Every engagement starts with a fitness assessment. This one is the fitness assessment on its own: an AI opportunity map, ranked use cases, a readiness assessment, a business impact model, and a responsible-AI plan. Each use case gets a go/no-go recommendation, in writing.
Most AI assessments arrive with a foregone conclusion: you need AI, and here's the roadmap. This one doesn't. PVT maps where AI could genuinely pay off, ranks each use case against what your organization can actually support, and says plainly where the answer is no.
A structured view of where AI can pay off across your business, and where it plainly can't.
Every candidate use case ranked by value and feasibility, so you know what to do first and what to defer.
A direct look at your data, tooling, team, and process. Are you actually ready to run this today?
The business case with numbers: cost, expected return, and payback.
We set up governance before the build: data handling, human-in-the-loop points, and named limitations.
A clear call on every use case we surface: proceed, wait, or don't. You decide with the full picture.
The assessment moves fast because an AI agent team does the scanning and synthesis legwork. We still review and test every recommendation before it reaches you.
We learn your business first: the goals, the data, the tooling, the team, the constraints. We name no use case until we have.
An AI agent team speeds up the scan across your operations and surfaces candidate use cases quickly.
We test each candidate against your actual readiness (data, tooling, team, process) and work out what it would cost.
A prioritized roadmap and a live readout: ranked use cases, the business impact case, and a go/no-go call on each.
This is the core of the assessment. Most firms selling an AI roadmap have an incentive to find opportunities everywhere. PVT doesn't work that way.
Where AI isn't the answer, we say so in the deliverable, so you can hold us to it.
A broken workflow or a missing dataset is often the actual constraint. Fixing that beats bolting AI onto a bad process.
Sometimes the right tool is simpler than an LLM, or there already is one. We'd rather say that than sell you a build you don't need.
You'll know why, in writing, for every use case we look at: proceed, wait, or don't.
The responsible-AI plan is part of the assessment itself. We do not use your data to train models. Human-in-the-loop by default. Limitations named in writing. A bias and fairness review for anything that ranks or scores. Planned to the data rules that apply to you. See our full Responsible AI commitments →
Tell us where you're considering AI. We'll map the opportunity, size the readiness gap, and tell you plainly, in writing, where it's worth building and where it isn't.
Let's talk