DataVisor Vera and Vera Code vs osapiens Agent Factory

Quick answer

DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting) (DataVisor (DataVisor, Inc.)) and osapiens Agent Factory (supplier and supply-chain compliance agents) (osapiens) are both listed in the Risk category of Agent Index.

They share no framework tags in our dataset.

This is not a ranking.

DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting) (DataVisor (DataVisor, Inc.)) and osapiens Agent Factory (supplier and supply-chain compliance agents) (osapiens) are both listed in the Risk category of Agent Index. They share no framework tags in our dataset.

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Field DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting)osapiens Agent Factory (supplier and supply-chain compliance agents)
Vendor DataVisor (DataVisor, Inc.)osapiens
HQ United States · North AmericaGermany · Europe
Primary category RiskRisk
Also listed in Risk, ComplianceRisk, Compliance
Summary AI teammate for fraud and AML teams on the DataVisor platform. From a plain-language request, Vera orchestrates agents that author detection rules, features and lists, tune strategies against production telemetry, summarise alerts and draft FinCEN-aligned SAR narratives; changes are proposal-only and a human approves before anything reaches production. Vera Code turns requirements into tested, documented configurations.Agent layer across the osapiens HUB that runs supplier onboarding, record validation, questionnaire pre-fill, supplier case management and risk-trend analysis for supply-chain due diligence (LkSG, CSDDD, EUDR and more), within customer-set guardrails.
Frameworks (vendor-stated) ——
Frameworks (vendor-claimed) —LkSG, CSDDD, EUDR, EU Forced Labour Regulation, CSRD
Capabilities / tasks fraud detection, aml, alert triage, sar narratives, case investigationvendor risk, risk assessment, questionnaire automation, workflow automation
Pricing (as published) Not publishedNot published
Pricing model quotequote
Primary source https://www.datavisor.com/agentic-ai/verahttps://www.osapiens.com/en/platform/agent-factory
Last checked 2026-10-212026-10-18
Official site https://www.datavisor.com/agentic-ai/verahttps://www.osapiens.com/en/platform/agent-factory

FAQ (from this dataset)

What is the difference between DataVisor Vera and Vera Code and osapiens Agent Factory?

Both are listed under Risk. They share no task tags in this dataset. DataVisor Vera and Vera Code-only tasks: fraud-detection, aml, alert-triage, sar-narratives, case-investigation. osapiens Agent Factory-only tasks: vendor-risk, risk-assessment, questionnaire-automation, workflow-automation. Differences are from stored category and task tags, not a ranking.

Which one publishes pricing?

DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting): Not published osapiens Agent Factory (supplier and supply-chain compliance agents): Not published

Where are DataVisor Vera and Vera Code and osapiens Agent Factory headquartered?

DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting) publishes HQ in United States. osapiens Agent Factory (supplier and supply-chain compliance agents) publishes HQ in Germany.

Side-by-side data is generated from the open dataset. “Vendor-claimed” frameworks are as marketed by each vendor and not verified by Agent Index; framework tags indicate relevance, not certification. Request current quotes from each vendor before buying. This page does not rank or score vendors. Sponsored comparisons, if any, will be labelled.

Also in this use case

Other verified listings that share a task tag or use-case group with DataVisor Vera and Vera Code (agentic AI for fraud and AML strategy, tuning, alert summaries and SAR drafting) or osapiens Agent Factory (supplier and supply-chain compliance agents). Open a pair page or the use-case table — this is not a ranking.

Use-case comparisons

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