Chainguard vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Seattle software supply chain security (founded 2021); $892M+ raised, $3.5B valuation (Apr 2025), $40M ARR growing 640% YoY with zero-CVE container images for ANZ Bank/Canva/GitLab competing with Snyk for DevSecOps.
About
Chainguard is a Seattle, Washington-based software supply chain security company — having raised over $892 million total including a $356 million Series D in April 2025 at a $3.5 billion valuation and an additional $280 million growth financing from General Catalyst's Customer Value Fund in late 2025 — providing enterprises with hardened open source container images and virtual machine base images rebuilt from source daily with zero known CVEs (common vulnerabilities and exposures), eliminating the vulnerability debt that accumulates in standard open source distributions. Founded in 2021 by CEO Dan Lorenc (9 years at Google securing code and infrastructure), Kim Lewandowski (Google representative on the Open Source Security Foundation Governing Board), Matt Moore (Google, creator of the original "distroless" container image), and Ville Aikas (co-founder of Kubernetes), Chainguard's founding team pioneered the open source supply chain security concepts — sigstore (code signing), SLSA (supply chain levels for software artifacts), and distroless containers — that became CISA and NIST software security standards. The company grew from ~$5 million ARR in 2023 to $40 million ARR by January 2025 (640% year-over-year growth) and projects exceeding $100 million ARR before end of 2026. Chainguard serves 150+ paying enterprise customers including ANZ Bank, Canva, GitLab, HPE, Snap, Wiz, and Anduril.
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).
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