Kaman.ai - Your data, unified. Your agents, deployed everywhere.

Hey Product Hunt! We're the team behind Kaman, and we'd love to tell you what drove us to build this. Every AI agent demo looks great — until you ask it about your actual data. That's when the cracks show: stale context, no memory between sessions, siloed databases that agents can't reach, and ballooning LLM costs from routing everything to GPT-4. We spent months running agents in production and hitting every one of those walls. So we built the infrastructure layer we wished existed — starting with KDL, a version-native data lake designed specifically for AI workloads. Sub-second queries, automatic versioning, time travel, and OpenLineage-compatible lineage tracking — without the Spark/JVM overhead of Delta Lake or Iceberg. The rest of the platform grew from there: hierarchical agent memory (KMMS), 16-channel deployment, 39+ MCP connectors, and intelligent multi-provider LLM routing that's cut inference costs by 35–55% in production. We're live and would love your feedback — especially from anyone who's wrestled with data infrastructure for AI agents. Ask us anything! 🚀