Side-by-side comparison of AI visibility scores, market position, and capabilities
Human-in-the-loop workflow automation; $35M Series A from a16z and Khosla (Mar 2025); connects 100+ apps with embedded human approval steps for AI-human collaboration. Founded 2021, SF.
Relay.app is a human-in-the-loop workflow automation platform founded in 2021 in San Francisco. The company was built around the insight that fully automated workflows break down at the edges — when decisions require human judgment, context that only a person has, or approval before an irreversible action. Relay.app's core design principle is that AI agents and humans should collaborate in workflows rather than the AI operating autonomously.\n\nThe platform connects to 100+ applications including Salesforce, HubSpot, Slack, Gmail, Notion, and Airtable, enabling teams to build complex cross-app automations with embedded human checkpoints — approval steps, form fills, and manual decisions that slot naturally into otherwise automated flows. Relay.app's AI agents can draft content, classify data, extract information from documents, and make routing decisions, with humans stepping in only where judgment is needed. Target users are operations, revenue, and customer success teams at mid-market B2B companies.\n\nRelay.app raised a $35 million Series A in March 2025 co-led by Andreessen Horowitz and Khosla Ventures, validating its human-in-the-loop positioning in a market increasingly crowded with fully autonomous automation tools. The funding has accelerated the expansion of its AI agent capabilities and integration library. Relay.app competes with Zapier, Make, and newer AI automation platforms but differentiates through its thoughtful balance between automation efficiency and human oversight.
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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