AI Readiness & Data Foundations
The groundwork that decides whether an AI project ships: honest assessment of your data, your workflows, and where AI is actually worth it.
SYS — Overview
Most AI projects fail before a line of model code is written. The data is spread across systems that disagree with each other, nobody has defined what a good answer looks like, and the use case chosen first is the one that demos well rather than the one that pays.
This engagement is the work that happens before the build: an honest audit of your data, your workflows and the use cases actually worth pursuing — including the ones we'll tell you to drop.
SYS — What you get
- A written assessment of your data: what exists, what's usable, and what needs work before a model can rely on it
- A ranked shortlist of use cases with rough effort and expected payoff for each
- Success metrics agreed in advance, so 'is it working?' has an answer
- A build plan you can hand to us, to your own team, or to nobody at all
SYS — Capabilities
AI readiness audit — data, workflows, and realistic use cases
Cleaning, consolidating & governing the data a model will rely on
Business case with success metrics agreed before anything is built
A prioritized roadmap, including where we recommend not using AI
Ideal for: Teams who know AI should be doing something for them, and want a straight answer on what's feasible before committing to a build.
SYS — Related work
SYS — Questions
What if the honest answer is that we shouldn't use AI?
Then that's the deliverable, and it's the cheapest possible outcome. A readiness assessment that stops a project costs a fraction of a build that quietly fails eight months in.
How long does an assessment take?
Usually two to four weeks depending on how many systems your data lives in. It's a fixed scope with a fixed price — you know the cost before we start.
Do we have to build with you afterwards?
No. The roadmap is yours either way. Plenty of clients take it in-house, and that's a fine result.
SYS — Other services
Need ai readiness & data foundations?
Tell us where the project stands and we'll come back with a clear read on scope, timeline and cost.