Send the evidence
Bills, interval data, service photos, panel schedules, cut sheets, one-lines, rejection notes, and prior permits.
When the reviewer asks for a clearer load basis, ampscale organizes the utility data, bills, service evidence, project documents, and open assumptions into a path the installer, PE, AHJ, and utility can actually inspect.
Permit rescue is not a workaround for code or professional review. It is a fast way to turn scattered evidence into a clean load basis and next-step plan.
Bills, interval data, service photos, panel schedules, cut sheets, one-lines, rejection notes, and prior permits.
Separate measured demand, proposed load, assumptions, missing proof, and jurisdiction-specific review questions.
A reviewer-ready packet showing what can proceed, what needs field verification, and what likely requires upgrade planning.
The first implementation is deliberately narrow: code context, SLD, panel schedule, load calculation, parsed gaps, and a correction matrix. It does not become a generic permit marketplace or a rubber-stamp PE flow.
Resolves the AHJ, adopted code profile, and local overlay for the Canon-seeded metros: Bay Area, Greater LA, DFW, and Austin.
Extracts service size, voltage, phase, meter, main breaker, panels, disconnects, grounding, and proposed EVSE equipment from OCR text.
Reads circuit numbers, descriptions, breaker sizes, poles, voltage, connected load, and protection notes such as GFCI/AFCI.
Separates measured demand, proposed continuous load, service capacity, assumptions, and pass/fail headroom using the metered-demand basis where present.
Turns rejection notes and parsed gaps into required evidence, code references, plan-sheet edits, and resubmittal response items.
Keeps measured, customer-provided, assumed, and missing inputs separate so PE review and AHJ acceptance remain explicit.
Permit rescue produces a source-grounded packet outline before anyone edits drawings: jurisdiction context, artifact summaries, missing evidence, code sections, checklist status, and the correction response matrix.
The output makes assumptions visible, cites source evidence, and routes licensed review where required. It never pretends that AI, software, or a PDF replaces an AHJ, utility, or PE.