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We’ve just introduced a powerful new capability to the Inaza platform that puts more control in the hands of our clients—especially those with internal data and engineering teams. With our new Python integration, insurers can now write and deploy custom Python code directly within the Inaza environment.
Create tailored made solutions and get flexible access to your data—right where it lives.
Until now, most platform workflows relied on purpose-built modules created by the Inaza team. With this new release, clients can now upload their own Python their own code, from simple scripts to complex data engineering jobs and run them natively on our infrastructure. This means full autonomy to tailor the platform’s functionality to suit unique business needs—without compromising performance or security.
Whether it’s a bespoke claims validation process, a custom enrichment workflow, or a specific compliance logic—if you can write it in Python, you can run it on Inaza.
The real power of Python lies in its ecosystem. With this update, clients can now harness Python’s world-class data science and analytics libraries—like pandas, NumPy, scikit-learn, and more—directly on the data extracted and transformed by Inaza.
Run regressions. Build forecasting models. Conduct historical analysis. All in one place. No need to export to external systems or juggle tools—our platform now supports deep analytical work natively.
For insurance providers with in-house technical teams, this unlocks a new level of operational efficiency and insight without the need for any team retraining, allowing teams to build custom solutions in a language they already know (Python). Instead of relying on rigid out-of-the-box solutions, they now have the tools to innovate from within—quickly, flexibly, and at scale.
This release is part of our broader mission to make insurance data not just accessible, but actionable. And most importantly—yours.
