
From zero to one: how QAble built a QA practice for a real-time risk analytics platform
Standing up manual and automated QA from scratch for EigenRisk's EigenPrism platform, then scaling to 900+ automated test cases without slowing the release cadence.
Client
EigenRisk
Headquarters
Ann Arbor, Michigan, USA
Engagement
Ongoing, 1+ year
Platforms
Web, cross-browser
Technologies and tools
Results by the numbers
900+
Automated test cases
0→1
QA practice built from scratch
1+yr
Engagement duration
Faster
Release cycles
4×
Browser and OS environments
Daily
Agile QA governance
Here's a bit about EigenRisk
Industry
Insurtech
Platform
EigenPrism
Data providers
30+ connected
Reach
Global
EigenRisk is an independent insurtech firm behind EigenPrism, a real-time catastrophe risk analytics platform that brings data, geo-visualisation, modelling and analytics into one environment for reinsurers, insurers, brokers, MGAs and risk managers worldwide. The platform connects to more than 30 data and model providers, enabling high-speed event footprint analysis, location-based risk assessment and real-time catastrophe alerts at scale.
Risk decisions on EigenPrism are time-critical and the underlying data has to be right every time. That combination, complex analytical workflows, multi-source data integrations and cross-browser consistency, called for a QA practice built to the same standard, running alongside an evolving product roadmap and a release cadence that kept accelerating.
Before and after QAble
Before QAble
With QAble
No structured QA process in place
No test case library or requirement traceability
No regression testing coverage
No automation, all validation done ad hoc
No cross-browser or cross-OS testing
No QA governance or release readiness process
Releases delayed by defects found late in the cycle
No visibility into defect trends or product quality
Automation and manual testing efforts were disconnected
No consistent cadence for meeting sprint deadlines
Our engagement
QAble joined EigenRisk as its dedicated QA partner at a point when the platform had no structured testing process in place. Our team embedded directly into the product development lifecycle, starting with requirement analysis, building a test case library from scratch, and establishing end-to-end traceability across every user story and acceptance criterion tracked in Jira.
A core milestone of the engagement was scaling test automation significantly, building and maintaining over 900 automated test cases that ran as part of the sprint cycle. This let the team meet release deadlines consistently while expanding coverage well beyond what manual testing alone could reach. Regression cycles that had previously been a bottleneck were replaced with structured, automated suites that kept pace with the product's evolving roadmap.
Cross-browser validation across Chrome, Firefox and Safari on both Windows and macOS kept EigenPrism's analytics-heavy interface behaving consistently for every user segment. Confluence served as the central knowledge base for product understanding, housing feature documentation, requirement context and process notes that kept the QA team aligned with the product's evolving scope. Throughout the engagement, QAble maintained daily governance, participating in standups, triage sessions and sprint reviews, with daily and weekly QA status reports delivered to stakeholders by email, giving clear and continuous visibility into testing progress, defect trends and release readiness.
Engagement highlights
A QA practice built from zero, then scaled to carry release velocity: 900+ automated test cases, daily governance, and cross-browser coverage across Chrome, Firefox and Safari on Windows and macOS.
Engagement type
Ongoing partnership
Duration
1+ year
Automation scale
900+ test cases
Team size
Up to 4 QA engineers
What QAble delivered
Services
Manual and functional testing
Our team designed and executed detailed test cases covering functional, integration, smoke, sanity and regression scenarios across every sprint. Requirements and feature context lived in Confluence, while test cases, built with full execution steps, expected results, prerequisites and test data, were managed in Qase with complete traceability back to Jira. Positive, negative, boundary and edge-case scenarios were systematically covered to validate both new features and any existing functionality they touched across EigenRisk's risk analytics workflows.
Build QA into your platform before your next release, not after
Talk to us about standing up a QA practice for your platform, from test strategy and automation to daily governance and reporting.
QA built for platforms where accuracy can't wait
Real-time risk analytics demands QA that moves as fast as the data. QAble brings the structure, automation and governance your release cycle needs.
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