QuadSci AI

QuadSci is the most predictive and prescriptive AI for customer intelligence. We use AI and ML to transform product-usage data into predictable revenue growth.

[QuadSci AI @quadsciai]

Super proud to be a tech partner of @Salesloft . Check out the write up on the Salesloft blog: https://t.co/tc6xcG7Yoh

[The AI Philes @TheAIphiles]

QuadSci Named “Machine Learning Company of the Year” in 9th Annual AI Breakthrough ... https://t.co/T3tfetOXEJ #MachineLearning

[Alexa | Startup founder @alexabelonix]

@Benchmarkitai @quadsciai Exactly this. i pinned the messy founder version of pre-sales research

[QuadSci AI @quadsciai]

“Revenue teams don’t have a data problem. They have a signal problem,” said Sean Murray, co-CEO of QuadSci. We won the ML Company of the Year for second time! https://t.co/LKFtJdKMBz

[QuadSci AI @quadsciai]

@Benchmarkitai Thanks for having us on the pod! Dan had a great time chatting with Ray

[Benchmarkit @Benchmarkitai]

Your product telemetry is generating trillions of signals.
Most GTM teams aren't reading any of them.

Dan Harmeson, co-CEO of @quadsciai on the AI to ROI podcast:

👉 Median GRR dropped 4pts to 84% (2026 Benchmarkit data)
👉 At $100M+ ARR, 95% of revenue is renewals + expansion
👉 A 2pt GRR drop can't be offset by new logos in 12 months
👉 QuadSci runs retrospective predictions first — 90%+ accuracy before you trust the forward signals
👉 Same approach applies to governing AI token costs

Product data is the answer. Most companies just aren't using it.

🎧 https://t.co/YyJDktQZKP

#SaaS #GRR #NRR #AItoROI

[QuadSci AI @quadsciai]

AI isn’t the problem. Most models are already powerful enough.

The real issue is that they sit on top of fragmented data and disconnected workflows, which means they generate output no one can actually use.

QuadSci takes a different approach by grounding AI in unified customer behavior and tying it directly to revenue outcomes.

[QuadSci AI @quadsciai]

Most revenue teams are still guessing.

The real signals behind churn and expansion aren’t in your CRM. They’re buried in product usage data that go-to-market teams never see.

We built QuadsAI to change that.

By unlocking those hidden signals with machine learning, revenue leaders can:

• See risk and growth up to 12 months ahead
• Act on predictions with ~90% accuracy
• Drive durable expansion with 150% NRR

You can’t protect revenue you can’t see coming or leaving.

That’s the gap we’re closing.

https://t.co/EWBXTHTYt6

[QuadSci AI @quadsciai]

@svpino An LLM by itself isn't any of these. ML should do the modeling & GenAI should turn the output into explanation and action. At QuadSci, we build statistically grounded models on product telemetry to predict outcomes like churn/growth and use GenAI to explain & prescribe action.

[QuadSci AI @quadsciai]

More than half of SaaS companies are seeing NRR decline, and it’s not because teams are doing less. It’s because the signals they rely on to understand customers haven’t evolved with the market.

[QuadSci AI @quadsciai]

SaaS is under increasing pressure. New rounds of funding are harder to come by and more than half of SaaS cos are seeing NRR decline. What customers tell you doesn't lead to growth. The opportunity is in what they do on your software. #telemetryistruth

[QuadSci AI @quadsciai]

Kevin Knieriem, former president at Clari and now CRO at Asana, sat down with Bill Binch to talk about QuadSci and predictive intelligence. https://t.co/pkM3kM1Myx

[QuadSci AI @quadsciai]

More than half of SaaS companies are seeing NRR decline, and it’s not because teams are doing less. It’s because the signals they rely on to understand customers haven’t evolved with the market.

[QuadSci AI @quadsciai]

NRR is no longer something SaaS companies can assume will hold. It’s something that has to be actively managed. Expansion only happens when customers consistently find value, and most teams still lack visibility into whether that’s actually happening.

[QuadSci AI @quadsciai]

Customer intelligence should answer one thing:
What are customers doing, and what does it mean for revenue?

See 7 use cases that turn customer intelligence into revenue action: https://t.co/KSRDRq6fCf

[The SaaS News @TheSaaSNews]

QuadSci @quadsciai Raises $8 Million in Series A

#AI #GTM #CustomerIntelligence #PredictiveAnalytics #RevenueAI #AISolution #SaaS #SeriesA #Funding
https://t.co/uyWF69zufG

[QuadSci AI @quadsciai]

Product analytics make feature usage visible. CRMs capture commercial activity and conversations. Customer success platforms summarize engagement and health. None of them were designed to reveal the full customer journey. But with AI you can connect the dots using telemetry.

[QuadSci AI @quadsciai]

Buyer beware. Claims of 99% accuracy in AI tools, without a clear sense of what that actually means, is a sign it's too good to be true.

You need to understand exactly where that accuracy metric comes from, how it was calculated & the business context.

[QuadSci AI @quadsciai]

Product analytics, CRMs, and CS software can't tell you the whole story of your customers. Cohorts AI delivers intelligent customer segmentation and behavioral analysis that transforms how you build roadmaps, nurture customers and grow your business.

https://t.co/XDxZEEBdH9