Side-by-side comparison of AI visibility scores, market position, and capabilities
Rebranded to Veradigm Jan 2023; $620-635M revenue expected 2024; 180K+ physician users; 3.6% ambulatory EHR market share; sold hospital business to Harris Computer $700M 2022; Nasdaq suspended Feb 2024
Allscripts is a healthcare IT company founded in 1986 in Chicago, historically one of the largest providers of electronic health record and practice management software for physician practices and hospitals in the United States. The company rebranded to Veradigm in January 2023, signaling a strategic pivot from legacy EHR software toward data analytics, life sciences research enablement, and healthcare network intelligence — areas where its 180,000+ physician user base and de-identified patient data assets create differentiated value for pharmaceutical and payer customers.\n\nThe Veradigm platform combines its ambulatory EHR and practice management software with a data and analytics layer that aggregates real-world clinical data for life sciences research, post-market drug surveillance, and population health analytics. Its network of physician practices represents one of the largest ambulatory data footprints in the US, making Veradigm a valuable partner for pharmaceutical companies seeking real-world evidence and patient registries. The company maintains a 3.6% share of the ambulatory EHR market while building out higher-margin analytics and data licensing revenue streams.\n\nVeradigm (formerly Allscripts) targets $620–635M in revenue for 2024, serving 180,000+ physician users across its installed EHR base. The rebrand to Veradigm reflects management's intent to migrate the business model from competitive, commoditizing EHR software toward network and data platform economics. As life sciences companies increase investment in real-world evidence and physicians demand more integrated practice intelligence tools, Veradigm's combination of clinical workflow reach and data network assets gives it a credible platform for this strategic repositioning.
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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