eVetPractice vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Cloud veterinary practice management covering records, scheduling, invoicing, and pharmacy for small-animal clinics. El Segundo CA; developed by Covetrus as the cloud-native complement to legacy AVImark; targets practices moving to browser-based systems without on-premise hardware or IT maintenance overhead.
About
eVetPractice is an El Segundo, California-based cloud-based veterinary practice management software that provides independent veterinary clinics with scheduling, electronic medical records, treatment tracking, invoicing, pharmacy management, and client communication in a single web-based platform. Developed by Covetrus, eVetPractice represents the company's cloud-native veterinary practice management offering alongside its legacy AVImark on-premise system, targeting practices ready to move to a browser-based system without the hardware and IT maintenance overhead of on-premise software. The platform is designed for small-animal general practices and emergency hospitals, with clinical templates and workflows appropriate for companion animal medicine.\n\neVetPractice's pharmacy management module is a notable capability, allowing veterinary practices to manage in-clinic medication dispensing, track controlled substance logs, and connect to online pharmacy fulfillment through Covetrus's online pharmacy network. This pharmaceutical connectivity aligns with Covetrus's broader strategy of integrating its animal health distribution and pharmacy businesses with its practice management software. Practices using eVetPractice can process prescription refill requests and manage client prescription histories within the same system used for scheduling and medical records, reducing the context-switching that comes with managing separate pharmacy and practice management platforms.\n\neVetPractice competes with Shepherd, Digitail, ezyVet, and the modernized versions of legacy systems in the cloud veterinary practice management market. The company's positioning within Covetrus gives it integration advantages with the broader Covetrus ecosystem including diagnostic imaging, laboratory connectivity, and prescription management, but also means its development roadmap is influenced by the priorities of a large animal health distributor rather than solely by independent veterinary practice needs. eVetPractice serves practices primarily in the United States with a focus on the independent practice segment.
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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