For Advisory

Choose the right AI.
Deploy it well.

Independent advice for organisations deciding where AI fits, which tools to use and how to bring them into the business. Grounded in how AI systems behave once they are deployed.

For executive teams, transformation and technology leaders, operations and governance.

A man and a woman working on laptops at a long table in a wood-lined office.

Why organisations
work with Witcher.

We don't resell models, platforms or implementation. Our recommendation is shaped by your organisation, and sometimes the answer is a simpler tool, a process fix or not yet.

We start with the tasks, decisions and bottlenecks in each team, then look at where AI could help. Use cases come from how work gets done, not from a product demo.

Our advice draws on testing AI systems in real deployments. We weigh what a use case could reach, change or get wrong alongside the benefit it promises.

We help you set out who owns each use case, who approves changes and how decisions get made, so the work carries on without us.

Illustrative review of six AI requests from an operations team, each given a recommended route: an AI assistant pilot, an existing suite feature, rules-based automation or more data first
Illustrative advisory view: advice that isn't selling anything.

AI advisory,
in practice.

From the first shortlist of ideas to the decision to go live.

Illustrative chart plotting nine AI use cases by value and feasibility, with three shortlisted for discovery
Illustrative advisory view: find the use cases worth pursuing.

Find the use cases
worth pursuing.

Map where time, cost and risk sit across your teams. Prioritise use cases by the value they could bring, how feasible they are with your data and systems, and what could go wrong.

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Illustrative decision memo comparing building on a model API, buying a specialist product or extending a CRM suite for customer email triage
Illustrative advisory view: decide whether to build, buy or partner.

Decide whether to build,
buy or partner.

Compare building on a model, buying a product or extending tools you already pay for. Weigh cost, control, data handling, lock-in and the skills you have in-house.

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Illustrative supplier shortlist for a staff knowledge assistant, comparing three suppliers on data residency, access controls, audit logs and independent testing
Illustrative advisory view: choose vendors and models with evidence.

Choose vendors and models
with evidence.

Turn requirements into questions suppliers have to answer. Compare shortlisted products and models on fit, data handling, access controls and the evidence behind their claims.

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Illustrative rollout plan for a claims assistant, with pilot, integration, training and wider rollout stages and the checks needed before the second gate
Illustrative advisory view: plan a rollout that can hold.

Plan a rollout
that can hold.

Sequence pilots, wider rollout and the integrations behind them. Set the gates each stage must pass, so expansion follows evidence rather than enthusiasm.

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Illustrative AI use case register listing each use case with its owner, risk tier and status, and a new request awaiting review
Illustrative advisory view: set up governance that people follow.

Set up governance
that people follow.

Agree how new use cases are proposed, assessed and approved. Keep a register of what is in use, who owns it and the risk tier it sits in.

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Illustrative readiness review for an HR policy assistant across data, people, process and controls, with a go-live view for the pilot group
Illustrative advisory view: know when you are ready.

Know when you
are ready.

Check data, people, process and controls before go-live. Give leadership a clear readiness view and the conditions that should come with approval.

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Make your next AI decision
with a clearer view.

Tell us what you're weighing up and the decision you need to make.

Talk to Witcher