So, your AI vendor is building enterprise connectors — here are 9 questions to differentiate real enterprise AI systems

This post outlines critical questions for evaluating enterprise AI data connectors, focusing on the technical differentiators of indexing vs. federated fetch, permission enforcement (ACLs, identity graphs, real-time updates), sensitive data protection, data update frequency (minutes, API rate limits, crawl strategies), data modeling complexity (e.g., Slack's structure), breadth and depth of indexing (content, activity, people data, dynamic algorithms), knowledge graph organization, index storage location (cloud-prem, zero data retention with LLMs), and scalable connector infrastructure (horizontally distributed, handling API quotas and data complexity). It emphasizes that robust connectors are the foundation for intelligent AI agents.