Persistent Adds Databricks Accelerator for Governed AI in Financial Services

Persistent Systems, a provider of digital engineering and enterprise modernization services, has received a Databricks Brickbuilder Solution specialization for its Banking, Financial Services and Insurance offering, expanding its work around governed data and AI deployments in regulated environments.

The latest instance is the Company's Merchant Risk Management and Fraud Detection solution, built on Databricks and powered by Agentic AI, which enables institutions to shift from reactive fraud controls to predictive, intelligent merchant risk management. It is designed to help financial institutions develop and deploy AI applications while maintaining controls around data governance, security, compliance, and model operations. Persistent leverages the Databricks Data Intelligence Platform to unify financial data into a governed, AI-ready layer. Delta Lake, Unity Catalog, and Mosaic AI support the development, evaluation, and monitoring of data products, models, and AI agents within institutional security and governance requirements.

Persistent also provides secure, data-grounded GenAI agents for operations, analytics, and compliance, supported by evaluation and monitoring mechanisms designed for accuracy, explainability, and alignment with BFSI workflows. The solution combines Databricks technologies with reusable components and industry-specific frameworks intended to shorten implementation work.

The offering also addresses governance requirements associated with generative and agentic AI. Financial institutions increasingly need to track the data used by AI systems, control access to sensitive information, and maintain oversight as models and agents become embedded in operational workflows.

For enterprise data teams, the specialization reflects a broader shift from isolated AI experiments toward platforms that combine model development with governance and production operations. In financial services, that architecture is particularly important because AI applications often depend on customer, transaction, and risk data subject to strict security and regulatory requirements.

Posted by Pure AI Editors on 09/21/2026