Armadin vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
AI-native cybersecurity using agentic attacker swarms. Founded by ex-Mandiant CEO Kevin Mandia. Record $189.9M Seed+Series A (Mar 2026). Founded 2025, Palo Alto.
About
Armadin was founded in 2025 in the United States by Kevin Mandia — former CEO of Mandiant, widely regarded as one of the world's foremost cybersecurity incident response firms — with a mission to fight AI-powered cyber threats with AI-native offensive and defensive capabilities. The company was built on the premise that as adversarial AI lowers the barrier to sophisticated attacks, the only effective defense is an equally capable AI system that can simulate, anticipate, and respond to attacker behavior autonomously.\n\nArmadin's platform uses agentic attacker swarms — coordinated AI agents modeled on real adversary tactics, techniques, and procedures (TTPs) — to conduct continuous red teaming, vulnerability discovery, and attack surface validation against enterprise environments. Unlike periodic penetration testing engagements, Armadin's agentic approach delivers persistent, automated adversarial pressure that reflects the reality of modern threat actors operating continuously. The platform integrates with existing security operations workflows to surface findings in actionable formats for blue team remediation.\n\nArmadin raised a record $189.9M across its Seed and Series A rounds in March 2026, an extraordinary funding level for a company founded just one year prior. The scale of funding reflects both Kevin Mandia's exceptional credibility in the cybersecurity market and the urgency enterprises feel around AI-native threat readiness. Armadin enters a market where legacy red team tooling and manual penetration testing are increasingly inadequate against AI-assisted adversaries, positioning it as a defining company in the next generation of offensive security.
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.
About
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).
AI Visibility Head-to-Head
Key Details
Capabilities & Ecosystem
Capabilities
Integrations
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.