Side-by-side comparison of AI visibility scores, market position, and capabilities
$74.6M funding ($47M Series C 2022 Accel-KKR); $66.6M revenue 2024 (+35.9% YoY); 11K customers; 230 employees; acquired WizeHive Aug 2024; grants management leader
Submittable is a grants and social impact management platform founded in 2010 and headquartered in Missoula, Montana. Originally built as a submissions management tool for literary magazines and creative organizations, Submittable evolved into a comprehensive platform for managing grant applications, corporate social responsibility programs, scholarship disbursements, and community impact initiatives. Its mission is to help organizations deploy resources efficiently and generate measurable social impact at scale.\n\nThe platform provides end-to-end tools for grant program design, applicant intake, review workflows, decision management, reporting, and payment disbursement. Submittable serves foundations, nonprofits, corporations, and government agencies running structured giving or scholarship programs that require managing high volumes of applications with diverse reviewer teams. In August 2024, Submittable acquired WizeHive, a competing grants management platform, significantly expanding its customer base and capabilities in the nonprofit and higher education segments.\n\nSubmittable reached $66.6 million in revenue in 2024, a 35.9% year-over-year increase driven by organic growth and the WizeHive acquisition. The company serves over 11,000 customers and has raised $74.6 million in total funding, employing approximately 230 people. Submittable competes with Fluxx, Salesforce Nonprofit, and Blackbaud in the grants management category. Its strong growth rate in a previously underpenetrated vertical and the strategic acquisition of a direct competitor demonstrate execution discipline and clear category consolidation ambitions.
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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