JPMorgan Chase & Stack Overflow partner to Tackle AI ‘hallucinations’ in Enterprise Code
NEW YORK – November 13, 2025 - JPMorgan chase is turning to the power of community-driven knowledge to address a critical roadblock in enterprise AI adoption: the tendency for AI models to generate inaccurate or misleading information – often called “hallucinations” - when applied to complex internal systems. In a recent episode of the Leaders of Code podcast, JPMorgan chase VP of Platform Engineering Ramprasad Rai revealed a strategic collaboration with Stack Overflow to leverage its structured Q&A data as a grounding force for AI, ensuring accuracy and compliance within the financial institutionS vast codebase.
The partnership aims to solve a fundamental problem: AI models trained on general datasets frequently enough lack the specific internal context required for reliable performance in enterprise environments. “AI models frequently hallucinate in enterprise settings due to a lack of internal context,” Rai explained. By fine-tuning AI using Stack Overflow’s meticulously curated data, JPMorgan Chase hopes to build probabilistic tools anchored in trusted, internal expertise, balancing AI-driven productivity gains with stringent security and compliance demands.
This approach recognizes that accomplished enterprise AI projects aren’t solely about sophisticated algorithms, but about providing those algorithms with access to verified, relevant knowledge. Stack Overflow CEO Prashanth Chandrasekar highlighted the unique suitability of the platform’s data, stating that its structured Q&A format provides “ideal fine-tuning material for the next generation of AI models.” The collaboration underscores a growing industry trend: the recognition that a robust knowledge layer, fueled by community contributions, is essential for unlocking the full potential of AI within large organizations.
