The pressure to adopt AI arrives before the plan does
Most businesses know AI matters. Far fewer know which workflow to start with, what it would cost, and what should stay human.
The system object
many signals · few candidates · one to prove first
01
Signals
volumes · delays · rework · re-keying
02
Candidate opportunities
where capability is stuck
03
Priority
value · risk · time to result
04
Feasibility
data · access · controls
05 · Your decision
Decision
one to prove first, or none
Where it fits
If nobody can say where AI fits, that is the first job.
Leadership wants AI on the agenda. Vendors are pitching platforms. Teams are quietly experimenting with tools nobody has approved. What is missing is a clear view of where AI would actually change the economics of the business, and where it would simply add cost and risk.
The result is either paralysis or scattered pilots that never reach production. Both waste the one thing that matters at this stage: a decision about which opportunity deserves real investment first.
- A board or leadership request to "do something with AI" without a defined use case01
- Several small pilots running, none connected to a production workflow02
- Vendor proposals that are hard to compare because the underlying problem is unclear03
- Uncertainty about what data, systems and permissions an AI system would need04
- Concern about compliance, confidentiality or decisions being made without oversight05
- A budget that needs a defensible business case before it can be released06
The approach
We start from the process and the economics, not the technology
An opportunity assessment is a structured look at how work actually moves through your business: the volumes, the hand-offs, the delays, the rework and the decisions that require judgement. We map that against what current AI, automation and integration can reliably do, and against what your systems and data can support.
The honest outcome is sometimes that a process change or a deterministic automation will beat an AI system. We say so. The goal is capability per unit of cost and risk, not AI for its own sake.
1. Opportunity assessment
Working sessions with the people who own the work, followed by a review of the workflows, systems and data involved. We quantify effort, delay and error using your own figures rather than industry averages.
2. Readiness and feasibility
For each candidate use case we check whether the data exists, whether systems can be accessed, whether the task tolerates probabilistic output, and what controls would be required.
3. Prioritisation
Use cases are ranked by business value, implementation risk, time to a working result and dependence on other work. The first one should be meaningful and achievable, not the most ambitious.
4. Build, buy and platform decisions
Where an off-the-shelf tool fits, we recommend it. Where a custom system is justified, we explain why. Model, hosting and data-residency choices are made explicitly and documented.
5. Risk and human-control design
Before anything is built, we define which decisions stay with people, how exceptions are surfaced, and what an audit trail must show.
What we build
What you leave with
Illustrative of what a system in this area can include. Every build is designed from your workflow, not from a catalogue.
- 01An opportunity mapThe workflows where AI, automation or integration would create the most leverage, with the reasoning visible.
- 02A prioritised use-case listEach candidate scored on value, feasibility, risk and sequencing, so the order of work is defensible.
- 03A target architectureHow the first systems would connect to your CRM, ERP, documents and people, including where humans approve.
- 04An adoption roadmapA realistic sequence from first sprint to production system, with decision points rather than promises.
- 05A control frameworkRules for data handling, confidentiality, approvals and monitoring that the later builds must follow.
Decisions about AI stay with the people who own the business
Human authority · the decision to proceed is yours
An assessment produces recommendations, not commitments made on your behalf. Every prioritisation call is shown with its assumptions so your leadership can challenge it, change the weighting or stop.
- Named owners for each workflow in the map, on your side and ours
- Explicit statements of what a system may decide alone and what it must escalate
- Data and confidentiality boundaries agreed before any system touches real records
- A written recommendation that includes the option of not proceeding
Your current systems are the starting point, not an obstacle
Most opportunity lies in the gaps between systems that already exist: the spreadsheet beside the ERP, the inbox that feeds the CRM, the approval that lives in a chat thread. We inventory what you run today, how data moves between those tools, and where access is possible without disruption.
- ERP and finance platforms (SAP, Oracle NetSuite, Microsoft Dynamics, Odoo, Tally, Zoho Books)
- CRM and sales tools (Salesforce, HubSpot, Zoho CRM, Pipedrive)
- Email, calendars and collaboration suites (Microsoft 365, Google Workspace)
- Document stores and shared drives (SharePoint, Google Drive, Dropbox)
- Spreadsheets and internal databases that carry real operational load
- Customer support, ticketing and messaging channels
- Existing APIs, reporting tools and data warehouses
How an engagement runs
How an engagement runs
1. AI Leverage Call
A short conversation about your business, the workflows that consume the most effort, and whether there is a genuine opportunity worth assessing.
2. AI Opportunity Blueprint
The structured assessment described on this page: opportunity map, prioritised use cases, architecture, controls and roadmap.
3. Automation / AI Agent Sprint
A bounded build of the first prioritised workflow, proving value with real data under real controls.
4. Production intelligent system
The proven workflow hardened, integrated and handed over with monitoring and documentation.
5. Ongoing optimisation
Review of results, extension to the next use case on the map, and adjustment as the business changes.
Scope grows only as value is shown. The next workflow is chosen, not assumed.
Start with one honest conversation
If you know AI should matter to your business but not where it fits, that is exactly the question an assessment answers. Bring the workflow that frustrates you most. Discuss an AI opportunity with us and we will tell you whether it deserves a blueprint.
Questions about this service
Do we need to have chosen a use case before we talk to you?
No. Arriving without a use case is normal and often better, because the assessment exists to find the right one. It helps to know which parts of the business feel slow, manual or error-prone, but we will do the structured work of turning that into candidates.
What if the assessment concludes that AI is not the right answer?
Then the recommendation says so. Some of the highest-value findings are that a process should be simplified, that two systems should be connected, or that a rule-based automation will do the job with less risk. You still leave with a clear roadmap; it just may not be an AI roadmap.
How much of our team's time does an assessment take?
Typically a small number of working sessions with process owners, plus access to the systems and sample documents involved. We design the sessions to fit around operations rather than pull people out of them for days.
Can you assess a single department rather than the whole business?
Yes. Scoping to one function such as finance, sales operations or customer support is common and often produces a faster first result. The map can be extended later.
Will you recommend specific vendors or platforms?
Where a platform clearly fits, we name it and explain the trade-offs. We are not tied to any vendor, and we will recommend a custom build only when the workflow genuinely needs it.
Where is capability hiding in your business?
Bring one workflow that costs your team more time than it should. We will tell you honestly whether AI, automation or a better system belongs there.