In development
Economic intelligence
for corporate tax.
The inversio Engine reads annual securities filings and turns the tax positions inside them into analysis a professional can stake a decision on. Not a summary. Not a search index. Every figure it publishes resolves to the filing text that supports it, or it is not published.
The product
inversio Engine
Corporate tax disclosure is written to satisfy a filing requirement, not to answer a question. The material facts are real and public — they are simply buried in narrative, spread across years, and phrased so that two filings describing the same position rarely describe it the same way. It is built to read that disclosure at the standard a tax professional would apply to it, and to show its work every time.
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Evidence-anchored extraction
Reads annual filings — Form 10-K as the core corpus, with controlled and explicitly guarded Form 20-F support — and captures each tax position together with the exact source text behind it.
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Governed analysis
Positions are evaluated against approved formulas and expert-authored tax mechanics held in a versioned registry. Analysis is a governed artifact, not a heuristic that drifts between releases.
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Auditable provenance
Every published value resolves through a provenance ledger to a source anchor or a recorded derivation path. Findings carry an explicit evidence basis, so a reviewer can see how strong the support actually is.
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Deterministic by construction
No language model runs at inference time. The same filing produces the same answer on every run — a property you can test, and one that matters when the output has to be defended.
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Fail-closed
Where the evidence is missing or unstable, it returns nothing and says so. It does not fill the gap with an estimate and present it in the same typeface as a fact.
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Built for review
Issuer library, analytics, peer comparison, and generated reports — each surface built so a finding can be traced from headline to underlying filing language without leaving the product.
Audience
Know which potential tax strategies a company may be pursuing — and what its filings say about each one.
The inversio Engine reads years of annual filings and surfaces the potential tax strategies and sub-strategies a company may be pursuing, each one attached to the disclosure language that supports it. The judgment stays yours — but you start from evidence, not a guess.
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Corporate tax departments
Benchmark your positions against comparable filers: which potential strategies peers are pursuing, how they disclosed them, and where your own treatment sits against the field — with the source text behind every comparison.
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Transaction diligence
Map a target’s tax profile before the bid: which potential strategies it depends on, where exposure concentrates, and what the filings actually say — across its full filing history, without reading each one by hand.
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Advisers and analysts
Answer “what are others doing here?” from evidence rather than recollection. Firms covering more issuers than any team can review manually, where every claim has to survive a partner’s read or a client’s challenge.
Across all three, the starting point is the same: filings most people do not have time to read line by line, turned into potential strategies with their evidence attached. What you conclude — and the professional judgment behind it — stays yours.
Approach
Three commitments we will not trade away for coverage.
A tax platform can always look more capable by loosening what it requires before it will speak. We have taken the opposite position, deliberately, and we hold it under engineering gates rather than good intentions.
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I
Determinism over inference
A number a professional relies on has to be reproducible. Ours is computed, not generated, and the same inputs return the same result indefinitely.
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II
Provenance over assertion
Confidence is not a substitute for evidence. Each claim carries the route back to its source, and the strength of that route is stated plainly rather than smoothed over.
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III
Silence over a plausible guess
The costly failure in this field is not an absent answer — it is a confident wrong one. When the filing does not support a finding, we would rather show nothing.
Founders
Who is building this.
Tax practitioners and scholars who have been working on these questions together since 2019. The domain expertise predates the company.
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Julianne Jones
Co-Founder & CEO
Director of the University of Akron's School of Accountancy and Professor of Practice in accounting. Previously a tax manager in practice; she is a CPA with a JD and a Master of Taxation, and conducts research on federal and state taxation.
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Doron Narotzki
Co-Founder & CTO
Full Professor of Tax and Business Law at the University of Akron's School of Accountancy, where he directs the Master of Taxation program. He has published more than seventy articles on corporate and international taxation and practiced international tax at PwC. He originated the approach behind the inversio Engine.
Contact
inversio Engine is not yet publicly available.
We are building toward a limited early-access release. If you work in corporate tax, transaction diligence, or financial data — or you would like to be told when access opens — write to us directly. Every message is read by a founder.