AI strategy consulting for your first build.
AI strategy consulting from Precision picks the work worth automating first. You get a ranked shortlist, a data map and a first-build plan. It is the first step of every Managed engagement.
Recurring work from the discovery conversation, with assumptions to test.
- 01Client handoff preparation
Evaluate first · recurring work with a named reviewer.
- 02Document completeness check
Confirm the required-document list before a build.
- 03Client status reporting
Confirm access to the source records first.
What you get
A ranked shortlist of workflows to evaluate first, with the assumptions behind each one written down to test.
A data map: what's ready, what's scattered and what's missing for each workflow on the shortlist.
A risk view of client data, approvals and policy, including who approves what in each workflow.
A first-build plan you keep, covering your data pipeline and first agents, whether or not you build them with us.
AI readiness assessment
Readiness depends on the specific job. We check four things before recommending a build:
Data: which records the job needs, whether they're usable and where gaps need a person's attention.
Systems: what your current tools and supported connections already do, and which access must be confirmed.
Workflow: a process owner, rules your team can write down, real examples for testing and a named reviewer.
Governance: permissions, client-data handling, approval points and who maintains the workflow after launch.
What a good first workflow looks like
Usually a recurring handoff, a document check or preparation before a review: work that repeats, follows rules your team can write down and produces something a person can check.
Questions
Do we need to be "AI ready" first?
No, and most businesses aren't. The assessment shows what's ready today and what your data pipeline needs before agents can do their best work.
Who needs to be involved?
An owner sponsors it, your operations lead and a few people who do the work walk us through it, and your IT lead joins for the data and security review.
How do you measure whether AI is worth it?
Before a build, we agree what to compare on that workflow: handling time, review effort, how exceptions are handled and whether handoffs arrive complete. We don't promise savings in advance.
What if our current tools already cover the job?
Then the plan says so. We check what your current tools and supported connections already do first, and recommend a build only for the part of the job they don't cover.
What happens after the plan?
You decide. Most teams move straight into building their pipeline and first agents with us on Managed, but the plan is yours to keep.