For marketing and agency teams tracking client KPIs, Databox is an agentic analytics platform that pulls data from 130+ tools into live dashboards and adds an AI analyst that answers performance questions in plain language.
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 →
Databox is positioning itself as an agentic analytics layer that sits between the sprawl of marketing and client-reporting tools and the people who have to explain performance from them: dashboards pulling from more than 130 sources, paired with an AI analyst that answers plain-language questions about the numbers rather than requiring a dashboard build first. The September 2026 relaunch pushes that positioning further, reframing the product as infrastructure for agencies and AI-implementation teams building governed, permission-aware AI workflows on top of client KPI data rather than a reporting tool with AI bolted on. Public conversation around the brand is still early relative to that repositioning, without an established track record of practitioner discussion to draw on yet.
Rings AI
Goodfit
Champify
Amplemarket
WynterMorningstar, RWE, AkzoNobel, BambooHR, Wistia, CSL, Dana, Riachuelo, New Breed
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Business Profile
Databox has operated as a marketing and client-reporting analytics platform since 2012, based in Boston. Rather than publish funding or headcount figures, the company anchors its public narrative around scale of usage, citing service to more than 20,000 businesses, and around compliance, holding SOC 2 certification with GDPR-aligned practices. In September 2026 the company announced a two-year rebuild culminating in a relaunch as an agentic analytics platform, positioning the current product as a departure from its original dashboarding roots rather than an incremental feature release, with implementation services now offered alongside the free and paid dashboard tiers.
Agent Readiness
Not yet graded.
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Databox publishes both a REST API and an MCP server, the latter built to make the platform usable as a backend for AI assistants rather than just a dashboard. The MCP server exposes tools for ingesting data from arbitrary sources and for querying datasets in plain language, using OAuth for permission-scoped access, and it's built to work with Claude, ChatGPT, and Cursor alongside Databox's own AI analyst.
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