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AI Harness

Take AI from pilot to production

Your team already has AI pilots running. AI Harness takes the right workflow into production, with clear rules, a named owner and numbers you can track.

Example workflowSupport ticket triage
Ready for production
AccessReads only the helpdesk and the knowledge base.
RulesDrafts replies. A person sends anything that reaches a customer.
OwnerThe head of support owns the results.
MeasurementTime to first reply, against a 4h 10m baseline.
Failure planWhen unsure, it hands off to a person and logs why.
CostCost per ticket, tracked every week.
What we're seeing

Plenty of pilots. Few in production.

Most teams have proved AI can do the work. What's missing is everything around it.

01

The demo works, then it stalls

Everyone likes the pilot, and nobody knows what it takes to run it every day.

02

Nobody owns it

When an agent gets something wrong, it is unclear who fixes it or who decides it is safe to continue.

03

The costs are a guess

Without a baseline, nobody can say whether the agent saves money or adds a new bill.

04

The tools change every month

New agent platforms launch constantly, and picking one feels like a bet.

Our point of view

Rent the plumbing. Own the judgment.

The harness is everything around the AI model: what it can reach, the rules it follows, who approves its work, how it's measured and what happens when it gets something wrong. Harness platforms improve every month, so rent them. The decisions about which work to automate and where the lines sit belong to you, and we help you keep them.

What you rent

  • AI models
  • Agent platforms and harnesses
  • Hosting and monitoring

What you own

  • Which work gets automated
  • The rules and approval points
  • Owners, budgets and the call to scale
How it works

Two steps, each with its own scope

Step 1 · Fixed scope

Harness Readiness Assessment

We look at the work you want AI to do and design how it should run before anyone builds.

  1. Workflow inventory: the work you are piloting or considering, mapped end to end.
  2. Suitability: which workflows suit an agent. "Don't build an agent" is a valid answer.
  3. Baseline economics: what the work costs today, so savings are measurable.
  4. Operating boundaries: what the agent can reach, and where a person approves.
  5. Harness and infrastructure: the platforms that fit your stack, compared side by side.
  6. Ownership and failure design: who owns it, and what happens when it gets something wrong.
  7. Reference architecture and roadmap: the plan for your first workflow and the ones after it.
Step 2 · Its own scope

Agent Production Pilot

We take one workflow from the assessment into production, with your team, and measure it against the baseline.

  • One workflow from the assessment, chosen together
  • Built on the harness the assessment selected
  • Live with real users, rules and approvals
  • Measured against the baseline
  • Handed to the owner named in the assessment
Who it's for

Built for teams ready to go further

  • You have AI pilots running and none in production yet.
  • You run a small or mid-sized business without an in-house AI or platform team.
  • You want proof in numbers before you scale.
  • You want to own the decisions, whatever tools you pick.

Just getting started with AI?

Start with AI for your team: a knowledge base, the right tools and the habits that get hours back every week.

See AI for your team →

Questions

Good to know

Do we need to choose a platform first?

No. Comparing harnesses and infrastructure is part of the assessment, so you choose with your own workflows and numbers in front of you.

What if an agent is the wrong fit?

We say so. "Don't build an agent" is a valid outcome, and it saves you a build you would regret.

Do we have to do the pilot?

The assessment stands on its own. You keep the architecture and roadmap, whether you build with us, with your own team or later.

Which models and tools do you work with?

We stay tool-agnostic: models from Anthropic, OpenAI, Google, Microsoft and AWS, plus the agent platforms built on them. We recommend what fits your systems and your rules.

How is it priced?

Each step has its own scope and price, agreed before work starts. We quote after a first call, once we know the workflows involved.

Let's look at your pilots

Select all that apply
Select stage

What happens next

  1. We read your note and reply within two business days.
  2. A 30-minute call on the workflows you're piloting and what's holding them back.
  3. You leave knowing whether the assessment fits, whether or not you work with us.

Prefer email? hello@kuadro.ai