Wineberry
BerryEval

The assessment before the AI build.

BerryEval is a structured operating review that answers a simple question: where will AI create measurable leverage, and what needs to be true before we build?

Composite readinessSample
76/100

Conditionally ready - strong workflow signal, governance gap.

4≥70 ready
1conditional
1foundational
berryeval · scored rubricevidence-backed ✓
№ 01The Assessment

What BerryEval specifically does.

It is part interview, part systems review, part scored rubric, and part implementation brief. The point is to prevent vague AI exploration from becoming expensive software with no operating owner.

Understand the operating realityIntake

We capture workflows, tools, handoffs, data sources, pain points, constraints, and decision-makers. Not just generic AI goals.

Artifact · Operating brief

Score readiness across six dimensionsRubric scoring

Each answer is mapped to a rubric so we can distinguish real automation leverage from vague interest in AI.

Artifact · Readiness scorecard

Ground claims in artifactsEvidence review

We look for proof: sample workflows, CRM hygiene, data availability, approval paths, reporting gaps, and risk boundaries.

Artifact · Evidence register

Prioritize by value, effort, risk, and timingOpportunity ranking

Potential AI projects are ranked so quick wins, foundational data work, and high-risk ideas do not get mixed together.

Artifact · Opportunity map

Turn the evaluation into actionRoadmap handoff

The final output becomes the build brief for WineberryOS or a standalone decision artifact for leadership.

Artifact · 90-day roadmap
№ 02The Scoring Rubric

It scores readiness, not enthusiasm.

The rubric separates strong AI candidates from distracting ideas. A workflow can be painful and still be a bad first AI project if the data, ownership, or risk model is not ready.

Readiness dimensions · 06
  • 01
    Workflow clarity

    Are the processes repeatable enough to automate?

    82/100
  • 02
    Data readiness

    Can the system access clean, useful operating data?

    74/100
  • 03
    Decision leverage

    Would better recommendations change business outcomes?

    88/100
  • 04
    Automation fit

    Can AI safely trigger, route, or assist the work?

    69/100
  • 05
    Governance readiness

    Are approval paths and blocked actions clear?

    61/100
  • 06
    ROI confidence

    Can value be measured after implementation?

    79/100
№ 03Deliverables

The assessment becomes the plan.

BerryEval does not end with a PDF. It becomes the operating brief for WineberryOS: what to automate, what to leave alone, what data needs cleanup, and where governance must be in place before action.

01

Scorecard

A scored view of readiness, constraints, and confidence across the dimensions that determine whether AI will help now, later, or not at all.

02

Opportunity map

A ranked backlog of AI opportunities with expected value, effort, risk, dependencies, and recommended sequencing.

03

Build brief

The implementation-ready handoff: systems involved, first workflows, governance rules, data needs, and acceptance criteria.

04

Leadership artifact

A concise decision document operators can use to secure buy-in, reject weak ideas, or scope the first WineberryOS deployment.

Better than an AI audit.
Smaller than a transformation program.

BerryEval gives operators enough evidence to make a decision without committing to a giant engagement or chasing generic AI use cases that do not fit the business.