Question 1

What is QuadSci?

Accepted Answer

QuadSci is a customer intelligence AI platform that uses product telemetry to predict customer churn, identify growth opportunities, and prescribe actions for go-to-market teams. It transforms real customer behavior into predictive insight, behavioral understanding, and execution strategies through machine learning and embedded AI agents.

Question 2

How does QuadSci predict churn and growth?

Accepted Answer

QuadSci predicts churn and growth by analyzing historical product telemetry and identifying behavioral patterns that correlate with retention, contraction, and expansion. Its machine learning models generate forward-looking predictions up to 12–18 months in advance based on how customers actually use a product.

Question 3

What is product telemetry and why does it matter?

Accepted Answer

Product telemetry is the data generated from how customers use a software product, including events, feature usage, sessions, and system interactions. It matters because real usage behavior provides a more accurate and earlier signal of churn and growth than CRM data, surveys, or subjective health scores.

Question 4

What is Growth AI?

Accepted Answer

Growth AI is QuadSci's predictive intelligence engine that forecasts customer churn, contraction, and expansion. It uses product telemetry and behavioral data to identify revenue trajectory and surface early signals of risk and opportunity.

Question 5

What is Cohorts AI?

Accepted Answer

Cohorts AI is QuadSci's machine learning system for behavioral customer segmentation. It groups customers based on real usage patterns and identifies how adoption behavior correlates with retention, churn, and growth outcomes.

Question 6

What is Q-Chat?

Accepted Answer

Q-Chat is QuadSci's AI agent framework that translates predictive insights into prescriptive actions for go-to-market teams. It explains why an account is at risk or growing, identifies the underlying behavioral signals, and recommends specific next steps based on product usage and best practices.

Question 7

How does Q-Chat work with Growth AI and Cohorts AI?

Accepted Answer

Growth AI predicts what will happen. Cohorts AI explains how customers behave. Q-Chat turns those insights into action. Together, they create a system that connects customer behavior to predictive outcomes and recommended execution strategies.

Question 8

What data does QuadSci use?

Accepted Answer

QuadSci primarily uses product telemetry, including feature usage, event streams, session activity, and API interactions. It can also incorporate CRM, customer success, and data warehouse inputs to enrich predictions and connect insights to GTM workflows.

Question 9

How is QuadSci different from traditional health scores?

Accepted Answer

QuadSci uses product telemetry and machine learning to generate predictive and explainable insights. Traditional health scores rely on rules, surveys, and subjective inputs, which are often lagging indicators and less reliable predictors of future outcomes.

Question 10

How accurate is QuadSci?

Accepted Answer

Accuracy varies by dataset, but QuadSci has demonstrated up to 94% accuracy in predicting churn and strong accuracy in identifying growth opportunities up to 9–18 months in advance.

Question 11

What integrations does QuadSci support?

Accepted Answer

QuadSci integrates with 50+ enterprise tools across CRM, product analytics, customer success, data infrastructure, and communication platforms. This includes systems like Salesforce, Snowflake, Gainsight, and Slack, allowing insights to flow directly into existing workflows.

Question 12

Do we need a product analytics tool like Pendo or Amplitude for you to use our telemetry data?

Accepted Answer

No but if you have one, it helps. QuadSci can consume telemetry from Pendo, Amplitude, Mixpanel, Heap, FullStory or any other product analytics tool. Any SaaS company has a robust observability metrics history from applications like Datadog, New Relic, Grafana or any other observability system. Our AIs operate completely fine with your home-grown metrics. Most importantly, our AI's are trained with your telemetry data as-is, we don't require new instrumentation to generate data to "fit" our products.

Question 13

How long does it take to implement QuadSci?

Accepted Answer

Most implementations take 4 to 8 weeks depending on data readiness and integration scope. Because QuadSci is deployed within your environment, timelines are primarily driven by data integration and setup.

Question 14

Does customer data leave our environment?

Accepted Answer

No. QuadSci is deployed within your infrastructure, so your data does not leave your environment. This ensures security, compliance, and full control over customer data.

Question 15

How do you handle security, privacy, and compliance (SOC 2, GDPR, ISO, etc.)?

Accepted Answer

QuadSci meets enterprise security standards. Each customer deployment inherits their own cloud security posture (AWS, GCP, Azure). No data leaves the environment. QuadSci is fully SOC 2 certified, and all engineers undergo background checks and customer-specific training.

Question 16

Can QuadSci work with both SaaS and on-prem/self-managed environments?

Accepted Answer

Yes. We support hybrid architectures — cloud, self-managed, or on-prem. Many customers combine cloud telemetry with on-prem observability metrics.

Question 17

Can this live across multiple CRMs or business units?

Accepted Answer

Yes. QuadSci can run across multiple CRM instances or business units within one organization, normalizing data in a single model view.

Question 18

How do your predictions and insights show up in Salesforce, Gainsight, Clari or Gong for sellers and CSMs?

Accepted Answer

Insights appear where your teams already work — as CTAs, account scores, and growth classes directly inside Salesforce, Gainsight, Clari or Gong as well as similar GTM apps. Sellers see "growth class" and next-best-action guidance; CS teams see churn signals and retention plays.

Question 19

Who is QuadSci for?

Accepted Answer

QuadSci is designed for B2B software companies that want a more predictive and objective way to understand customer behavior, churn risk, and growth opportunities. It is used by go-to-market teams across revenue, customer success, product, and operations.

Question 20

What kind of ROI or business outcomes have customers seen?

Accepted Answer

Customers consistently see faster forecasting accuracy, reduced surprise churn, and new growth uncovered. To protect confidential information, we can't share client names but we can tell that one client hit their retention target for the first time in 8 quarters, identified and reversed $5M in surprise churn and discovered $32M in new expansion opportunities.

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