Zeer
Napier AINapier AI buying intent
10 tracked signals — top 7 topics below — Marketing and Sales are carrying most of it.
Attention by team
taxonomy_intent_rollup × social_profile.roleEvery tracked signal from a Napier AI employee, placed by the team they sit in and the theme they engaged with. Darker means more concentrated attention.
Topics being researched
30-day windowAll tracked topics, ranked by signal volume. Confidence is the classifier's certainty that the signal belongs to this topic.
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Need intent for a specific topic or industry?
We track the full taxonomy across every account in the graph — including themes not shown on this page.
Who to contact at Napier AI
verified title on filePeople at Napier AI whose own activity produced these signals. Names are withheld pending a consent decision; titles, seniority and topic are real and free to browse.
Top accounts researching Napier AI
names withheld on the public pageCompanies whose people mention Napier AI in their own activity. Account names are withheld here; not yet classified as implementation partner vs. genuine prospective buyer.
No buyer signal yet for this account
Nobody in the graph is currently discussing this company by name in a way we can attribute to a specific employer.
Buyer profile
company size · seniorityHow big those accounts are, and who inside them is senior enough to matter. Competitor products still not yet computed for this account.
What's been said
public posts mentioning Napier AIReal public activity that surfaced Napier AI in a tracked topic. Not a sentiment score — just what people actually wrote.
Great session on Wednesday at the FinCrime Leaders Summit East Coast in Charlotte. It was an honor to join Thomas J. Nadratowski (Citi), Sean Meisler (USAA), and Ervin Brabham (AWS) on stage to discuss the operational reality of AI adoption and model governance. The conversation moved beyond the theoretical and straight into how we are fundamentally redesigning financial crime operating models in light of the recent FinCEN and SR 26-2 guidance. Here are my three key takeaways from our discussion: Target the "Noise" First: Find the lowest risk and most repetitive manual tasks in the investigative workflow. In my opinion, the highest impact right now is getting rid of the noise by automating the L1 alert review process.. By using AI agents to adjudicate low-risk false positives in milliseconds, firms are seeing 60-90% increases in operational efficiency, allowing investigators to focus on actual risk. Layer, Don’t rip and replace: You don't need a multi-year "rip and replace" program to see results. By layering AI into legacy infrastructure, financial institutions can move from implementation to production in weeks, not months—often with zero IT resources required. The New Governance Standard: With the shift from SR 11-7 to SR 26-2, regulators are moving away from check-the-box compliance toward risk-based judgment. Vendors must provide full decision architecture—traceable data lineage and sensitivity analysis—that proves to internal auditors and regulators exactly how accuracy and coverage are achieved. The industry is moving from simply making existing processes "faster" to making them fundamentally "different." Excited to keep pushing the needle on what's possible in the AI compliance space! Thanks to Transform Finance #TransformFinance for a well executed event. If you missed this panel and want to learn more about AI and SR 26-2, Castellum.AI is hosting a fireside chat on Tuesday talking about SR 26-2 and Model Risk Management for Agentic AML Systems - Register here https://lnkd.in/ehfTprJe