Side-by-side comparison of AI visibility scores, market position, and capabilities
AI workspace for sales reps that auto-updates Salesforce, enforces methodologies like MEDDPICC, and captures call notes with AI. $49.6M raised; tens of thousands of users in thousands of companies.
Scratchpad is an AI-powered sales productivity workspace founded in 2019 and headquartered in San Francisco, providing Salesforce-connected tools that eliminate the manual data entry burden for account executives and sales teams. The company has raised $49.6 million across three rounds, including a $33 million Series B in January 2022 led by Craft Ventures with participation from Accel.\n\nScratchpad's core offering is a fast, flexible workspace that surfaces Salesforce data alongside AI-generated call notes, pipeline views, and deal scorecards—allowing reps to update fields, leave notes, and manage deals without switching between Salesforce tabs. Its AI call recorder and notetaker automatically capture and transcribe customer conversations, then use AI to analyze interactions and automatically update Salesforce fields based on what was discussed. The platform enforces sales methodologies including MEDDPICC, SPICED, and BANT by surfacing methodology completion scores and flagging missing qualification data.\n\nScratchpad is used by tens of thousands of reps inside thousands of companies and is priced accessibly at $19–$49 per user per month, making it popular with mid-market and enterprise teams seeking Salesforce productivity gains without a full process overhaul. The platform competes with Groove by Clari and Momentum.io in the Salesforce productivity and activity capture space.
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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