We gave 3Dogs Nexus the real Enron executive email archive and one instruction: read it and tell us if there's a case. No hints. Then we checked its work against history.
A consumer chatbot can't ingest a set this large — its context window holds a few hundred pages, not half a million emails. So we did what a real e-discovery team does: collect everything, scope to the people who matter, remove the duplicates, then read what's left in full.
Source: the public CMU Enron corpus (the same dataset used in academic research for two decades). Attachments were not part of the public set.
We deliberately withheld any hint of what happened at Enron. The engine had to discover the story itself. Here is what it surfaced from the emails alone — scored against the public historical record.
| What the record actually held | Did we tell it? | What 3Dogs surfaced from the emails |
|---|---|---|
| The off-books entities — LJM1, LJM2, Raptor I–IV, Chewco | No. Never named. | FOUND Named LJM1, LJM2, Raptor I–IV and Chewco as off-balance-sheet vehicles, and noticed the references clustered around quarter-end reporting. |
| Senior executives at the center | Only that these were their mailboxes. | FOUND Placed Skilling, Whalley, Delainey and Buy in the pattern — a "convergent, multi-actor" signal across people with different roles. |
| Internal warnings that were overridden | No. | FOUND Surfaced the suppressed dissent of Vincent Kaminski (risk-model integrity) and Sherron Watkins (accounting ethics) — objections "escalated and overridden by identifiable senior executives". |
| The mechanism: hiding debt, inflating earnings | No. | FOUND Concluded the vehicles were used to hide debt and inflate profits, and classified that finding as VERIFIED against the record. |
| Is it strong enough to act on? | That was the question. | DECISIVE A 9-analyst panel returned "Launch the formal investigation now" at 87% confidence — reached via explicit Bayesian reasoning to the "probable cause" threshold. |
The real Enron Task Force, the SEC, forensic accountants and a court-appointed examiner established these same threads over roughly four and a half years (bankruptcy Dec 2001 → Lay & Skilling convictions May 2006).
The single biggest fear with AI in legal work is a confident machine inventing what isn't there. 3Dogs did the opposite. Nine models debated the evidence adversarially, and the majority case was published next to its strongest rebuttal — the dissent preserved, not smoothed away.
That dissent is not a weakness in the output — it is the output. It's exactly the objection opposing counsel would raise, surfaced up front. And it was correct: Fastow's mailbox genuinely wasn't in the set we provided, and the panel caught the gap without being told. Its prescription reflected that honesty — it didn't just say "investigate," it said how: institute an immediate litigation hold on all Enron and Arthur Andersen records, bring in forensic accounting within 30 days to quantify materiality, run a parallel "null-hypothesis" workstream to guard against confirmation bias, and subpoena the board and audit-committee minutes.
3Dogs didn't reach a verdict a court would — it produced an investigative decision brief. But it did it on the same underlying email record that took human institutions years, at a rounding error of the cost. And we didn't have to guess at that cost — the analysis priced it itself.
That $2–5M isn't ours — it's the engine's own estimate, in the report: a full forensic review of these 45,320 emails at $50–$100 per email, against a value-at-stake it put at $4–25 million. Even at bargain managed-review rates ($1–3/email) it's six figures. 3Dogs' $69.20 is the actual metered cost of 5,371 model calls across 11 AI models — not an estimate. An ROI, in other words, that is off the charts.
These aren't competitors — they're the stack. E-discovery platforms and review teams do the collection and culling; 3Dogs sits on top as the assessment and second-opinion layer.
This isn't a self-serve feature. Reading a record this size is a bespoke engagement, scoped to your matter — a litigation record, an M&A data room, a regulatory investigation, a contract portfolio. Same engine, whatever the mountain. And because it's legal-grade, your data is handled that way:
Your matter data is never comingled with anyone else's — a dedicated, isolated data store per engagement.
For the most sensitive matters, the entire stack runs inside your own environment, behind your firewall, with your encryption keys — data never leaves your boundary.
Your privileged material is never used to train models. Zero-retention handling and full control over retention and deletion.
Hand us a real record you're weighing. We'll read the whole thing and show you the call — before you commit to anything.
Book a test run →Or reach us directly — [email protected] · (702) 845-2886 · Alan Finney, 3Dogs Nexus
Every number on this page comes from this run. The full client-facing decision brief 3Dogs produced:
Methodology & honest limits. The engine was given six of the ~150 mailboxes and no outside summary; it reconstructed the story from that scope. Two central figures — CFO Andrew Fastow and Chief Accounting Officer Richard Causey — were not in the mailboxes provided (Causey's is absent from the public corpus), so intent is established only circumstantially; the panel flagged this itself. This is an investigative decision brief — a fast, defensible read of the evidence to inform a go/no-go — not a legal finding or a substitute for adjudication. The "answer key" it was scored against is the public historical record of the Enron cases. Run: 45,320 deduplicated emails · 981 documents · 5,371 model calls · 11 AI models · 2h 28m · $69.20 metered.