Risqly
The Operating System for SaaS Renewals and Retention
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- Categories
- Analytics & MonitoringCRM
- Use Cases
- Risk ManagementData Integration
- Target Audience
- B2B SaaS CompaniesCustomer Success TeamsSaaS Founders
- Pricing
- Free
- Platforms
- Web
- Featured in
- Best CRMBest Tools for B2B SaaS Companies
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How AI and people discover Risqly on PeerPush
About Risqly
B2B SaaS teams move from reactive to proactive retention with Risqly. Customer data is unified across systems, enabling early identification of churn risk and clear insight into why accounts are at risk. Teams can prioritise the right actions, improve renewals, and drive measurable revenue impact. We deliver a unified view of customer data across CRM, billing, support, and product systems Predictive models that surface churn risk and renewal opportunities early. Risqly's explainable insights that highlight the drivers behind customer behaviour and automated workflows that enable immediate, scalable action across teams. When you partner with Risqly you add retention intelligence to your core offering. You'll be able to unlock new revenue streams and upsell opportunities. For scaling businesses you can prove impact with measurable churn and renewal outcomes.
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Product Updates (2)
FinTech Retention Health Check
It would be great to get your feedback on the below tool as this will be used to help develop the marketing messaging. www.risqly.com/fintech-retention-health-check
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Find the blind spots in your SaaS retention engine
www.risqly.com/retention-health-check A quick and easy way to find the blind spots in your SaaS retention engine. ‍No database integrations required, 3 minutes and it's completely free. A data-backed assessment of your B2B SaaS customer retention maturity, operational visibility, and revenue risk exposure.
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Reviews (3)
Average 4.7 out of 5
Based on 3 reviews
Comments (4)
Risqly addresses a massive SaaS pain point - tracking and managing renewal revenue. The fact that it's ranked #3 today shows strong product-market fit. For any B2B company, missed renewals directly impact ARR. Having an automated system to
How does the explainability layer actually surface drivers? Linear coefficients, SHAP-style attributions, or attention over recent events? Most "why is this account at risk" tools end up with labels CS teams don't trust.
@honestdev fully agree most tools wrap SHAP outputs in a label and call it explainability, and CS teams see through it. During our validation period we spoke directly with CSMs and CROs, and that feedback directly shaped how we built.
rather than post-hoc model attributions, the drivers are the raw signals themselves, a failed invoice, an exec sponsor who's gone dark, a 40% usage drop in the last 30 days. Each one is weighted and surfaced transparently.
Nice, wish you the best with this it look promising
@meirraTeam Thank you :)
We want to enable teams to spend more time strengthening relationships that will generate ARR, rather than being stuck in the data weeds.