Most AI products generate outputs and forget everything. Mercury was built differently — from a Raspberry Pi SD card up — with persistent memory, continuous observation, and an intelligence loop that compounds with every cycle.
Every AI product you are using today resets after every conversation. It generates outputs — content, analysis, recommendations — and then forgets everything. The next session starts from zero. There is no accumulation. No improvement. No memory of what worked or what did not.
For casual use, that is fine. For businesses that depend on continuous intelligence — that need AI to watch their environment, detect changes, remember what happened, and get smarter over time — it is fundamentally broken.
Mercury was built to solve this. Not by adding a memory feature to an existing AI product. By designing the correct architecture from the beginning — an append-only ledger, a typed adapter interface, a universal scoring formula, and a continuous observation loop — and running it in production until the intelligence compounds into something genuinely defensible.
The architecture is open. The ledger is not. Every cycle accumulates proprietary operational intelligence that cannot be purchased or replicated without time. That is the moat.
Every table serves the intelligence loop. Mercury_ tables are the core operational layer. Conference_ tables are the plugin layer. Core tables handle auth, sites, and integrations.
GSC Connector requires a fresh OAuth connection to produce live search signals. AI Gateway queued for verification. All core infrastructure connectors healthy.