Side-by-side comparison of AI visibility scores, market position, and capabilities
Employee scheduling and time tracking app for hourly teams. Minneapolis MN, raised $35M+, used by 200,000+ workplaces across retail, food service, and healthcare.
When I Work is an employee scheduling and time tracking platform designed specifically for hourly and shift-based workforces. Founded in 2010 and headquartered in Minneapolis, Minnesota, the company has raised over $35 million in venture funding. The platform serves more than 200,000 businesses across the retail, food service, healthcare, and service industries, helping managers build schedules and communicate with their frontline teams through a mobile-first experience.\n\nThe platform's scheduling tools allow managers to create and publish weekly schedules, fill open shifts, and manage time-off requests in a drag-and-drop interface. Team members receive shift notifications via the mobile app, can request swaps, and communicate with their team through an integrated messaging feature. The time clock function supports GPS-based clock-in, kiosk mode, and web clock options to match different workplace environments.\n\nWhen I Work has positioned itself as the accessible, affordable option for small and mid-market businesses that need practical scheduling without the complexity or cost of enterprise workforce management suites. Its freemium entry point and simple onboarding have driven strong adoption in industries where workforce churn is high and manager bandwidth is limited.
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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