QuadSciA representative verified their company email and completed GTM Report’s profile fact-check. Not a ranking, endorsement, or paid placement.
For customer success and RevOps leaders at B2B SaaS companies, QuadSci is a predictive customer-intelligence platform that combines product telemetry, CRM, and call data into a custom model forecasting churn and expansion 9-18 months ahead.
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 →
QuadSci is positioning itself as a customer-intelligence layer for revenue teams, using product behavior to identify churn risk and expansion opportunities before renewal. Its approach combines telemetry with CRM and conversational data in models tailored to each business. [Its website](https://quadsci.ai/) centers that predictive use case. Its GTM footprint is early, with outside attention focused on funding and the churn-and-expansion category. The company's own communication adds detail around explainable predictions, model maintenance and the engineering work involved in customer deployments.
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Upside
SalesfinityClari, Reltio, Movable Ink, Boomi, Tenable
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Business Profile
Founded in 2023, QuadSci builds predictive customer-intelligence software for B2B SaaS companies, with backing from Crosslink Capital, Correlation Ventures, and Alumni Ventures Group. It closed a Series A in February 2026, bringing total funding to $12.1 million, and has used it to grow go-to-market, engineering, and data science headcount past 35 employees. QuadSci says its models have processed trillions of product telemetry events, and the product line has expanded from its original churn-and-expansion forecasting engine into a newer behavioral-segmentation tool. The company remains independent.
Agent Readiness
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Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
QuadSci publishes an MCP surface for its prediction system, alongside Q-Chat, an agent product built by its own GenAI engineering hire. Prediction scores come paired with an explainability layer designed to give a reasoned story rather than a bare number, a property aimed as much at agents consuming the output as at human reviewers. The team behind it is still growing, with data-science and forward-deployed hires added within weeks of each other this year.
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