Glossary · The Truth Score
Leverability read
The Leverability read says which AI ideas your data can use now, which need fixes first, and which it can’t support at all, with the reason in your own records.
- Deploy now
Lead scoring
Contact and win or loss history complete
- Needs work
Customer churn prediction
117 customers with no shared ID
- Blocked
AI agent on collections
Payment terms live in a spreadsheet
In plain terms
The Truth Score™ says how far data can be trusted. The Leverability read answers the next question, the one the budget depends on: what can this data actually run?
It takes each AI play in front of the business, from a vendor proposal, a business plan, a value creation plan or a board paper, and works out what that play needs from the data: which records, which fields, how much history, and which systems have to agree. Then it checks whether that data is there and can be trusted.
Each play is marked one of three ways. Deploy now: the data it needs is present and holds up. Needs work: a defined fix unblocks it, and the fix is named. Blocked: the data it depends on doesn’t exist yet, or lives somewhere the play can’t reach, such as a spreadsheet on one person’s laptop.
Every mark comes with its reason, in the client’s own records: “117 customers with no shared ID between CRM and billing” rather than “data quality concerns”. That makes the read something a board can vote on, and something a fixer can act on.
It is a read, not a score. AI plays don’t average out: one blocked play can matter more than three that are ready, so the read is shown play by play rather than collapsed into a number.
- See it in a real memoThe sample Truth Score ReadReal engine output on generated test data, not a client
- How we measure itThe method, including the capPillars, weights, bands and what is never guessed
- What happens to your exportsSecurity and data handlingExports only, NDA and data processing agreement first
Questions
Leverability read, answered.
The questions people ask about Leverability read, answered in plain English.
Book the callWhy isn’t Leverability a score?
Because AI plays don’t average out. A churn model that is blocked doesn’t become half-ready because lead scoring is ready. Each play gets its own mark and its own reason.
Where do the AI plays come from?
From whatever is in front of the business: a vendor proposal, the business plan, a growth strategy, a value creation plan or an investment thesis. If there is no document, we agree the plays on the first call.
Does “deploy now” mean we should buy the product?
No. It means the data the play needs is there and can be trusted. Whether the product, the price and the vendor are right is still your decision. We sell no AI, so we have no view on which one you buy.
Related terms
Keep reading.
- The Truth Score Truth Score™ The Truth Score™ is DataTruth’s score out of 100 for how far a company’s data can be trusted, built from six weighted pillars and placed in one of four bands, A to D. Read the definition
- Method Plan test A plan test reads a business plan, growth strategy, value creation plan or investment thesis, pulls out the AI plays in it and the growth targets that lean on them, and shows play by play whether the data they need is there and can be trusted. Read the definition
- Method Remediation roadmap A remediation roadmap is a prioritised list of data fixes, each with an owner, an effort estimate and a “done when” test, written to hand to your own team or any outside firm. Read the definition
- AI readiness AI readiness AI readiness is whether a company’s data can support the specific AI it is about to pay for: whether the data can be trusted, and whether it can run that use case. Read the definition
Find out which of your AI plays can run. Before you pay for them.
Exports from two or more systems, matched between them, every red flag checked by hand. A signed memo with your Truth Score and a Leverability read, within 5 working days of complete exports.
Starts with a 30-minute call. Commits you to nothing.