For teams choosing their first use case or checking what needs to be ready before moving an idea into a pilot.
Nemely delivery view
Your AI readiness
01Useful tasks and clear limits
02Data, access and controls
03Pilot planning and evaluation
A few organizations we've worked with
What’s included
Start with useful work and clear responsibilities.
We look at the business need, the information AI can use and how people will check and operate it.
What we work towards
Work + value + boundaries
01 / Start with the work
Choose a useful starting point
Identify a task where AI could help, then assess its value, risks and the decisions people must keep.
✓Users, tasks and measurable outcomes
✓Use cases ranked by value and feasibility
✓Human decisions and limits on AI actions
What we work towards
Grounding + access + control
02 / Prepare the foundations
Check data, access and controls
Review what the copilot or agent can use and do, and what your systems and teams need to support it.
✓Data quality, reliable sources and ownership
✓Permissions, connectors and security controls
✓Governance, environments and ongoing operations
What we work towards
Pilot + evaluate + learn
03 / Prove responsible value
Plan a pilot people can evaluate
Set out a focused trial with clear measures, representative users and checks for both useful and unexpected results.
✓Scenarios, evaluation criteria and failure handling
✓Human review, feedback, monitoring and escalation
✓Roles, skills, training and adoption needs
This service covers assessment and planning for a pilot. We agree the products, use cases and review depth with you; building or running a pilot and implementing improvements are scoped separately.
How we work
From an AI idea to an informed next step.
01
Choose the use case
Agree the task, users, intended outcome and limits on what AI may do, then compare starting points.
02
Assess readiness
Review data, permissions, governance, systems and the skills and operations needed to support the use case.
03
Design the evaluation
Plan representative scenarios, success measures, human review and the response to failures for a focused pilot.
04
Agree the next steps
Prioritize gaps, owners and the work needed for a pilot, adoption and any later release.
What you take away
A clear view of readiness. A practical next step.
We agree the outputs around your use cases. Findings identify what to improve and test; they do not certify compliance or guarantee AI outcomes.
01
Prioritized use cases with intended outcomes and limits on AI actions
02
Data, permissions, security and system readiness findings
03
Findings on governance, operations, skills and adoption
04
A pilot and evaluation plan with human review and failure handling
05
Prioritized improvements, responsibilities and criteria for the next step
FAQs
Your questions, answered.
A few practical answers before we talk about your project.
Which AI technologies does the assessment cover?
The scope can include Dynamics 365 copilots, Microsoft 365 Copilot, Copilot Studio agents, Power Platform automation and custom agents. We agree which products and use cases are relevant to your decision.
Do we need a specific AI use case first?
Not necessarily. We can help identify and prioritize use cases. The assessment then focuses on a real task, its users, the intended outcome and the risks involved.
What affects the cost and timing of the assessment?
The use cases, products, available data and depth of investigation shape the work. We agree scope with the business, IT, data, security and change colleagues involved, including the information and time needed from your team.
How do you assess data, security and compliance risks?
We review relevant data sources, quality, ownership, sharing, least-privilege access and connector behavior for the intended use case. This identifies readiness gaps; it is not a security certification, penetration test, formal compliance or privacy impact assessment, or legal advice. Specialist security, privacy or legal review may also be needed.
How do you judge AI quality and value?
We define representative scenarios, expected behavior, acceptance criteria and failure categories for a pilot, combining structured evaluation with human review. AI outputs can vary, and an assessment does not guarantee business value. A pilot must demonstrate value with representative users, credible measures and an operating approach the team can sustain.
What happens after the assessment?
The findings may point to data or access improvements, governance work, training, process changes, a focused pilot or a decision to pause. Building and running a pilot, implementing a solution or providing ongoing support are separately agreed work.
Start a conversation
Let’s find your next step with AI.
Tell us which work you want to improve, who would use the AI and what feels uncertain about your data, systems or readiness.