OpenEvidence vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
OpenEvidence hit $100M+ ARR in under a year serving 430K+ US physicians (40% of all US doctors) at $12B valuation ($700M raised); fastest-growing physician AI platform, founded 2022 Miami.
About
OpenEvidence is an AI clinical evidence platform founded in 2022 and headquartered in Miami, Florida. Built specifically for physicians, the platform applies large language models trained on peer-reviewed medical literature to deliver instant, evidence-backed answers to clinical questions at the point of care. Its founding mission is to democratize access to the best available medical evidence so that every physician can practice at the highest standard, regardless of institution or specialty.\n\nThe platform aggregates and synthesizes peer-reviewed studies, clinical guidelines, and drug databases, presenting structured answers with citations that meet physician-grade accuracy standards. Unlike general-purpose AI assistants, OpenEvidence is purpose-built for clinical workflows. It is free to use for physicians, with monetization routed through pharmaceutical and healthcare industry partners who value the platform's direct access to practicing clinicians.\n\nOpenEvidence has achieved remarkable traction, reaching over 430,000 US physicians — approximately 40% of the entire US physician population — making it the fastest-growing physician AI platform on record. The company crossed $100M ARR in under a year from launch and earned a $12 billion valuation on $700 million in total funding. This trajectory places OpenEvidence among the fastest-scaling healthcare AI companies globally and signals a structural shift toward AI-assisted clinical decision-making at the point of care.
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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