Worked on the Arize-ai/openinference repository to deliver a Flexible Input Payload Processing feature, expanding the system’s ability to handle dictionary-shaped content and part payloads. This enhancement improved data ingestion flexibility, allowing for more versatile API integration and reducing the need for extensive pre-processing in backend development workflows. Addressed compatibility issues in the google-genai integration by enabling support for dict-shaped payloads, which increased reliability and interoperability with GenAI workflows. Leveraged Python for backend development and data processing, maintaining code clarity and documentation throughout. The work accelerated experimentation with downstream systems by streamlining input handling and supporting diverse payload formats.