Cribl provides data observability solutions that help tech teams collect, route, transform, and analyze logs and metrics. Cribl Stream routes and transforms data on either on-premises infrastructure or in the cloud, while Cribl Edge gathers real-time observability data from edge devices and forwards it to Stream or other destinations. The platform integrates with services like Office 365 and Microsoft Azure to simplify data collection and visualization. The goal is to give organizations real-time visibility into their data, improve operational efficiency, and strengthen security by managing data flows and observability insights.
Company Size
1,001-5,000
Company Stage
Series E
Total Funding
$596.4M
Headquarters
San Francisco, California
Founded
2018
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Competitive Salary
Stock Options
Medical, dental, and vision insurance
Flexible spending account (FSA)
401(k) plan offered (US)
Parental Leave
Professional Development and Career Growth
Generous Vacation and Holiday Policy, including 2 Floating Holidays for holidays you observe
Employee Resource Groups that reflect our values driven company culture
Cribl announces 2026 Customer Award winners leading the way in telemetry and AI. Moody's, ServiceNow, and Prudential Financial among organizations recognized with the inaugural Cribl GOAT Customer Awards. September 30, 2026 10:00 ET | Source: Cribl SAN FRANCISCO, Sept. 30, 2026 (GLOBE NEWSWIRE) - Cribl, the AI Platform for Telemetry, today announced the winners of its first Cribl GOAT Customer Awards at CriblCon 2026. The awards recognize organizations and partners that are using Cribl to take control of their telemetry data, operate at massive scale, prepare for AI-driven workflows, and help their companies succeed. The 2026 Cribl GOAT Customer Award winners are: * Data in Control: Moody's * Scale Without Limits: ServiceNow * AI Acceleration: Prudential Financial and University of Nebraska * Partner Innovation: Blackwood Associates "Our customers run some of the most demanding environments in the world, and this year's winners are setting the standard for what great Security and IT look like," said Abby Strong, Chief Customer Officer at Cribl. "They've taken control of their data and put it to work on the problems that matter most to their business. We're proud to celebrate them, and we're excited to keep building with them for whatever comes next." To learn more about the Cribl GOAT Customer Awards and this year's winners, visit https://cribl.io/customer-awards/. About Cribl Cribl is the AI Platform for Telemetry, purpose-built for IT and security data. Cribl's platform is a single, shared infrastructure that powers its own SIEM, observability, AI SOC, and other solutions, alongside custom applications people and AI agents build on top of it. Cribl provides a control plane to route and govern AI traffic, protect sensitive data, and monitor AI usage, cost, performance, and risk, so they can investigate issues and take action faster. Trusted by over half of the Fortune 100, Cribl gives IT and security teams the choice, control, and flexibility to build custom tools, run ready-made solutions, or route data anywhere, without paying to store it twice. Founded in 2018, Cribl is remote-first with an office in San Francisco. Media Contact: [email protected]
Introducing Cribl Detect, delivering a new way to SIEM. A complete security information and event management (SIEM) built on the platform security teams already trust. September 29, 2026 10:00 ET | Source: Cribl SAN FRANCISCO, Sept. 29, 2026 (GLOBE NEWSWIRE) - Cribl, the AI Platform for Telemetry, today announced Cribl Detect, built on the company's open data platform to provide a complete SIEM at up to 50% less cost than other companies. Cribl Detect gives security teams a better way to detect, investigate, and respond to threats without locking their telemetry into another monolithic, single-vendor stack. Cribl's new platform-first approach lets customers adapt and customize their SIEM to their unique security operations. This announcement brings Cribl into the $8.2 billion SIEM market. AI-generated attacks increase both the speed and sophistication of threats, putting pressure on security teams to detect and respond faster. Since Cribl Detect runs on the company's agentic AI-powered platform, with built-in inference and an agentic runtime, it can move beyond static, rules-based detection. Intelligence from Cribl's AI security operations center (AI SOC) capabilities helps automate detection and investigation workflows, applying analytics closer to the data to surface high-fidelity, actionable signals, reduce noise, and prioritize the threats that matter most. Together, these capabilities help security teams find blind spots and improve security outcomes. Security teams face difficult choices with today's SIEMs For years, security teams frustrated with their SIEMs have faced two flawed options. Legacy monolithic SIEMs offer integration without choice, forcing customers into one vendor's schema, one vendor's pricing model, and per-gigabyte economics that turn analysis into a tax. Newer "SIEM-less" stacks assembled on general-purpose data platforms offer choice without integration. Teams get to pick their tools, but they also become the integrator, stitching together separate schemas, contracts, and pipelines themselves. Cribl Detect is designed to offer the best parts of both: the openness and customizability of a platform-first approach with the comprehensive out-of-the-box detection, investigation, and response capabilities of a purpose-built solution. This same platform approach powers Cribl's expanding portfolio of solutions. "Customers don't want the SIEM they have today, and they don't have the resources to build the SIEM they want," said Clint Sharp, co-founder and CEO of Cribl. "With Cribl Detect, we've taken a different approach that solves both problems - an out-of-the-box SIEM experience built on a highly flexible platform specifically for telemetry that allows customers to adapt, mold, and even rebuild the SIEM for their specific needs. And because the platform natively integrates inference and an agentic runtime, Cribl Detect goes beyond rigid rules to catch fast-moving AI threats." Skip the "DIY" headaches While a "do it yourself" approach to SIEM and security operations can sound appealing, enterprises are rarely prepared to build and support what they need. Cribl's new way to SIEM offers an alternative that starts with the same telemetry organizations already access using the Cribl platform they already trust, in open formats they can control. This means Cribl Detect's alerts, investigations, and analytics can run against data wherever it resides, rather than being confined or duplicated to a monolithic, single-vendor stack. With Cribl Detect, federation allows analysts to investigate across distributed telemetry in pipelines, data lakes, object stores, and existing tools. Cribl also applies detections in-stream as telemetry moves through the pipeline, bringing security logic to the data wherever it flows, getting the right signals moving earlier, so correlation and investigation can happen faster. A key differentiator of Cribl Detect is that its detections and detection posture management (DPM), triage with AI security operations center (AI SOC), security orchestration/automation/response (SOAR), and compliance/governance capabilities all inherit access to any data available in the platform. This makes it possible to run the product without having to move historical data first. "Cribl Detect brings together two capabilities that matter to practitioners: investigating across data they already control and identifying detection gaps, broken rules, and missing telemetry," said Francis Odum, cybersecurity researcher at Software Analyst Cyber Research. "Building these capabilities into its existing data platform is a compelling direction for Cribl, giving security teams a path to modernize their SOC without creating another proprietary data silo." Built-In DPM and AI triage to accelerate incident response Cribl Detect includes detection posture management that gives security teams a continuously updated view of what they are and aren't detecting. Cribl Detect not only maps existing detections against MITRE ATT&CK techniques, surfacing coverage gaps, broken or noisy rules, and missing telemetry, but also provides recommendations and workflows for fast remediation. Alongside rules-based detections, AI SOC intelligence powers automated detection techniques that catch threats rules alone would miss. AI-driven triage, investigation, and disposition technology then helps analysts move from alert to answer faster, without manually correlating data across tools. Organizations that adopt Cribl Detect can expect lower total costs than incumbent SIEMs, since it is priced on infrastructure rather than an analysis tax. Cribl Detect is available now for Cribl.Cloud customers. To learn more, read its blog. About Cribl Cribl is the AI Platform for Telemetry, purpose-built for IT and security data. Cribl's platform is a single, shared infrastructure that powers its own SIEM, observability, AI SOC, and other solutions, alongside custom applications people and AI agents build on top of it. Cribl provides a control plane to route and govern AI traffic, protect sensitive data, and monitor AI usage, cost, performance, and risk, so they can investigate issues and take action faster. Trusted by over half of the Fortune 100, Cribl gives IT and security teams the choice, control, and flexibility to build custom tools, run ready-made solutions, or route data anywhere, without paying to store it twice. Founded in 2018, Cribl is remote-first with an office in San Francisco. Media Contact: [email protected]
Cribl has acquired technology assets from Radiant Security's AI-based security operations centre solution. The acquisition includes intellectual property for autonomously qualifying, analysing, and processing security alerts. The deal marks Cribl's second security technology acquisition this year, following CardinalOps in July. Cribl will integrate the AI-driven SOC technology into its telemetry data platform, enabling security teams to ensure AI makes appropriate decisions based on relevant data. The platform generates custom qualification logic for each alert rather than relying on predefined playbooks, executing investigations directly from telemetry data regardless of storage location. This approach aims to improve threat detection and reduce false positives. Cribl CEO Clint Sharp said the acquisition addresses data silos in the $121 billion security market, providing security teams with comprehensive insights as AI transforms operations.
Cribl advances ai-powered security operations with new AI SOC acquisition. Cribl has announced it has acquired technology assets from Radiant Security's AI-native security operations center product including intellectual property to autonomously triage, investigate, and resolve security alerts. With this acquisition, Cribl moves further into security and is adapting this AI SOC technology to run as an application on its telemetry data platform, giving security teams peace of mind that AI is making high-quality decisions over the right data. "Too much of the $121 billion security market is trapped in data silos, giving security teams incomplete information," said Clint Sharp, co-founder and CEO of Cribl. "We're breaking that cycle. By pairing AI SOC technology with Cribl's open telemetry platform, we're ending the era of siloed solutions and giving security teams the intelligence they need, right when AI is reshaping the entire operations landscape." Cribl's platform makes telemetry data actionable wherever it lives, fueling faster, more accurate threat investigations. AI SOC capabilities generate custom triage logic on the fly for each alert rather than relying on pre-built playbooks, and execute those investigations directly against telemetry data wherever it resides. Security teams will be able to detect threats and reduce false positives more effectively, transforming incident response into a seamless, high-fidelity operation. This is Cribl's second security technology acquisition this year, following its acquisition of CardinalOps in July. As AI reshapes security operations, capabilities that once justified being sold as standalone products increasingly make more sense running on a shared telemetry platform than as another disconnected tool that creates its own data silo. "Cribl's approach centers on transforming raw telemetry into a unified foundation for AI-driven applications," said Andrew Braunberg, Principal Analyst at Omdia. "By layering AI SOC, threat detection, and observability on top of its open data platform, Cribl is enabling organisations to customise their security stacks and finally unlock the true value of their data." This acquisition is one piece of a broader direction for Cribl's platform, and more additions to its platform will be shared at CriblCon on September 28, 2026.
Cribl buys Radiant Security's AI SOC tech in second security deal of 2026. Telemetry data company Cribl Inc. today said it has acquired technology assets from artificial intelligence security operations startup Radiant Security Inc. The purchase covers... Source and context SiliconANGLE · Prepare 6-24 months Aug 19, 2026, 1:00 PM Today's signal Fast orientation Structural Shift Confidence Medium · 6-24 months Reality status Reported development Real, still developing. Treat this as a concrete reported move, while keeping some distance between the underlying fact and the broader consequences being inferred from it. Signal panel Scan the signal before you read the analysis. * Signal level - Structural Shift * Signal strength - High * Time horizon - 6-24 months * Human impact - Medium * Economic impact - High * Governance impact - High * Confidence - Medium Original signal What the source is actually reporting. What happened Telemetry data company Cribl Inc. today said it has acquired technology assets from artificial intelligence security operations startup Radiant Security Inc. The... Who is involved The clearest named actors are Cribl and Radiant Security. The likely spillover reaches companies, platform operators, and workers likely to absorb the operational change. What changed Capital, competitive position, or market structure is moving around this part of the AI stack. It is being reported now because money, leverage, or competitive positioning in AI is visibly shifting. Chip rewritten report A fuller reader version of the report. Reader version SiliconANGLE reports this core fact: Telemetry data company Cribl Inc. today said it has acquired technology assets from artificial intelligence security operations startup Radiant Security Inc... The clearest named actors are Cribl and Radiant Security. The likely spillover reaches companies, platform operators, and workers likely to absorb the operational change. Capital, competitive position, or market structure is moving around this part of the AI stack. It is being reported now because money, leverage, or competitive positioning in AI is visibly shifting. For readers, this belongs in the AI Risks and Governance lane and the AI Business and Markets topic, which means the important details are not only who announced what, but which expectations, costs, rules, or capabilities may now move around it. The useful reading is simple: Capital and competitive pressure may be shifting around this part of the AI stack. Chip interpretation What it means The factual signal is straightforward: Telemetry data company Cribl Inc. today said it has acquired technology assets from artificial intelligence security operations startup Radiant Security Inc. The purchase covers... Read this through The practical question is whether this changes incentives, costs, rules, or behavior beyond the announcement itself. Decision test Read this through budgets, workflow design, labor pressure, and business adaptation rather than through launch language alone. For anyone affected by business, the useful test is whether this changes trust, cost, rules, capability, or expected human judgment after the first attention wave passes. Why this matters The consequence is more important than the headline. These are the areas most likely to move if this reported change hardens into policy, infrastructure, or default expectation. Impact card Business impact. This can change budgets, rollout timing, or vendor leverage faster than the headline suggests. The practical business question is whether it shifts cost, speed, or bargaining power. Impact card Human impact. People may not feel the effect immediately, but the signal can still change day-to-day expectations. It matters once the behavior becomes normal, not just once it gets announced. Impact card Governance impact. This is really about who gets to approve, delay, or shape deployment. Once release decisions move closer to institutions, technical change becomes a power question. Impact card AI ecosystem impact. This matters to the AI ecosystem if it starts to change standards, expectations, or the balance between builders, buyers, and regulators. Repetition is what turns this from news into infrastructure. Who gains / who is pressured Follow the incentives, not the announcement. * Teams that adapt early: They can convert new capability into faster workflows, lower cost, or clearer strategic positioning. * Infrastructure and platform providers: They benefit when AI usage deepens and demand moves upward through the stack. Who is pressured * Slow incumbents: They are exposed if they wait too long to translate the signal into operational change. * Roles built on repeat tasks: They feel pressure when AI starts taking over routine judgment or task execution. Multiple perspectives Trust improves when the angles are visible. Enterprise view The useful lens is whether this changes cost, workflow design, procurement logic, or execution speed inside a company. Worker view The real question is whether the change removes routine work, raises expectations, or shifts what counts as valuable human judgment. Investor view The signal matters if it changes margins, adoption speed, defensibility, or where value accumulates across the stack. What humans should do Primary action: Prepare. * Review the workflow, budget, policy, or product area this signal touches before it becomes urgent. * Decide what would trigger a real change in plan if more stories of this kind appear. * Translate the signal into one concrete preparedness step for the team rather than vague concern. Signal memory Original source Source and evidence still matter. This page is a Chip interpretation of the original article. It is not the original article. Please read the original source for the full report. Curation note: this brief uses the source link, attribution, and original Age for AI commentary. It is not permission to repost the publisher's full text, images, or reporting elsewhere. What readers are saying. No comments yet