CEO
Where can AI change operating leverage, speed, service quality, or strategic focus?
AI opportunity assessment
Find the AI workflow worth building first.
Most companies have too many AI ideas and not enough clarity on which one should become a funded system. Ferre Torres B.V. helps leadership identify the workflows where AI can create value, reduce risk, and move quickly into an MVP or proof of concept.
- CEO priority
- CFO value case
- CTO readiness
- MVP shortlist
Assessment fit
Turn AI urgency into a ranked build plan.
- Map workflows where AI can reduce manual work, improve decisions, or create new service capacity.
- Separate attractive ideas from workflows with enough data, ownership, usage, and economic value.
- Identify where RAG systems, agents, dashboards, Company Brain architecture, or AI-native tools fit.
- Choose the first MVP or PoC with clear success criteria and a realistic path to production.
Executive questions
The assessment aligns business value with technical reality.
CFO
Which workflow has enough measurable value to justify budget and implementation effort?
CTO
Which data, security, integration, evaluation, and ownership constraints shape the build?
Users
Where is the current process slow, repetitive, hard to search, or dependent on manual coordination?
Assessment output
What the company can use immediately.
Opportunity map
A ranked view of AI use cases by value, feasibility, data readiness, stakeholder ownership, and risk.
Data readiness map
Key sources, permissions, quality gaps, retrieval needs, reporting inputs, and integration constraints.
MVP candidate
The first workflow to validate with users, success metrics, expected usage, and a production path.
Architecture notes
Recommended RAG, agent, dashboard, evaluation, monitoring, and governance components for the build.
Readiness checklist
A clear view of workflow ownership, data access, users, security constraints, usage profile, and scale criteria.
Assessment sequence
From many AI ideas to one build decision.
The objective is not to produce a generic AI strategy deck. The objective is to decide what should be built first, what must be validated, and what needs to be true before the system can scale.
- Discover
Capture workflows, systems, data sources, users, constraints, and current pain points.
- Prioritize
Score opportunities by value, feasibility, risk, sponsorship, and implementation speed.
- Design
Outline the MVP, AI components, architecture, evaluation plan, and operating model.
- Decide
Choose whether to build the first MVP, run deeper discovery, or pause a weak opportunity.
AI assessment questions
Questions companies ask before prioritizing AI opportunities.
What is an AI opportunity assessment?
An AI opportunity assessment identifies where AI can create practical business value by reviewing workflows, data sources, users, tools, risks, and the feasibility of a first MVP or PoC.
Who should join the AI assessment?
The assessment should include the business owner, a technical owner, and the people who understand the current workflow. Larger companies may involve CEO, CFO, CTO, operations, finance, data, or compliance.
What does the company get at the end?
The company receives a ranked AI opportunity map, data readiness notes, MVP or PoC candidates, architecture considerations, risk areas, and a recommendation for what to build first.
How does this lead to an AI MVP or PoC?
The assessment narrows many possible AI ideas into one or two workflows that are valuable, feasible, and measurable enough to validate through an MVP or proof of concept.
Assessment next step
Bring the workflows where your company feels AI pressure.
Share the buyer role, business area, current workflow, systems involved, expected users, and what would make the first AI build worth funding.