Execlenz finds every AI and automation opportunity across your enterprise, prices each one, and shows the order to build in, with a proof of concept standing at the end.
Rather look first? Explore the four platforms →
Invoice matching automation
The portfolio
Blue works top down from what the business wants. Teal works bottom up from what you hold and run. Each stands on its own.
“Where do we invest in AI, in what order, and what comes back?”
vs a reportA live business case, updated as estimates firm up, not a deck that ages the week it lands.
“How do we get staff using AI without losing control of it?”
vs licencesAdoption you can report on, not a chat window handed out and hoped for.
“Is our data good enough to build on, and what will it expose?”
vs guessing“The data is fine” becomes a measurement, answered before the AI spend is committed.
Lineage · customer_email3 hops · PII
“What are we spending on AI, where is it going, and is it worth it?”
vs the invoiceCost governed as it accrues, not explained after the provider bill arrives.
Tokenz · token spend by departmentUSD, this month
How an assessment runs
Stakeholder interviews, department assessments and a five-pillar maturity baseline, captured straight into the platform.
Every opportunity scored on the same five numbers, reviewed by architects and priced with real vendor quotes.
Board-ready business cases, a sequenced roadmap, and proofs of concept already standing at the approval gate.
Why Execlenz
Scored identically in every department, so candidates are compared on evidence instead of argued about on instinct.
| Opportunity | Fit | Confidence | Complexity | Priority | Annual saving |
|---|---|---|---|---|---|
| Invoice matchingFinance | 86 | High | Low | Quick win | $212K |
| Claims triageOperations | 74 | Medium | Medium | Must-do | $340K |
| Access requestsIT | 61 | High | Low | Low-hanging | $64K |
Example register - illustrative figures
Weeks, not months
Insight shows up in the first weeks, while the assessment is still running.
Three to six months before you see anything
Every engagement, down to a single use case, ends with a proof of concept standing, not a proposal for the phase that would build one.
Ends at a recommendation
Three scenarios with the assumptions visible, so a figure can be interrogated rather than trusted.
AI is one of nine accelerators. Each requirement goes to the one that fits: integration, BPM, RPA or data.
A live model that keeps updating after the engagement closes, with governance and approval gates built in.
Nothing remains when the engagement ends
Where to start
A single business function takes a few weeks and produces a costed, scored business case you can take to the board, with a proof of concept standing at the end of it.