Combining AI engineering with synthetic data intelligence for production-grade AI across underwriting, fraud, compliance—with privacy and governance by design.
Cognition AI and zypl.ai announced a strategic go-to-market partnership to deploy autonomous AI engineering and governed synthetic data workflows across financial institutions, focused on MENA and Central Asia. Under this partnership, banks, fintechs, and financial infrastructure providers will gain access to Cognition’s Devin and Windsurf autonomous engineering platform alongside zypl’s Lucid AI development environment and state-of-the-art synthetic data generator zGAN—enabling institutions to accelerate production deployment of cutting-edge AI models while maintaining strict data privacy, regulatory compliance, and auditability from day one.
The collaboration addresses a critical inflection point across the region: AI adoption is no longer constrained by ambition but by engineering capacity, legacy architecture, and regulated data availability. Institutions face mounting pressure to deliver measurable outcomes—improved underwriting accuracy, stronger fraud defenses, faster software releases, modernized core systems—while navigating fragmented tooling, privacy restrictions, and slow validation cycles that trap promising pilots in perpetual testing.
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By unifying Cognition’s autonomous software engineering capabilities with zypl’s privacy-safe synthetic data generation and AI model governance, the partnership aims to collapse time-to-production from quarters to weeks. Financial institutions can now deploy AI-driven decisioning models, automate complex software workflows, and modernize legacy infrastructure—all within governed, privacy-compliant environments designed for regulated markets.
Deployment Focus & Production Use Cases
The partnership will prioritize engineering-intensive, regulator-driven modernization initiatives across financial institutions:
Core Banking Modernization
-COBOL to Java migrations
-Monolith decomposition into microservices
-API enablement for open banking
-Framework upgrades (.NET, Java, Spring)
Regulatory-Driven Code Change Programs
-Large-scale schema updates (e.g., ID format changes)
-Reporting pipeline refactors to meet central bank mandates
-Risk engine logic updates across distributed systems
Security & Technical Debt Reduction
-Automated remediation of SonarQube findings
-CVE patching across hundreds of repositories
-Deprecated library upgrades and dependency modernization
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QE & Regression Automation
-Autonomous test case generation
-Regression cycle reduction
-CI/CD failure triage and repair
CI/CD & DevOps Modernization
-Jenkins to GitHub Actions migration
-Azure DevOps integration
-Pipeline definition rewrites and validation
The integrated offering will be deployed via secure cloud environments, ensuring data residency, zero data exposure, and full auditability across model lifecycles.
