Miner evidence
Kernel/runtime logs, status screens, hashrate, temperature, fans, shares, pool state, and other miner-reported evidence.
Drop in a miner log, fleet export, screenshot, telemetry, or repair history. Get the likely cause, the evidence behind it, and the safest next check.
Read-only·No miner control·Free to try
See the evidence-first workflow in action, then open the live ChatGPT plugin and try it with your own evidence.
No mining account connection is required. Supply only the evidence you want analyzed.
Kernel/runtime logs, status screens, hashrate, temperature, fans, shares, pool state, and other miner-reported evidence.
Compare cohorts, outliers, topology, DNS/TCP evidence, rack boundaries, PDU data, power, thermal, and shared failure patterns.
Use supplied repair history, incident notes, prior symptoms, and recurrence patterns without inventing missing events.
The result keeps observations, missing evidence, likely causes, confidence, and the next safe check visibly separate.
Important claims should trace to supplied evidence, preserve age/freshness, and keep disagreements visible.
Missing remains Unknown. Confidence is explicit, and “Insufficient Evidence” is allowed when the evidence cannot support a conclusion.
Shared infrastructure and competing explanations are considered before isolated failures, followed by the safest high-value next observation.
Bitcoin Mining Troubleshooter reasons over evidence supplied to the AI session. It does not add a miner-control backend or privileged remote-management path.
Five synthetic scenarios let you test the reasoning without exposing real customer data or credentials.
5,250 miners · startup/recovery patterns, Unknowns, explicit units.
Download sample4,800 miners · topology + reachability evidence.
Download sample4,920 miners · feed loading + thermal evidence.
Download sample3,500 miners · 12,050 events · recurrence reasoning.
Download sample3,000 synthetic cases · healthy, startup, thermal, pool, PSU, and hashboard symptoms.
Download sample1. Download a sample. 2. Attach it in ChatGPT. 3. Ask:
What most likely happened, and what should I check next?
Open the official ChatGPT plugin and bring the mining evidence you want diagnosed.
Bitcoin Mining Troubleshooter grew from firsthand mining operations experience and software built around the diagnostic problems technicians and operations teams encounter.
Built from real Bitcoin mining operations experience and software developed around day-to-day diagnostic work.
About the developeraustin@wnclogiclab.comThe synthetic suite exercises fleet-scale reasoning; it is not a substitute for hardware acceptance testing.
See benchmark methodology for the public evaluation model.
No. v1.1.0 reasons over evidence supplied to the AI session and ships no hosted collection or mining-control backend.
No. The five release scenarios are synthetic. Private real-world validation material is not published here.
No. Bitcoin Mining Troubleshooter is standalone. ASIC Intelligence Desktop is a separate product in development.
That is the existing public repository/package name. The user-facing product is Bitcoin Mining Troubleshooter, powered by ASIC Intelligence.
The public package is source-available under the PolyForm Shield License 1.0.0. Use, modification, and redistribution are subject to that license. See the license terms or contact austin@wnclogiclab.com.
A separate mining-operations intelligence platform currently in development. The Troubleshooter does not require Desktop, and Desktop capabilities are not represented as Troubleshooter capabilities.
Trying the product comes first. Vendors and mining operators can also discuss compatibility work or separately scoped development partnerships.
Run a diagnosis, test the synthetic demos, and report diagnostic-quality issues using sanitized evidence.
Use in ChatGPT →Firmware, API, monitoring, repair, power, networking, and infrastructure vendors can fund concrete compatibility work.
Integration paths →Mining operators and hosting companies can discuss separately scoped ASIC Intelligence product evaluation and development.
Design partnership →