Pluscode
Proof of concept

Prove your AI use case in production.

One validated use case, built into a working pilot on your data and your stack in 4 to 6 weeks, measured against evals you trust, and closed with a clear rollout decision.

4 to 6 weeksIn your environmentFixed scope, single use caseTeams with a validated use case
Scope the PoC

Built to prove, not to demo

The proof of concept takes one validated use case and turns it into a working pilot in your environment: your data, your stack, your security constraints. It is not a demo built on cherry-picked examples. Everything we ship runs against representative data and is measured with an evaluation harness we design together in week one.

The engagement runs 4 to 6 weeks with a fixed scope. We start by locking the use case and defining the evals, then wire up the data, build against the harness, and harden the pilot for real traffic. You get a short written update every week and a working system you can inspect at any point, not a reveal at the end.

After the PoC you know, with numbers, whether the use case is worth rolling out. If it is, you have a pilot ready to extend, an eval harness to keep it honest, and a rollout plan with scope, cost, and risks. If it is not, you have saved a quarter of budget and learned exactly why, in writing.

What you leave with

A working pilot deployed in your environment, on your data
An evaluation harness with metrics your team agreed on
Documented eval results against the targets set in week one
A rollout plan covering scope, cost, risks, and operations
An internal pitch deck to secure budget and buy-in
Full ownership of code, prompts, and evals, no lock-in
Proof of concept

How the PoC runs

01

Scope and eval design

We lock the use case, define what success means in numbers, and build the evaluation harness first. If we cannot measure it, we do not build it.

02

Data plumbing

We wire the pilot into your real data sources, handle access, privacy, and formats, and assemble the representative test set the evals will run against.

03

Build against the harness

We build the pilot iteratively, running every change through the eval harness. Scores decide what ships, not vibes. You see the results move every week.

04

Harden

We stress the pilot with edge cases, adversarial inputs, and failure modes, then add the guardrails, fallbacks, and monitoring that production will demand.

05

Rollout decision

We put the eval results next to the targets from week one and hand over a rollout plan, or a clear, documented reason to stop. Your call, made on real numbers.

Who it's for

You have a validated use case, not just an idea.
You need hard proof before funding a full rollout.
You want it running on your data and your stack, not in a vendor demo.
You have a decision-maker ready to act on the results.

How to prepare

You do not need much, but the right people and access on day one make the weeks count.

A named product owner who can make scope calls within a day
Read access to representative data, agreed before kickoff
An engineer who knows the systems the pilot must touch
Security or compliance sign-off started, not necessarily finished

Questions, answered

What do we need to start?

A validated use case, access to representative data, and one decision-maker who can act on the results. We handle the build, the evals, and the environment setup.

How is this different from a demo?

A demo is happy-path theatre. We build in your environment and measure against real evals, so the results hold up when you pitch them internally.

What if the evals show it does not work?

That is a valid, valuable outcome. You get clear metrics and an honest written reasoning, which saves you from funding a rollout that would have failed.

Who owns the code and the model?

You do. The pilot, prompts, evaluation harness, and rollout plan live in your repos and your accounts. Fine-tuned models and their weights are yours as well. No lock-in.

What if our data is messy or unlabeled?

Expected. Part of the first two weeks is data plumbing: access, cleaning, and a representative test set. If the data genuinely cannot support the use case, you will know early, not in week six.

What happens after the six weeks?

Three options: your team takes the pilot forward with our rollout plan, we harden it into production together, or a fractional AI team runs it month to month. All three start from code you already own.

Where this leads

A pilot that passes its evals deserves a team that takes it to production and keeps it there. That is what the fractional AI team does.

Explore the fractional AI team

Scope your PoC

One call to check fit. No obligation.

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What you're booking
4 to 6 weeks · In your environment · Fixed scope, single use case
  • A working pilot deployed in your environment, on your data
  • An evaluation harness with metrics your team agreed on
  • Documented eval results against the targets set in week one
  • A rollout plan covering scope, cost, risks, and operations
  • An internal pitch deck to secure budget and buy-in
  • Full ownership of code, prompts, and evals, no lock-in
What happens next
  1. 1We match you with the right engineer.
  2. 2You hear back within one business day.
  3. 3A 30-minute call to scope it.
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