Adapt.io vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
B2B contact database and sales intelligence platform. Chennai India, raised $4M+, provides 200M+ contact records and company profiles for global sales prospecting via web app and Chrome extension.
About
Adapt.io is a B2B contact database and sales intelligence platform that provides sales and marketing teams with access to over 200 million professional contact records and company profiles for global prospecting. Founded in 2016 and headquartered in Chennai, India, the company has raised over $4 million in funding. Adapt.io competes in the large but price-sensitive B2B contact data segment by offering broad global coverage at accessible price points, targeting individual sales professionals, SMBs, and growth-stage companies seeking affordable prospecting data.\n\nAdapt.io's contact database covers business email addresses, direct phone numbers, and firmographic data across companies globally. Its Chrome extension integrates with LinkedIn, enabling users to reveal contact information for profiles visited during prospecting research. The web application provides list-building tools where users can filter contacts by industry, company size, geography, job title, and technology stack to build targeted prospect lists for outbound campaigns.\n\nAdapt.io has built its user base largely in the Asia-Pacific and global SMB market segments where US-centric data platforms provide less coverage or carry price points beyond smaller teams' budgets. The platform's combination of international data coverage and affordable pricing has made it popular among sales teams in India, Southeast Asia, and Latin America targeting global markets. Adapt.io's API enables integration with CRM and sales engagement platforms for automated prospect data enrichment and list synchronization.
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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