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POC 16BStability guaranteeRScale classificationSmall build (single system)Wave 3POC
BSEMoridainDefenseSSO Defense ATRSolvFilter

Assured Sensing Stack

BSE cleans the sensor stream → detection (± SSO) → MoridainDefense ranks what the operator sees. One co-sell bundle from raw time series to role-tailored alert queue.

0.80
Recall@10 min (Phase 1 synthetic)
1.00
Cross-cuing rate (Phase 1)
97.8%
BSE win rate (135 dysts benchmark)
0.83
MoridainDefense Recall@10 (alerts)

The scenario

Set the picture

A shipboard radar track picture degrades under sea clutter and jamming. The fusion node still generates hundreds of candidate alerts per watch. The operator endpoint cannot host the fusion math — it needs a bounded queue that surfaces the threats that matter to that role without drowning in single-signal false positives.

Today's stack treats signal conditioning, detection, and operator triage as three separate procurements with three separate ML retraining cycles. When the AO changes, each layer drifts independently.

What it costs today

Custom denoising per sensor program. CFAR tuned per environment. On-device ML triage retrained per deployment. No shared bounded handoff between layers — each vendor optimizes locally and the operator pays the integration tax.

BSE mixed-noise win rate is 50.3% on the disclosed benchmark — co-sell with eyes open; quasi-periodic structural losses 2.2% disclosed.

What changes with SolvNum

Four Resonix SKUs compose a single Assured Sensing reference architecture — each layer validated independently, wired in the Phase 1 synthetic harness.

BBSE — bounded signal layer

Bounded-influence Takens LP denoising never degrades the input signal. 97.8% win rate on 135 dysts systems in the synthetic benchmark. Optional ABFR adaptive pre-screen (τ=1.2) before OS-CFAR in the hybrid wiring path.

RMoridainDefense — bounded operator queue

Fusion-node alerts compress to 17-byte bounded packets. Role/AO projection on the endpoint (32-byte static profile). Recall@10 0.83 on synthetic streams; cons-5 cross-cuing 1.000 in the 8-seed sweep.

Measurable outcome

What we'll claim — and how it survives review

Each line below maps to a captured number in the demo section. Every number is reproducible from the SolvNum validation suite.

  • Phase 1 synthetic harness: recall@10 minimum 0.80, cross-cuing 1.0 (20-seed strict gate).
  • G001-HYBRID-INT (job 8646): BSE→mor_adaptive(τ=1.2)→OS-CFAR→MoridainDefense — no regression vs baseline.
  • Optional SSO Defense ATR: +6–15 pp precision at 50% coverage on MSTAR (classification-only; bbox SSO not shippable).
  • Optional SolvFilter EKF prediction at dim=140: 74× cheaper than UKF, best NEES consistency at scale (SF-3 CONFIRMED).
  • Field operational tapes: POC — partner shadow required (G-001, G-003).

The demo

What was tested. How. What the script printed.

Phase 1 extension harness (20 seeds): BSE denoised time series → detection branch → synthetic fusion alerts → MoridainDefense bounded triage. Measured recall@10, cross-cuing rate, cons-5 injection test.

Hybrid wiring branch (job 8646): same metrics with ABFR pre-screen inserted before OS-CFAR. Compared against baseline chain without hybrid pre-screen.

Illustration

In-browser diagram of what the demo proves. The numbers underneath are the captured demo output.

Upstream · raw fusion ingest

300 alerts × 12 dims

~28.1 KB / cycle raw float64 — alert flood: watchlist, geofence, comms-pattern, dwell, vehicle sig, sigint, network, pattern-of-life, sensor corroboration, history…

Fusion mainframe

log-norm → per-signal cap → consequence × probability

log-space normalize
per-signal cap
cons × prob rank

17-byte handoff packet(+2 B AO tag · projection on)

5.6× vs raw float64
alert_id
4 B
score
2 B
cons
1 B
n_ctr
1 B
top-3 provenance
9 B
AO tag
2 B *

300 × 17 B = 5,100 B / cycle on the wire (base) · 19 B / alert with the optional 2-byte AO tag side-band · no model weights · no calibration tables

Per-endpoint local relevance projection

same packet stream → 32 B static role/AO profile per endpoint → bounded local re-rank (≤ 1 cons-band shift / entry) → top-K heap

severe-band (cons 5) alerts surface for every role they touch, regardless of profile

Operator endpoints · one stream → four role-projected queues

Strike pilot

Knee-board

profile · 32 Bair · ingress-corridor
priority · top 10live
1.089C5
2.142C4
3.217C5

SOF ground team

Handheld

profile · 32 Bground · in-AO
priority · top 10live
1.217C5
2.011C4
3.088C4

Ship CIC

Console

profile · 32 Bmaritime · surface
priority · top 10live
1.044C5
2.102C4
3.217C5

Vehicle TOC

Toughbook

profile · 32 Bground · convoy route
priority · top 10live
1.217C5
2.165C4
3.011C4
945 Bdevice memory
18ops / alert
32 Brole profile
0model weights
no FPfloating-point math

Captured demo output

The numbers the script actually printed.

Assured Sensing Phase 1 synthetic harness (strict 20-seed gate)
MetricResultGate
Recall@10 (min)0.80≥ 0.80
Cross-cuing1.00≥ 1.0
Hybrid wiring (job 8646)PASSNo regression

Evidence pointers

Where the claims live in the repo

These are the files a reviewer should run, read, or grep to re-derive every number on this page.

  • moridain/business/assured_sensing_stack.md
  • moridain/business/g001-assured-sensing-e2e-runbook.md
  • solv/17-defense-validation-gaps.md (G-001, G-003)
  • phase1_extension_20260525T163757Z/
  • G001-HYBRID-INT job 8646

Want to see this in your environment?

Brief us on a program where this POC matters.

ITAR-aware. Air-gapped delivery available. Every claim above traces back to a script in the public repo.

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