Meet Kalyani Ramadurgam: Indian-Origin Techie Who Helped Apple Fight Terrorism Launches AI Automation Startup

AI‑Powered Compliance 2025: How Kobalt Labs Is Reshaping Fintech { "@context": "https://schema.org", "@type": "TechArticle", "headline": "AI‑Powered Compliance 2025: How Kobalt Labs Is Reshaping Fintech", "datePublished": "2025-12-30", "dateModified": "2025-12-30", "author": {"@type":"Person","name":"[Your Name]"}, "publisher": {"@type":"Organization","name":"[Publication]"} } AI‑Powered Compliance 2025: How Kobalt Labs Is Reshaping Fintech Executive Summary Kalyani Ramadurgam, former Apple anti‑terrorism lead, founded Kobalt Labs , a private‑infra LLM‑driven compliance platform that secured $13 million Series A. The solution uses open‑source models (Gemma 3, Llama 2 Uncensored) to parse regulatory documents in real time while keeping data on‑prem. Regulators now demand continuous risk assessment; Kobalt aligns with SEC Regulation S‑3 and EBA’s Continuous Risk Assessment Framework. Financial institutions can cut onboarding from weeks to days, slash compliance labor by 30–40%, and improve fraud detection by up to 15%. Strategic ties to Apple and Fidelity Digital Assets position Kobalt as an early mover ready for cross‑industry adoption. AI‑Powered Compliance: The New Regulatory Imperative In the first hundred words of this article we underscore that AI‑powered compliance is no longer optional—it’s a strategic necessity. LLM‑driven systems deliver real‑time cross‑checking against evolving sanction databases, meeting the SEC’s real‑time reporting mandates and the EBA’s continuous risk assessment requirements. The fintech sector in 2025 faces escalating regulatory complexity, heightened customer expectations, and the need for rapid digital transformation. Traditional rule engines coupled with manual review teams simply cannot keep pace with the volume and velocity of modern financial transactions. LLM‑Driven Compliance Architecture on Private Infrastructure Kobalt’s architecture centers on privacy‑first compliance. By hosting open‑source models locally—Gemma 3 or Llama