How it works · the method
Most data work answers what happened. We close the loop.
ResolvHQ connects what happened to why, what to do, and whether it worked — with cited evidence, a confidence level, and its blind spots named. Every finding says what would prove it wrong. The X-Ray runs the front of the loop today; where “today” ends is marked on this page, not blurred.
Detect → Explain → Assign → Resolve → Prove
See what the Operational X-Ray includes01 The loop
Five moves. The last one is the part nobody else does.
Coverage feeds Detect. Proof feeds the Value Ledger. The loop is the destination; the X-Ray runs the front of it today.
01
Detect
Source-backed, deterministic checks read across the data you provide and surface what is leaking, breaking, or drifting. Coverage feeds Detect: the system tracks what it has not seen.
02
Explain
Every finding arrives with its evidence attached — the exact export, rows, and time range. A confidence level and what would disprove it travel with it.
03
Assign In-build
Routing a finding to an owner and tracking it through the Issue Lifecycle to closed is a product surface we are building. In the X-Ray today, ownership is assembled by the operator.
04
Resolve In-build
The assign-to-resolve workflow the client runs, and continuous re-checking, are in development. The X-Ray delivers the finding; the always-on loop is where it grows.
05
Prove
Detected exposure, confirmed value, and recovered cash stay separate — never collapsed into one hopeful number. The Value Ledger records confirmed dollars only.
The Operational X-Ray runs Detect and Explain end-to-end on your data today. The client-run assign-to-resolve workflow and the Value Ledger compounding month over month In-build are where the engagement grows.
02 The proof standard
This is the part that makes the rest trustworthy.
A finding you cannot trace is just an opinion with a number attached. The standard is what keeps ours honest — the same discipline every finding carries.
- Cited evidence
- Click the number, see the source. Every figure traces to the exact export, rows, and time range that produced it.
- Coverage honesty
- The system states what it cannot see. Blind spots are named, not buried. The Coverage Map shows what is covered and what is not.
- A falsifier on every finding
- Each finding carries what would disprove it. If that condition appears, the finding is wrong — and the standard said so first.
- Visible corrections
- When a finding is wrong, the correction is a permanent record, not a quiet edit.
03 A finding, end to end
What one finding looks like when it arrives.
An illustrative pattern the X-Ray looks for — not a result delivered for a client. Labeled, so it can never be read as proof it is not.
Completed work that shipped but was never invoiced — sitting in the gap between the project system and billing.
Cited evidence
- Project export
- milestones marked delivered with no matching invoice id
- Billing export
- no line item within 60 days of delivery
What would disprove it: a matching invoice outside the 60-day window. Needs both a delivery signal and a billing export — work tracked only in email stays a named blind spot.
04 Is this “AI”?
Not “the AI says so.” Show the receipt.
The detection is deterministic and source-backed — rules reading your data, not a model guessing. Where AI is used, it explains a finding in plain language. It never decides one.
That division is why a number can always be traced back to the row that produced it, and why the system can say “I don’t know” when the evidence is not there. The receipt is the cited evidence: the source data, time range, and reasoning behind the answer. An answer you cannot check is not an answer we ship.
05 Who runs it
Operator-led, on dedicated infrastructure.
Right now, every engagement is run by the person who built this — direct access, not a support queue. Your data lands on dedicated, isolated infrastructure, and operator access is scoped and ticketed.
It will not stay this way as the client list grows — which is exactly the advantage of coming in now. The Trust page covers exactly how data is handled.
06 Questions
The ones worth answering first.
- How is this different from BI or a dashboard?
- A dashboard can show what happened. ResolvHQ answers why, what to do, and whether it worked — with cited evidence, a suggested owner, and dollar context. When the answer lives in the gaps between systems, a dashboard is expensive noise.
- Is this “AI”?
- The detection is deterministic and source-backed — rules reading your data, not a model guessing. Where AI is used, it explains a finding in plain language; it never decides one. Rules decide, AI explains, and every answer carries the receipt.
- What data do you need to start?
- Exports — CSV, spreadsheet, or a database dump — from the systems where the money moves. No API access, no credentials. The Operational X-Ray page lists exactly what to send.
- Can I see a demo?
- No. Sample data can only show what the system looks like — never a finding that matters to you. The Operational X-Ray runs the method on your actual exports; that is the demonstration.
One next step
See the method run on your own data.
The proof standard is easy to describe and hard to fake. The Operational X-Ray shows it working on your exports — findings, evidence, coverage, and all.
See what the Operational X-Ray includesFixed scope. Fixed price. Five to ten days.