The problem
Most firms are busy with AI. Few make it count.
As AI budgets come under scrutiny, activity alone is no longer enough. Companies need to demonstrate measurable value.
Activity without value
Licences and pilots multiply, but nobody can show the return, and that spend is the first to go.
Delegated, not led
AI is handed down the organisation instead of led from the top, so it never connects to the strategic objectives.
Prototypes that never become reliable
Building an agent is easy. Building one the business can trust, every day, is hard.
Technology people do not adopt
Tools arrive without the people who do the work, and usage fades after launch.
What we do
Business judgement first, technology second.
The difference is what happens before anything is built, and how the work is delivered afterwards.
01Assess and prioritise
A short, fixed-scope assessment. Strategic objectives set from the top, a map of the workflows and where capacity goes, and a quantified investment case for the priority workflows: costs, benefits, assumptions and success measures.
02Build and embed
Where the case stacks up, we design and build reliable AI workflows, working with your team. They run through our portal or are integrated into your own systems, whichever fits best.
03Measure and improve
Benefits are verified against the baseline after deployment, with clear ownership so the workflow keeps improving after go live.
You leave the assessment with a decision, not another report: prioritised opportunities, an evidence-based investment case and a clear plan for implementation. If the economics do not support a build, we say so.
Who we work with
One company, or a whole portfolio.
Companies
Management teams who want AI tied to their strategic priorities and the P&L. We assess, build where the case stacks up, and measure the return.
Investors
Private equity and other investors with a portfolio-wide mandate. Methods run across companies, so what is proven in one carries to the next: workflows, benchmarks and investment cases. Each company's data stays its own.
Our approach
A working prototype is only the beginning.
Reliable AI needs trusted information, controlled workflows, human review and clear measures of success. Building and testing AI agents has taught us one lesson: a convincing prototype is relatively easy. Making it reliable enough for everyday business use is much harder.
- CaptureInputs collected once, in one place
- System of recordSources and standards the work is built from
- AutomateAgents draft, check and assemble the work
- Human gateA named person approves before anything leaves the firm
People throughout. We work with the people who do the work from the first interview to go live. Their best practice sets the standard, the workflow carries it to everyone, and they stay at the decisions.
About
Commercial judgement. Technical delivery.
Enacture was founded by Markus Massem, who has spent close to two decades in strategy and value creation, M&A and corporate development, across Jefferies, EY-Parthenon, Mastercard and Finastra. We work with specialist engineers who build to our specification, so the people who make the business case are accountable for what gets built.
Contact
Where could AI make a measurable difference in your business?
No technology pitch, just a practical discussion about where AI might pay.