Fixing Data Before Retrieval

Reddit r/AI_Agents Tools
data-quality knowledge-base ai-agents data-remediation api

Summary

The article argues that fixing underlying data quality is more critical than improving retrieval methods for AI agents, and introduces a platform that continuously audits knowledge bases to serve as a single source of truth via an API.

Data retrieval has been the focus of agent engineering efforts, but my thesis is that efforts need to be concentrated on ensuring underlying data is remediated, current, and structured for AI to fix the “garbage in, garbage out” issue. I’m building a platform that would connect to any data source once and continuously audit a knowledge base as a single source of truth for all AI agents. Served as an API endpoint. Founding team worked Ops and Data analysis at Series B and D startups, pitched to Tier 1 VCs and data-centric background. Deploying agents only went as far as we could manually remediate our knowledge base. Is anyone currently experiencing this? Would love to chat!
Original Article

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