Todd Jacobs: Define AI use cases before metrics for KPIs and OKRs

The deal is done! 🙌 Panther acquired Datable.io, a Security Data Pipeline innovator. AI is the solution… But DATA is the problem. With this move, we’re doubling down on our core data strengths and accelerating delivery of a complete AI SOC platform. For our customers, this means increased investment in three key areas: 1️⃣ AI-powered pipelines — smarter ingestion, less manual toil. 2️⃣ Open security data lakes — more choice, control, and cost efficiency. 3️⃣ Enhanced usability — expanding the tent so more teams can contribute. Our mission is to make security teams smarter and faster than attackers.  That starts with clean data.  Julian Giuca and team — WELCOME TO PANTHER. Let’s get to work. 👉 https://lnkd.in/gedxU4BR

🔥 Big news from Panther: we’ve acquired Datable.io, a leading innovator in security telemetry pipelines. This acquisition strengthens the core of our platform and gives security teams the ability to onboard new log sources in hours instead of weeks. It also enables cleaner, more consistent data streams and provides rock-solid reliability at scale. By bringing Datable’s pipeline orchestration into Panther, we’re accelerating the shift toward AI-driven detection and response. This will help teams reduce noise, lower costs, and build a high-quality data foundation for modern security operations. 👉 Read more in Will’s post below.

Thrilled to share some big news: Panther has acquired Datable.io! This is a major step toward building a complete AI SOC platform, one that starts with clean, well-routed data. Datable’s approach to pipeline orchestration brings serious engineering muscle to a problem every security team struggles with. I’m especially excited to work alongside Julian and the Datable team as we push what’s possible in AI-driven security.  👉 https://lnkd.in/g4wTidVd

Exciting day at Panther! This acquisition means (even) faster log onboarding, (even) more reliable data streams, and pipelines built to keep up with how fast security teams need to move. Big step forward toward truly effective AI-driven security. https://lnkd.in/gUTf2HVm

Meta transforms data warehouse access with multi-agent AI system featuring specialized data-user and data-owner agents. The solution addresses growing complexity in data access patterns through context-aware permissions, granular query control, and rule-based risk management while maintaining security guardrails. https://lnkd.in/ejQrU7_N

Admit it, adopting GenAI is scarier than that movie Se7en with Brad Pitt. You never want to play “What’s in that box?” with GenAI. If Se7en taught us anything, it’s that ignoring the signs never ends well. Yet in the rush to boost productivity and innovation, security teams are committing predictable, costly, and frankly avoidable sins that are exposing sensitive data. So we’ve come up with a free guide to help you stop committing data security sins. What You’ll Learn: ✔️ The 7 most common GenAI “sins” undermining your enterprise data security ✔️ How Shadow GenAI, bad classification, and over-permissioned data quietly multiply risk ✔️ Why draconian governance policies cause more chaos than control ✔️ A simple framework for replacing risk with visibility, balance, and smarter guardrails ✔️ Practical steps to transform your GenAI adoption into something secure, scalable, and sustainable Remember: The worst mistake is pretending you’re not guilty of any sins. Get the guide below before your data governance becomes the sequel no one asked for: Se8en! #GenAI #DataSecurity #DataSecurityGovernance #AISecurity

Every customer I work with is concerned about what AI is doing to and with their sensitive data, and most are shocked at what Concentric AI is able to show them is happing in the "box". Here's a handy guide of some of the to help you navigate this ever-changing landscape. Ask me for a demo to learn how we can help you protect your data from #AI misuse, and much more. #DSPM #DataSecurity #DataGovernance #CISO

𝗬𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝘁𝗲𝗹𝗹𝘀 𝘀𝘁𝗼𝗿𝗶𝗲𝘀. 𝗧𝗿𝘂𝘀𝘁 𝗮𝘀 𝗮 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗮𝗰𝘁𝗶𝗼𝗻. Common data tools tell you what happened.  Triple A 𝗽𝗿𝗼𝘃𝗲𝘀 what happens next. When decisions run at scale, trust isn't a feeling - it's a system you can measure. 𝗧𝗿𝗶𝗽𝗹𝗲𝗔 operates in three layers:  → Detect: Continuous monitoring surfaces anomalies before they cascade  → Decide: Policy engines verify thresholds and confidence in real-time → Prove: Every action writes to an auditable ledger, replay on demand We built this for high-stakes environments where failure isn't an option - but preparing for it is.  Latency spikes, model drift, bad inputs: we test against them by design. 📌 𝗧𝗶𝗺𝗲-𝘁𝗼-𝗧𝗿𝘂𝘀𝘁 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲. 𝗥𝗲𝗰𝗼𝘃𝗲𝗿𝘆 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗿𝗲𝗳𝗹𝗲𝘅. If you're operating where decisions can't wait and mistakes compound fast, let's talk. Business is open. 🌍 https://datyq.com #YourDataTellsStories #DecisionOS #AIOps #Reliability #OperationalIntelligence

Last week I wrote that AI will finally succeed in Data Management because it’s deterministic — measurable week by week, month by month. The reason the time for this change is now, because you don't want your #agents dead on arrival because of poorly integrated, poorly reconciled - bad data. So what does the measurement look like in practice? For the first time, data management can be run like engineering - with velocity metrics, burn-down charts, and clear outcomes. Agents don’t just automate; they report their progress. Clearly this has been the biggest challenge in existing efforts in proving direct relatable value as opposed to notional value. When a #DiscoveryAgent finds new datasets, it tracks coverage growth. When a #ClassificationAgent tags attributes, it logs accuracy and drift. When a #PolicyAgent writes or enforces rules, it measures compliance improvement over time. Every one of these becomes a quantifiable signal of progress - something we never had in traditional governance programs. Enterprises can now measure advancement in data readiness the same way they track software delivery or cloud cost efficiency. That’s a seismic shift - from activity-based reporting (“we documented 500 tables”) to outcome-based accountability (“95% of data used in models is policy-compliant and quality-verified”). Agentic Data Management isn’t just automation but autonomous! #AgenticAI #DataManagement #DataGovernance #Acceldata #Autonomous25 Acceldata Mahesh Kumar Mike McQuaid 🤝 Ramon Chen Ashwin Rajeeva Hitesh Gupta Sam Wolff Anna Meyer Ashok Gunasekaran Raghu Mitra Kandikonda Gaurav Nagar Joseph Murphy Michael Setticasi Michael Garrett Duncan Paul Justyn Goodenough Connor McCaffrey Amy Kyleen Lute Lorena Andrews Ajay Dawar

We Just Hit Enterprise Scale. Here's What Teams Are Getting Next. Three months ago, DefendML was an idea: build the fastest, most accurate AI security platform powered by Anthropic's ASL-3 framework. Today? Phase 3 is live. For the teams already protecting their AI with DefendML, this changes everything. What we shipped: Phase 1 — Foundation (✅ Complete) The basics had to be bulletproof. We built secure onboarding, GitHub-based CI/CD, and aligned every policy with Anthropic's ASL-3 AI Safety Framework. No cutting corners on security when you're building security. Phase 2 — Feature Enablement (✅ Complete) Feature-flag control went live. Incident-center visibility launched. New guardrail logic deployed across UI + API layers. Now customers can see threats in real-time and toggle protections on-demand. Phase 3 — Enterprise Readiness (🚀 Now Live) This is where it gets serious: • Multi-Tenant Dashboard — Multiple teams, one platform, complete isolation • Automated Guardrails — Set-it-and-forget-it protection that adapts to threats • ASL-3 Compliance Reporting — Prove to auditors you're using the highest safety standards • Enterprise Scale Monitoring — Handle millions of requests without breaking a sweat Why this matters: Most AI security tools are built for experimentation. We built DefendML for production at scale. The difference: ❌ Other tools: "Install our SDK and hope it works" ✅ DefendML: Multi-tenant, compliant, monitored, and battle-tested ❌ Other tools: Manual threat detection ✅ DefendML: Automated guardrails that evolve with attack patterns ❌ Other tools: "Trust us, it's secure" ✅ DefendML: ASL-3 compliance reports you can show regulators What's next: Phase 3 means DefendML is ready for the largest enterprises. If you've been waiting for "fully baked," this is it. Transparent. Safe. Trustworthy. Built into every interaction. That's not marketing—it's architecture. ✅ See Phase 3 features in action → defendml.com/demo ✅ Book a security review → DM me P.S. If your team hit AI security blockers because existing tools couldn't scale, we built Phase 3 for you. Let's talk. #DefendML #AISecurity #ASL3 #EnterpriseAI #LLMSecurity #ProductLaunch #AICompliance