Prioritise and validate scattered AI initiatives before you invest in capabilities that won't create value.

A Minimal Viable Agent is the smallest useful AI agent that proves one workflow end to end — the data it needs, the human review points, and the business value — before you scale. One job, done well enough to make a build/buy/partner decision with evidence instead of opinion.

A pilot usually tests whether the technology works. An MVA tests whether a scoped workflow creates real business value and can be operated by real people. Many pilots impress in a demo and never scale, because they were never scoped against an owner, a metric, or a production workflow.

A focused external benchmark for one business domain. Internal teams naturally start from the processes and technologies they already know — which creates blind spots. We run a structured intake with your domain experts, benchmark relevant AI developments outside your field of view (peers, adjacent industries, AI-native organisations), and deliver a blind-spot and opportunity report with a prioritised shortlist: what to explore, accelerate, reconsider or stop.

ScopeRight is an independent AI scoping and validation partner. We help leadership teams prioritise which AI opportunities to pursue, validate the strongest ones through Minimal Viable Agents, and make a defensible implementation decision before significant budget is committed. Once a use case is validated, we can take it into operation: deploy a proven solution, configure specialist technology from our ecosystem, or build custom.

Yes. Operating partners and value-creation teams use ScopeRight to create a common AI decision system across portfolio companies: one prioritisation methodology, comparable business cases, kill criteria, and validated use cases — with reusable capability identified across the portfolio and execution kept company-specific where it matters. See our dedicated page on AI value creation for private equity.

No. Agencies typically start from implementation. ScopeRight starts one decision earlier: which problem is worth solving, what the workflow should be, what evidence is needed before scaling and which implementation model makes sense. Once that is clear, we can deploy, integrate or build the solution — but implementation follows the scope, not the other way around.

Yes, when custom delivery is the right implementation path. ScopeRight combines senior product and engineering capability with a specialist delivery network, so we can build focused solutions directly, assemble the right technical team for larger implementations, or deploy proven technology when building from scratch would add no value. The implementation model follows the scope.

Recommendations start from your business objective, not from a preferred vendor. In some engagements we may receive a referral or success fee from partners, but the shortlist is always fit-based and transparent.

Mid-market and larger companies — leadership, GTM, product, and innovation teams that have budget and ambition but need clarity before they commit.

Forward Deployed Engineering: senior engineers embedded with your team to ship production AI. Faster than traditional consulting, more accountable than freelance work. Best when scope is clear and stakes are high.

You walk away with an implementation-ready scope brief your leadership team understands — plus a recommended validation direction, implementation path or partner shortlist. We can stay involved through validation and delivery, or step out entirely.

Yes. We compare scope, budget logic, and assumptions side by side and flag overengineering, under-scoping, and hidden risks — so you can walk into the negotiation with clarity.

Free intake at €0. Scope Workshop from €5,000. Minimal Viable Agent Sprint from €12,500. Partner Matching from €7,500. Implementation is custom: it is priced once the validated scope, architecture and delivery model are known.

Yes. We are designed to make your internal team's next decision easier — not to replace them. Many engagements start because internal teams want a sharper scope before they go to procurement.

That is the most common starting point. The workshop is built for exactly this: translating broad AI ambition into a concrete, prioritised, validated use case.

No. Part of the scoping work is assessing what data and integrations are realistic for v1. We help you decide what is good enough to start and what can wait.

Yes. These are the most common starting points: lead qualification, proposal generation, CRM enrichment, marketing workflow automation, internal knowledge assistants, and product-led AI features.

Yes. We maintain a vetted and growing network of FDE boutiques, AI agencies, product studios, automation specialists, freelancers, and vendors — and only recommend when there is a strong fit.

A clear, honest read on whether your scope is workshop-ready, prototype-ready, or partner-ready — and what we recommend as the next concrete step.