Traditional data engineering often relies on manual processes for metadata generation, schema mapping, data profiling, and ETL code creation slowing delivery and increasing errors. HARMAN’s Agentic AI Framework addresses these inefficiencies with intelligent agents powered by large language models (LLMs).
Built on a modular, cloud-native architecture, the framework delivers autonomous workflows, contextual understanding, and continuous learning. With capabilities like explainable prompts, memory retention, semantic reasoning, and human validation, teams can reduce manual workload, ensure auditability, and scale smarter data platforms with confidence.
