Use Case // Buy-Side Diligence
AI Quality of Earnings (QoE), Run Deterministically.
The management presentation is built to defend adjusted EBITDA. The raw ledger is not. The RAVEN Protocol™ triangulates the two and preserves the contradiction — so aggressive add-backs and net-working-capital anomalies cannot be smoothed away before they reach your IC.
RAVEN Protocol · U.S. Prov. Patent No. 63/994,876
// The Add-Back Problem
Adjusted EBITDA is a negotiation, not a fact.
By the time a deal reaches diligence, the sell side has already done the work of making the numbers persuasive. The quality-of-earnings question is not “what does management say earnings are” — it is “what does the ledger support when you strip out everything that flatters the trailing twelve months.” That gap is where purchase price is won or lost. Here is the problem with the conventional read: a probabilistic model handed the management presentation will tend to reconcile the contradictions away, because it is optimizing for a clean, confident summary. We do the opposite.
// Cross-Document Triangulation
We preserve the contradiction. We do not reconcile it away.
This is not a QoE tool. It is judgment infrastructure that executes deterministic quality-of-earnings verification. The distinction matters at the architecture level: a summarizer is rewarded for collapsing conflicting inputs into one tidy answer. The RAVEN Protocol is built to hold the conflict open.
When the management add-back schedule says one thing and the trial balance says another, that divergence is the finding. RAVEN surfaces it, ties it to both source documents, and hands it to the deal team to adjudicate. LLMs optimize for persuasion. askOdin compiles for physics.
The architectural mechanics of RAVEN's triangulation engine are protected under U.S. Provisional Patent No. 63/994,876 and are not publicly disclosed.
$ raven reconcile --workstream=ebitda-addbacks
src: mgmt_presentation.pdf · trial_balance.csv
mgmt adjusted EBITDA . . . . $14.2M
add-back: “non-recurring” . $2.1M
→ ledger: recurs Q1–Q4 (4/4 periods)
→ CONTRADICTION — not reconciled
NWC peg vs TTM trough . . . −$0.9M leak
finding tied to: GL §4100, BS §working-cap
// QoE Workstreams
The workstreams your QoE provider already runs — as deterministic checks.
Same workstreams, executed as cross-document checks with provenance on every line. Not a probabilistic read of the management presentation — a citable, reconcilable test against the raw ledger.
CLAIM 01
EBITDA Add-Back Validation
Every management add-back — “one-time” legal, “non-recurring” consulting, owner compensation normalization — triangulated against the raw trial balance and the general ledger. Recurring costs dressed as exceptional are surfaced line-by-line, not netted into adjusted EBITDA. The bridge is only as defensible as the ledger behind it.
CLAIM 02
Net Working Capital (NWC) Peg Integrity
The net-working-capital peg validated against the trailing-twelve-month build and the balance sheet. A peg set off a normalized average rather than the true seasonal trough is a post-close purchase-price leak; the divergence surfaces before the SPA mechanics lock.
CLAIM 03
Proof of Cash · Revenue Reconciliation
Reported revenue and earnings reconciled against bank-statement cash collection. When the income statement, the model, and the deposits diverge, the contradiction is preserved as a citable finding — not smoothed into a single confident number.
CLAIM 04
Customer Concentration & Revenue Quality
Concentration, churn, and revenue-durability claims cross-checked across the management presentation, the model, and the contract schedules. Each contradiction is tied to both source documents, with provenance intact.
CLAIM 05
Non-Recurring & Pull-Forward Items
Pull-forward bookings, channel-stuffing signatures, and accounting reclassifications that flatter the trailing twelve months surfaced as discrete findings — so the run-rate the model leans on is the run-rate the ledger supports.
We do not compete; we consume. Keep your QoE provider, keep the data room, keep the deal team — add the deterministic audit underneath. RAVEN surfaces the contradictions the workflow was never built to hold open.
The architectural mechanics of RAVEN's triangulation engine are protected under U.S. Provisional Patent No. 63/994,876 and are not publicly disclosed.
// The Standard
One deterministic check, reproducible across every deal.
The same engine, the same forensic dimensions, the same standard — whether the target is a $30M lower-middle-market platform or a $1.5B sponsor-to-sponsor buyout. Run it twice on the same data room and it returns the same findings, byte for byte. That reproducibility is what makes the output defensible to the IC, to the lenders, and to the next buyer in the chain.
// OBJECTION HANDLING
QoE & M&A Diligence FAQ
Can askOdin produce a quality-of-earnings analysis, or does it just summarize the CIM?
It deterministically reconciles reported earnings against cash collection and disclosed costs, flagging non-recurring and add-back items as citable findings. It surfaces the quality-of-earnings signals; your deal team and QoE provider adjudicate.
Does it validate EBITDA add-backs and working-capital normalization?
Yes. The RAVEN Protocol triangulates claimed add-backs and the net-working-capital peg across the model, the financials, and the disclosures, flagging any line that does not reconcile to source — deterministic, not estimated.
Can it flag customer concentration and revenue quality across the data room?
Yes. Concentration and revenue-sustainability contradictions surface as cross-document findings tied to both source documents — not a probabilistic summary.
Does this work for a carve-out where financials are entangled with the parent?
The RAVEN Protocol is built for heterogeneous data rooms; it surfaces where carve-out financials fail to reconcile with parent-level disclosures, with provenance preserved. Complex carve-outs remain a human-adjudicated call on a defensible evidence base.
How is this different from a virtual data room’s AI or a RAG tool over the room?
Those retrieve and summarize within a document. askOdin triangulates across documents and preserves contradictions instead of reconciling them away. We do not compete; we consume — keep the room, add the audit.
Is our confidential deal-room data used to train models?
No. Stateless orchestration, ephemeral processing, and strict data sovereignty; deal data is processed in isolated, short-lived compute and never enters any training corpus.
Audit the earnings before you wire the equity.
Venture capital is the last unaudited asset class. askOdin provides the infrastructure to close the gap — and the same deterministic discipline tests every quality-of-earnings claim in your data room.