
Worked on the ScottLogic/InferESG repository, delivering features that enhanced ESG data extraction, analysis, and reliability. Developed dynamic knowledge graph integration by generating Cypher queries and data models from CSV data, leveraging Neo4j for scalable backend data modeling. Improved data integrity through prompt-driven Cypher query validation and explicit null filtering, while launching agent-based ESG analysis tools that utilized OpenAI for report generation. Refined agent architecture and routing for more reliable task execution, expanded asynchronous learning, and strengthened web scraping with realistic browser headers. Used Python, TypeScript, and Docker, focusing on backend development, API integration, and configuration management throughout the project.
January 2025 monthly summary for ScottLogic/InferESG focusing on delivering key architectural improvements, enhanced data collection quality, and improved developer documentation to drive reliability, scalability, and business value in ESG data extraction.
January 2025 monthly summary for ScottLogic/InferESG focusing on delivering key architectural improvements, enhanced data collection quality, and improved developer documentation to drive reliability, scalability, and business value in ESG data extraction.
December 2024 monthly summary for ScottLogic/InferESG: Delivered two major features enhancing data integrity and ESG analysis capabilities. Implemented Prompt-driven Query Integrity for Cypher with explicit null-filtering rules and examples added to prompts. Launched Materiality ESG Analysis Suite, including a dedicated Materiality Agent for ESG report analysis and a Materiality Chat Agent leveraging OpenAI for report generation, with enhanced file handling, configuration, and tests. Also fixed datastore prompt to skip null values to improve query reliability. These efforts improved data quality, enabled more reliable ESG analysis, and accelerated report generation.
December 2024 monthly summary for ScottLogic/InferESG: Delivered two major features enhancing data integrity and ESG analysis capabilities. Implemented Prompt-driven Query Integrity for Cypher with explicit null-filtering rules and examples added to prompts. Launched Materiality ESG Analysis Suite, including a dedicated Materiality Agent for ESG report analysis and a Materiality Chat Agent leveraging OpenAI for report generation, with enhanced file handling, configuration, and tests. Also fixed datastore prompt to skip null values to improve query reliability. These efforts improved data quality, enabled more reliable ESG analysis, and accelerated report generation.
November 2024 performance summary for ScottLogic/InferESG: Delivered a Dynamic Knowledge Graph integration enabling CSV-driven Cypher and data model generation in Neo4j; completed MIT license adoption to improve compliance and distribution clarity. Highlights include business-ready data modeling automation and governance improvements with low-risk licensing changes.
November 2024 performance summary for ScottLogic/InferESG: Delivered a Dynamic Knowledge Graph integration enabling CSV-driven Cypher and data model generation in Neo4j; completed MIT license adoption to improve compliance and distribution clarity. Highlights include business-ready data modeling automation and governance improvements with low-risk licensing changes.

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