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Leone Intelligence Systems

Systems

Move one enterprise AI workflow from decision to operation.

Three ways in: a bounded review, a full build, or an evidence-led vendor decision. Each one names the owner, the data boundary, and the acceptance bar before spend.

04 ENGAGEMENT PATHS

Take the smallest step that retires the risk.

Advisory

AI workflow assessment

Stop/go before delivery

One workflow needs a stop/go before you commit budget, data access, or a build team.

Fit: an owner can name the workflow, what failure costs, and who decides.

You get: a decision record, a viable scope, and the risks in writing.

Risk: capped at one bounded review, before implementation.

Book the review
Delivery

Production AI delivery

Build with acceptance gates

One team maps, builds, evaluates, deploys, and hands over the workflow as an operating system.

Fit: the owner can make data, integration, review, and acceptance calls.

You get: a working system, the evidence bundle, the runbook, and owned source.

Risk: release gates agreed up front — a missed gate is an unpaid milestone.

Scope the build
Procurement

RFP and vendor evaluation

Ready for vendor review

Your buying process needs a defensible scope, evaluation criteria, and straight answers.

Fit: procurement, technical evaluation, or a shortlist is already running.

You get: an RFP-ready scope grounded in evidence, ownership, and constraints.

Risk: delivery, security, and handover gaps surface before the award.

Prepare the vendor decision

The workflow, not the model, is the product boundary.

Data, models, tools, human review, evaluation, deployment, and handover form one lifecycle. Security, integration, stop conditions, rollback, and ownership are part of the delivery scope, not a later add-on.

  1. Intake
  2. Memory
  3. Tools
  4. Review
  5. Evaluation
  6. Deployment
  7. Handover