publishes no implementation price. The $20 seat fee buys the software and the admin controls, not the work of putting Claude into your processes. With Harriet, implementation and platform are quoted together, per organization. The full answer is on the Claude Enterprise pricing page.

A deployment team that makes adoption stick

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