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Axle (Axle Automation / Axle Compliance) — Labeled transaction-monitoring outcomes: per-alert pairs of scenario-fired alert against investigator disposition (true positive, false positive, data-quality issue), scenario- and segment-level precision and SAR-conversion series, below-the-line recall test sets built by sampling activity just under thresholds and dispositioning it, SAR provenance tags (monitoring alert vs referral vs subpoena vs negative news), and downstream yield labels (law-enforcement inquiries, keep-open requests, continuing-activity reviews).. Early-stage — 13-person Seed-fun…
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Labeled transaction-monitoring outcomes: per-alert pairs of scenario-fired alert against investigator disposition (true positive, false positive, data-quality issue), scenario- and segment-level precision and SAR-conversion series, below-the-line recall test sets built by sampling activity just under thresholds and dispositioning it, SAR provenance tags (monitoring alert vs referral vs subpoena vs negative news), and downstream yield labels (law-enforcement inquiries, keep-open requests, continuing-activity reviews).
From 2 yearsFormat TabularCoverage Information Technology · Financials
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Axle (Axle Automation / Axle Compliance) — Labeled transaction-monitoring outcomes: per-alert pairs of scenario-fired alert against investigator disposition (true positive, false positive, data-quality issue), scenario- and segment-level precision and SAR-conversion series, below-the-line recall test sets built by sampling activity just under thresholds and dispositioning it, SAR provenance tags (monitoring alert vs referral vs subpoena vs negative news), and downstream yield labels (law-enforcement inquiries, keep-open requests, continuing-activity reviews).. Early-stage — 13-person Seed-fun…
Axleruns offers (Alternative, Sentiment, Fundamental) — Est. hundreds of thousands to low millions of dispositioned alert records across the client base (inferred from per-institution monthly alert volumes at community to mid-tier banks times the client count), plus tens of thousands of below-the-line sub-threshold labelled samples.
Training and benchmarking transaction-monitoring and AML alert-triage models; scenario tuning with genuine recall estimates instead of threshold-driven precision games; building labelled false-negative sets for SR 11-7 model validation and examiner defence; evaluating LLM alert-disposition and SAR-drafting assistants against real investigator decisions; calibrating alert-volume reduction claims across vendors.
The data is with 2 years of history.
Coverage spans US; Application Software, Financial Services; alternative, sentiment, fundamental; equities.
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