Adapt.io vs Cube
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.
San Francisco CA semantic layer and headless BI platform; raised $100M+; API-first data access layer that sits between warehouses and any BI or AI consumer.
About
Cube is a semantic layer and headless business intelligence platform founded in 2019 and headquartered in San Francisco, California. The company was founded by Artyom Keydunov and Pavel Tiunov to solve the problem of metric proliferation in data-driven organizations: when every BI tool, internal application, and data consumer defines its own metrics independently, companies end up with different answers to the same business question depending on where they look. Cube provides a single semantic layer — a governed data model layer — that defines all business metrics and dimensions once, then serves them consistently to any downstream consumer via REST, GraphQL, or SQL APIs.\n\nCube raised $100 million across multiple funding rounds from investors including Bain Capital Ventures, Decibel Partners, and 468 Capital. Its platform is built on an open-source core (Cube.js) with hundreds of thousands of community users and deployments. The commercial Cube Cloud product adds managed infrastructure, a development environment, testing tools, query caching for performance optimization, and access controls. Cube's API-first, headless architecture allows it to serve metrics to traditional BI tools, embedded analytics applications, internal data apps, and increasingly AI assistants and large language model (LLM)-powered analytics tools.\n\nCube's caching and pre-aggregation engine is a significant technical capability: it automatically builds materialized aggregates from frequently run queries and serves them from a high-performance cache layer, dramatically reducing warehouse query latency and costs for dashboards and embedded analytics applications. This performance layer makes Cube a practical choice for public-facing embedded analytics where end users expect sub-second response times that direct warehouse queries cannot reliably deliver.
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