Side-by-side comparison of AI visibility scores, market position, and capabilities
Cybersecurity unicorn ($1.2B valuation). AI hyperautomation for security ops. 300% revenue growth (2025). Serves Marriott, PepsiCo, Uber. Founded 2020, Tel Aviv. $332M raised.
Torq was founded in 2020 in Tel Aviv with the mission of bringing enterprise-grade automation to security operations — a function that had long relied on manual analyst workflows and brittle, script-based automation tools. The company built a security hyperautomation platform that uses AI to orchestrate incident response, threat investigation, and remediation workflows across the full security stack, enabling security teams to respond to threats at machine speed without sacrificing analyst oversight.\n\nTorq's platform integrates with over 700 security tools and IT systems, enabling no-code and low-code workflow automation across SIEM, EDR, SOAR, ticketing, and cloud platforms. Its AI layer — Torq HyperSOC — can autonomously triage alerts, enrich indicators of compromise, and execute multi-step response playbooks, dramatically reducing mean time to respond (MTTR) for high-volume alert environments. Customers including Marriott, PepsiCo, and Uber have deployed Torq to handle thousands of daily security events that would otherwise require manual analyst attention.\n\nTorq achieved a $1.2B valuation and recorded 300% revenue growth in 2025, making it one of the fastest-growing companies in the cybersecurity automation market. The company's growth reflects both the acute analyst shortage in security operations and the increasing attack surface created by cloud-first enterprise architectures. Torq competes with legacy SOAR platforms like Splunk SOAR and Palo Alto XSOAR, differentiating through AI-native architecture, no-code accessibility, and a broader integration library.
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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