Cloud Security

Upwind Security protects cloud environments from the inside out through a runtime fabric that delivers real-time visibility, prioritization, and threat detection. Unlike traditional configuration scanners, Upwind focuses on actual usage, analyzing workloads, network activity, APIs, and data flows to identify risks that truly matter. The platform automatically correlates exposures with runtime behavior, helping teams remediate active vulnerabilities faster and reduce the overall attack surface. Unified policy management and seamless integrations bring infrastructure, application, and identity security together in one view. Security and DevOps teams gain a single pane of glass across multi-cloud deployments, eliminating alert fatigue and unnecessary tool sprawl. Users get continuous, context-rich protection that makes cloud security faster, smarter, and more effective at scale.

KnowBe4 is the leading human risk management platform, empowering organizations to reduce their most targeted vulnerability: people. By combining AI-driven defense, behavioral analytics, and security awareness training, KnowBe4 helps employees recognize, resist, and respond to evolving cyber threats. Its cloud email security and agentic AI capabilities detect risky actions and stop phishing, malware, and social engineering attacks before they cause harm. Personalized training programs and real-time coaching drive lasting behavioral change while strengthening compliance and audit readiness. With over 15 years of behavioral intelligence and insights from 70,000 customers, KnowBe4 delivers proven protection across industries for a more resilient workforce, safer data, and a security culture built to rise above risk.

Gravwell is a time series data lake built to scale for enterprise data volumes. It offers a panoramic view of your security horizon and enables actionable insights through the Query Studio. Effortlessly filter and transform data to identify anomalies and understand user behavior, detecting potential security threats and attacker TTPs. The Gravwell search pipeline’s extensible structure promotes threat hunting and data exploration by using structure-on-read to extract, transform, and visualize data to execute complex and wide-reaching investigations. Since Gravwell uses one language for all investigations and detections, you can easily convert any threat hunt results directly into scheduled detections. What sets us apart are four differentiators - Our indexer pricing means you pay for the number of indexers in your cluster. Each indexer has an unlimited ingest, so your price doesn't change for sudden data spikes or if you have more data than originally thought. You are in charge of adding new indexers to meet your performance needs. - Our structure on read capabilities allows you to ingest and store data in its native format. There is no need to transform data to JSON or a specific format. Structure is applied to the data at search time. - Our query studio provides you with the flexibility to never stop asking questions of your data. - Our customer support is built into the price. All customers get access to our dedicated success program to switch, onboard, and train your team as quickly and with as minimal fuss as possible.

At Sagetap, we are transforming how technology solutions are discovered and evaluated. Our platform is crafted to help tech Vendors connect with leaders in the tech industry, or Sages, effortlessly and efficiently. Our platform exists to facilitate meetings between these tech sellers and tech buyers in a way that ensures buyer anonymity is always protected, preventing any spam or unwanted follow-ups.

Gomboc helps cloud and platform engineering teams fix infrastructure vulnerabilities automatically, reducing hours of manual remediation to minutes. Using deterministic AI instead of probabilistic suggestions, Gomboc delivers production-ready Infrastructure as Code fixes directly into Git workflows and CI/CD pipelines. Its DevOps CoPilot eliminates tickets and back-and-forth review cycles, allowing engineers to focus on building rather than fixing. Continuous guardrails and compliance enforcement ensure that every change aligns with security and governance standards. By automating remediation across Terraform, CloudFormation, and multi-cloud environments, Gomboc drives measurable efficiency and risk reduction. The result is faster, safer releases, higher engineering productivity, and clear ROI from AI adoption.

Stream is the AI-native platform built to fight AI-enabled attacks. It autonomously prevents, detects, hunts, and remediates exposures and threats across production at machine speed - driving risk toward zero. It replaces the fragmented stack of scanners, runtime agents, exposure tools and playbooks with one live model of production. Attackers don’t think in production boundaries anymore - Cloud, SaaS, identity, runtime, AI, network and on-prem no longer behave as separate estates. They operate as one connected system, and attackers move through them as one. The security industry answered with the opposite structure: separate tools, separate consoles, separate collection cycles - scanning for misconfigurations, listing vulnerabilities, producing findings for people to validate by hand. Adding AI agents on top of that structure only produces findings faster. The deeper problem is what a finding is. A finding describes the environment as it was when the scan ran. An attack happens in the environment as it is now. Finding a misconfiguration or a vulnerability is no longer the work. Closing exploitability, safely, inside a system that is still running, is the work. Defending Production needs a new approach : Stream is the only Autonomous Production Defense Platform that works across your entire production estate. It runs on a patented ProductionTwin®, a high-fidelity security data harmonization layer that models Cloud, SaaS, identity, runtime, AI, network, perimeter, on-prem, security controls, and the behavior running on top of them into one live model of production: real-time, fully correlated, continuously updating. Not a snapshot. And it does not stop at boundaries - the boundaries that fragment every other tool are the same boundaries an attacker moves across. Inside ProductionTwin they are one system. That single live data model is the foundation for everything Stream does: •⁠ ⁠Autonomous Prevention of attacks by finding and closing exploitable paths before an attacker finds them first autonomously. •⁠ Autonomous ⁠Detection of attacks as they move across boundaries, not just where they first appear, and by seeding deception canaries on the fly to slow down and mislead attackers before they reach anything real •⁠ Autonomous Remediation and Response - safely by simulating exactly what a containment action will do before it's taken, so the fix doesn't cause its own outage •⁠ Autonomous ⁠Hunting continuously against the live environment, instead of running a search against last night's data Autonomy is not a model problem. It is a ground-truth problem - an agent is only as safe as what it reads before it acts. Rebuild context out of logs and last night’s scan and the action is a guess about the present dressed as a decision - so a human is inserted, and becomes the bottleneck that made autonomy pointless. Read a live model and every step is computed instead: reachability, blast radius, impact before execution, closure after. The model enables the AI. The AI does not enable the model.