RF INTELLIGENCE · QALARC PRODUCT

The radio band, made readable.

RFAI Monitor captures live RF with an Airspy Mini (HackRF One on transmit), demodulates every conversation in the band, transcribes it with local Whisper, understands it with a local GLM 4.7 Flash model, and fingerprints the physical radio behind each transmission — filed into a searchable on-device archive. v0.8.0, field-tested from a bush valley to Bondi Beach.

9,470

transmissions in the production archive — 73.2 h of airtime, all searchable

80ch → 1

all Australian UHF CB channels captured in a single 6 Msps span

2s

local GLM 4.7 Flash intent + urgency classification per transmission

0bytes

leave the machine — STT, LLM, TTS and fingerprinting all run on-device

01 — What RFAI is

A signals-intelligence stack that fits in a backpack

One laptop, one SDR, every layer of understanding — from photons to priorities.

  • Capture. Airspy Mini pulls 6 Msps across 24–1700 MHz; the DSP engine demodulates NFM, WFM, AM and SSB, with digital signals (DMR, C4FM) detected and labelled instead of mistranscribed. All 80 UHF CB channels monitored in parallel from one capture.
  • Listen. Carrier squelch gates every transmission to a clean WAV; faster-whisper small.en transcribes locally (~6% WER on clean captures) with streaming partials and per-clip quality scoring.
  • Understand. A local GLM 4.7 Flash model classifies intent and urgency in ~2 s per transmission; a regex+model hybrid extracts callsigns (formal and phonetic), Q-codes, channel refs and CTCSS tones.
  • Identify. The fingerprinting engine reads carrier-frequency offset, spectral envelope and key-up transients to tell apart individual physical radios — field-verified on two identical handhelds.
  • Remember. Everything lands in SQLite + FTS5 with audio playback, then flows out through a Comms API with native Discord/Slack webhook formats.

Commercial foundation shipped in v0.8.0: named capture sessions with JSON/CSV export, and operator (full TX) vs consumer (listen-only, server-side gated) editions.

02 — The panels

Nine panels. Every one is a link.

Each panel opens directly in the hosted demo — no hardware, no login. Against a live engine, every panel also pops out as a standalone window for kiosk or second-screen use.

Beyond the panels

Voice descrambling (static, blind-rolling and keyed LCG for BK4819 fleets), UV-K5 fleet firmware flashing over DFU, morse TX/RX with auto-calibrating timing, SSTV, a psytrance-encoded data-over-RF link (PSYLINK), and text-to-RF transmission via Kokoro TTS.

04 — The AI stack

Every model runs on this machine

No API keys, no telemetry, no round trips. A laptop-class APU does the whole pipeline.

Speech-to-text
faster-whisper small.en, beam 5, radio-procedure prompt, VAD-gated, quality-scored; retranscribe on demand with larger models.
Understanding
GLM 4.7 Flash — abliterated — served by local Ollama: intent, urgency 0–1 and one-line reasoning, JSON-constrained and SQLite-cached, ~2 s per transmission.
Entities
Callsigns (VK-formal and phonetic), Q-codes, channel references, CTCSS tones — hybrid regex + model extraction stored per transmission.
Voice
Kokoro-82M TTS with 54 voices, ranked for radio readback; the same engine turns text into RF via the HackRF transmit path.
Fingerprinting
Carrier-frequency offset and drift, spectral envelope, key-up transient, cepstrum — online clustering into stable radio identities.

Why an abliterated model for radio traffic?

Distress traffic must never be declined, hedged or re-worded. A "mayday" transcript gets classified, flagged and scored — full stop. Classification output is JSON-constrained and validated against a fixed intent vocabulary before it ever touches the database, and any model can be pinned via a single environment variable.

HardwareRole
Airspy MiniPrimary RX — 24–1700 MHz, 12-bit, 3/6 Msps
HackRF OneTX + secondary RX — 1 MHz–6 GHz, up to 20 Msps
RTL-SDRISM + ADS-B lanes (SPECTRE sensor grid)
UV-K5 fleetFirmware flash panel, descramble targets
WiFi / BLEAll-domain sensor lanes — no SDR needed
05 — The wider grid

One interface system, sixteen native apps

RFAI is the main interface system in daily use at the centre of the qalarc Tauri ecosystem — four focus areas, one design language.

Focus areaApps
RF & signals intelligenceRFAI Monitor (v0.8.0) · SPECTRE all-domain SIGINT (v2.20) · Radio Agent Monitor · Cell Monitor
Communications & messagingQalarc Hub (Signal + WhatsApp) · HERALD accessibility · Privacy Chat · RFAI Chat mobile
Monitoring & operationsNetSleuth · chanalyse Monitor · Concierge Hub · email saviour · Snapper Manager
Identity, finance & utilityQal Wallet · GOETICA · MixID · DiskScope

Research lanes in flight: SPECTRE all-domain grid (drone Remote-ID with operator GPS recovery), PSYLINK 80 bps data-over-RF, GPS/APRS, P25/DMR/NXDN decoding, and the chat-first mobile build. Explore the whole project index →

06 — The small print

Field-tested, licence-clear

RFAI Monitor is designed, built, shipped and maintained by qalarc — an AI systems studio in Sydney, Australia. Verified in the field: 7/7 bands detected at ±0.0 kHz in TX/RX loopback, 28/28 full-system tests green, two identical radios separated by hardware fingerprint, 63/63 automated UI tests passing.

Licence: Qalarc Proprietary v1.0 — full ownership, control and commercial rights to qalarc; evaluation, research and personal use for everyone else. Third-party components keep their upstream licences. Transmitting on licensed frequencies may require an appropriate radio licence (ACMA class licences in Australia).