AxeAI finds your Bitaxe on the local network, explains why it is offline, benchmarks safe clock and voltage ranges, and keeps pushing for better accepted hashrate without treating your miner like a toy.
Rejects are rising while ASIC error stays clean, so the link gets fixed before clocks move.
AxeAI tracks RSSI, latency drift, disconnects, and reject pressure together.
Per-rig memory stores offline events, thermal history, and best learned profiles.
Fleet opportunity loss makes downtime and stale pressure visible in accepted hashrate terms.
AxeAI compresses accepted hashrate, reject pressure, thermal headroom, and opportunity loss into one operator surface.
One host device, one installer, automatic miner discovery, and manual IP recovery only when needed.
Safe sweeps, learned winners, thermal protection, network holds, and rollback memory stop reckless clock chasing.
Accepted work, reject pressure, uptime loss, and next safest move show up in one place instead of five tabs and a notebook.
Best for first rigs and solo miners who want discovery, monitoring, recovery guidance, and safe benchmarking without paying upfront.
For serious home operators who want one dashboard, one agent layer, and room to scale beyond a starter rack.
For builders, labs, and power users who want the full control plane without artificial fleet caps.
Run one installer on one laptop, desktop, or Raspberry Pi on the same LAN as the miners. That device becomes the secure bridge to the cloud.
Run BitHiveAI sweeps, let stable profiles and benchmark winners get cached, and stop relying on generic clock lore.
Use scored moves, network holds, health memory, and opportunity loss to push harder without silently wasting hashrate.
The firmware effort is now a visible part of the roadmap, but it is still coming soon. The current hosted app remains the live product.
The long-term goal is to move more autotune, control, and miner-aware intelligence closer to the hardware without losing the AxeAI cloud layer.
Even with future firmware, AxeAI still owns onboarding, fleet memory, benchmark history, solo-mining intelligence, and the user-facing AI experience.