How It Works
What is built, per the node’s audit evidence:
Full Next.js 14 SaaS frontend is code-complete with landing page, live dashboard, alert feed, stats API, and AI-powered ingest endpoint.
This is the current #1 priority active build at Neuruh — the first product targeted to generate paying subscribers.
evidence: _AUDIT-LEDGER.jsonl · cycle 1 · build_state
Python scanner backend exists separately.
The platform consists of two components: a Python-based scanner backend that captures and transcribes audio from sources like Broadcastify and RTL-SDR, and a full Next.js 14 SaaS frontend with a real-time dashboard, alert management, API endpoints, and Stripe billing.
evidence: _AUDIT-LEDGER.jsonl · cycle 1 · build_state
Not yet deployed to Vercel.
Not yet deployed to Vercel.
evidence: _AUDIT-LEDGER.jsonl · cycle 1 · build_state
Full Next.js 14 SaaS frontend is code-complete with landing page, live dashboard, alert feed, stats API, and AI-powered ingest endpoint.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
Python scanner backend exists separately.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
Raw transcript text is POSTed to the `/api/ingest` endpoint on the Next.js frontend.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
This endpoint sends the text to GPT-4o-mini with a specialized classification prompt.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
The classified alert is stored in Supabase.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
The frontend dashboard polls the alerts API every 30 seconds.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
Each alert card shows: type icon, severity badge, zone tag, time-ago timestamp, AI summary, AI insight, and location pin.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
The scanner.py backend POSTs raw text to the DISPATCH-IQ ingest endpoint.
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state
The frontend framework is Next.js 14 (App Router, TypeScript).
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evidence: _AUDIT-LEDGER.jsonl · cycle 2 · build_state