For RevOps and data teams feeding AI agents, Nekt is a data platform that centralizes 200+ sources into governed, permissioned tables and exposes them to Claude, ChatGPT, and other agents through a native MCP server.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Nekt is working to become the data layer that sits between a company's scattered systems and the AI agents acting on them, centralizing more than 200 sources into governed, permissioned tables that Claude, ChatGPT, and other agents can query directly rather than call app by app. Its own homepage messaging leans on that agent-first framing, positioning the product as what a company's data needs to look like before revenue agents can act on it reliably. Public conversation about Nekt is early: as a young, founder-led company, it's still building the third-party discussion base that more established data and orchestration tools carry, though the product itself is built squarely for the agent-tooling moment.
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Business Profile
Nekt was founded in 2024 in Brazil and has moved quickly from a data-connector tool into a full agent-facing data platform, adding a semantic layer, governed permissions, and native MCP support on top of its original 200+ source integrations. The company has raised roughly $1.3M across an early seed round and a smaller follow-on, and operates with a lean team of around eight. It remains independent and privately held, still building out core product surfaces: 200+ connectors, an SQL-generating natural-language analyst, and API access for both platform data and agent queries.
Agent Readiness
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Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Nekt ships a native MCP server that gives Claude, ChatGPT, and other agent clients direct query access to its governed data tables, alongside a Platform API and Data API for programmatic access. Nekt Analyst converts natural-language questions into SQL against those same governed tables, and access is scoped through granular, permissioned API tokens rather than blanket credentials. The build-out centers on making one governed dataset queryable by both agents and people through the same layer.
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