Delos vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
San Francisco AI wildfire MGA covering 25,000+ CA policyholders/$40B+ insurance value; $9M Series A with 265,000 additional homes unlocked by better risk AI competing with Hippo and FAIR Plan for California wildfire insurance.
About
Delos Insurance Solutions is a San Francisco, California-based AI-powered wildfire insurance Managing General Agent (MGA) — backed with $9 million in Series A funding — providing homeowners in California's wildfire-stressed markets with insurance coverage that the state's major carriers have discontinued, using proprietary satellite imagery and AI risk models developed by academic researchers that outperform industry wildfire risk scoring to identify insurable properties within territories that traditional insurers have abandoned. Delos has insured 25,000+ California policyholders representing $40+ billion in total insurance value written on behalf of AM Best A-rated carrier partners. In 2024, Delos expanded insurable coverage by 265,000 additional Southern California homes across five counties by improving wildfire modeling confidence. Awards include MGA/MGU of the Year from Insurance Insider US and CB Insights Top 100 Global Fintech Companies for 2024. Founded in 2017 in San Francisco.
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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