Side-by-side comparison of AI visibility scores, market position, and capabilities
$974.60M revenue TTM 2025 (+11% YoY); $3.51B market cap NYSE:TENB; #1 worldwide vulnerability management IDC 2024; Vulcan Cyber acquisition $148M Feb 2025; vulnerability leader
Tenable is a cybersecurity company founded in 2002 and headquartered in Columbia, Maryland, that pioneered the vulnerability management category and remains its global leader. The company was founded by Ron Gula and Jack Huffard around the Nessus vulnerability scanner, one of the most widely deployed security tools in the world, with a mission to help organizations understand and reduce their cyber exposure across their entire attack surface. Tenable's core conviction is that organizations cannot defend what they cannot see — and that comprehensive, continuous visibility into vulnerabilities is the prerequisite to effective security.\n\nTenable's platform portfolio includes Tenable.io (cloud-native vulnerability management), Tenable.sc (on-premises), Tenable OT Security (operational technology), Tenable Web App Scanning, Lumin (exposure-based risk scoring), and the Tenable One exposure management platform. The company serves enterprise and government customers globally with a product suite that covers cloud workloads, on-premises infrastructure, operational technology, and web applications. In February 2025, Tenable completed the $148 million acquisition of Vulcan Cyber, a risk-based vulnerability prioritization platform, expanding its capabilities in correlating vulnerability data with threat intelligence and business context.\n\nTenable reported trailing twelve-month revenue of $974.60 million as of 2025, up 11% year over year, and was named the number one worldwide vulnerability management vendor by IDC in 2024. The company trades on Nasdaq under the ticker TENB and competes against Qualys, Rapid7, and a growing set of cloud-native exposure management entrants. Its Nessus heritage, market leadership validation from IDC, and strategic expansion into broader exposure management through Tenable One and the Vulcan Cyber acquisition position it as the reference platform for enterprise vulnerability and exposure management.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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