Flagship deployment

Catch likely solar plan issues before the AHJ or utility does.

Solar QC Agent reviews project emails and engineering plan PDFs, cross-checks them against AHJ and utility requirements, and flags likely issues before submission.

Inputs

What it reviews

Project email thread + plan PDFs + AHJ rules + utility requirements + historical corrections catalog

✅ Fewer resubmittals. Faster approvals. Better internal QC.

Permitting delays are expensive.
Late QC catches make them worse.

When errors are found after submission, teams waste time in correction loops, engineer rework, and status chasing.

📑

Plan review issues

Missing notes, wrong code references, and documentation mismatches slow approvals down.

🏛️

AHJ variation

Requirements shift by jurisdiction, and teams lose time checking the same rules repeatedly.

🔁

Correction loops

Every avoidable rejection creates more back-and-forth between ops, engineering, and permitting.

Review faster. Catch more. Keep humans in the loop.

1

Ingest project materials

Watch project inboxes or upload plan sets and attachments directly.

2

Cross-check requirements

The agent compares plan details against AHJ, utility, and historical correction patterns.

3

Flag likely issues

Your team gets findings with severity, confidence, and evidence for human review.

A QC layer built for real project ops.

Review

Plan + file review

  • Engineering PDF ingestion
  • Metadata extraction
  • Project fact summary
  • Document-linked findings
Rules

Requirements intelligence

  • AHJ requirement lookup
  • Utility-specific checks
  • Corrections catalog matching
  • Evidence-backed issue flags
Ops

Human review queue

  • Approve or dismiss findings
  • Escalate to engineering
  • Track reviewer decisions
  • Build repeatable QC process

Use Solar QC Agent as your first flagship deployment.

If your team is buried in plan reviews, AHJ variation, and correction loops, this is the kind of workflow AI should be handling with you.