Shipping an AI feature without derailing the roadmap
The company shipped a usable AI feature while retaining ownership of the code and configuration.
4 weeksAI feature MVP shipped
2 engineering sprintsavoided by using a focused external build
Services · Last updated June 2026
AI readiness and strategy, tied to the P&L
Blash AI is the artificial-intelligence division of Blash Advisory, a London-headquartered corporate finance and advisory firm specialising in AI readiness and strategy, serving founders, operators, corporates and funds across the UK, EMEA and the Far East.
We work with leaders who want AI to move revenue, response time and admin load, not a slide deck. Every recommendation ties to one measurable number.
What we build
- An operational AI audit of where hours and enquiries leak
- A prioritised roadmap scored by payback, not novelty
- Build-versus-buy recommendations for each candidate
- A target operating model your team will actually adopt
- A costed plan with the first workflow ready to build
Why it matters
Most AI programmes stall because the wrong first project was chosen. We start inside your real workflows, score each automation candidate on hours saved or revenue recovered against the cost to build, and tell you plainly where AI pays back and where it does not.
- A clear first project with a measurable return
- A roadmap your board and team can follow
- Honest guidance, including when the answer is an off-the-shelf tool
What we install first
The workflows we automate first
We name the workflow rather than sell a model. These are the jobs that pay back first.
- A scored shortlist of automation candidates
- An internal policy assistant with citations and an audit trail
- Knowledge search across your document estate
- Founder-productivity workflows on the startup track
- A customer-support assistant with a human in the loop
- A costed first build, ready to start
How it actually works
Week one is an audit, not a workshop. We sit inside the inbox where leads land, the spreadsheet where the numbers live, and the system nobody updates. Out of that comes a short list of candidates, each with a number attached. We then sequence the build so you see working software early, because a recommendation you cannot click is only an opinion.
Built to be governed
The strategy is written so a board can read it: each recommendation states the assumption, the expected return, the data it touches, and the controls required before it goes live. Nothing is proposed that we could not later defend in front of an auditor.
Our method
The Blash AI Audit Framework
- Map the real workflows and where time and money leak
- Score each candidate on payback divided by build cost
- Sequence the build, highest-return workflow first
- Define the controls and reporting before any deployment
Proof SaaS Financial services Manufacturing See all proof →
Where this has paid back
A governance-first AI rollout for financial services
The firm moved from informal AI usage to a controlled rollout model with clear ownership.
18AI use cases mapped and risk-scored
100%approved live workflows designed with audit trails
Finding the first AI workflow worth building
Leadership received a practical first-build recommendation instead of a generic AI strategy deck.
16workflows scored for payback and risk
3priority builds selected for the first roadmap
Questions about AI readiness and strategy
What does an AI readiness assessment actually produce?
A prioritised list of automation candidates from your real workflows, each scored on payback, plus a costed plan for the first build. It is a document you keep, even if you do not engage us further.
Is this only for large companies?
No. Smaller teams often move faster because workflows are easier to map and decisions move quicker. A five-person team with one painful workflow is frequently a better first project than an enterprise pilot.
How long does the audit take?
Typically two weeks. One week mapping your workflows and data sources, then a short list of scored candidates and a recommended sequence.
What if AI does not make sense for us?
We will tell you. If an off-the-shelf tool solves the problem, or the payback is not there, we say so rather than sell a build.
Do you tie recommendations to numbers?
Yes. Every recommendation maps to one measurable outcome: hours saved, leads recovered, support resolved, or reports produced. If we cannot put a number on it, we do not propose it.
Ready to build this?
Book a call and we will map the first workflow worth automating
Book an AI audit → Explore the rest
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