PATENT PENDING: U.S. App. 64/148,570 • Deterministic Entropy Telemetry Gating
QuantAIM CORE AI HOST-SIMD RUNTIME ENGINE
Host-CPU Vector Native • ARM64 NEON & x86 AVX-512

Telemetry triage for physical AI.
Zero MB GPU allocation.

QuantAIM Core AI replaces 4-week cloud batch ingestion with a line-rate host SIMD runtime. Triage 100,000 multi-sensor haulage and urban AV frames in under 1 hour inside your own VPC with --network none.

70%+ Cloud Write Purge
100% Anomaly Recall (H ≥ 0.40)
Read-Only Volume Mounted (:ro)
CORE TELEMETRY MONITOR
SIMD PASS 100k
Raw Ingestion Buffer 100,000 Frames (1.2 TB)
Nominal Purge Rate (H < 0.40) 72.4% Purged
HOST GPU ALLOC
0.00 MB
p95 FRAME LATENCY
28.4 ms
NETWORK EGRESS
0 BYTES
CRITICAL RECALL
100.0%
$ audit_summary.json emitted: checksum verified.
Hardware-Level Specifications

Architecture & Low-Level Kernels

QuantAIM Core AI eliminates GPU bottlenecks by computing spatial-temporal entropy directly inside host CPU vector registers.

Architecture Node 01

SIMD Micro-Kernel (AVX-512 & ARM64 NEON)

Vectorized line-rate entropy evaluation across uncompressed byte streams.

_mm512_popcnt_epi64 vaddq_u8

Standard perception stacks decode ROS/MCAP files into memory-heavy C++ object trees, saturating memory buses. QuantAIM uses zero-copy memory mapping (mmap) to stream raw chunks directly into 512-bit vector registers.

By executing parallel 1D histogramming and Shannon entropy passes concurrently across 8 execution lanes, the kernel completes heterogeneous sensor triage in < 35ms per frame on standard server host cores.

// Vectorized Entropy Accumulation Loop
__m512i v_bytes = _mm512_loadu_si512((const __m512i*)raw_ptr);
__m512i v_hist = _mm512_permutexvar_epi8(v_bytes, v_bins);
float entropy = quantaim_simd_shannon_h(v_hist);
if (entropy >= 0.40f) gate_to_wal_buffer(frame_id);
else commit_cold_parquet(frame_id);
Architecture Node 02

Born-Shannon Closed-Form Entropy Sieve

Mathematical gating replacing brute-force neural network filtering.

H(X) ≥ 0.40
DYNAMIC ANOMALY THRESHOLD
Spatial Variance H(s)

Evaluates spatial frequency across LiDAR point distributions and camera gradients. Rejects repetitive flat haul surfaces and clear sky.

Temporal Rate dH/dt

Detects instantaneous spikes in information density caused by sudden dust plumes, rockfalls, or moving objects in the clearance envelope.

State Gating Override

Fuses CAN bus wheel-slip, steering jerk, and braking deltas. Any dynamic vehicle event forces H=1.0 to ensure zero dropped anomalies.

Architecture Node 03

Zero-VRAM Operational Guarantee

Full perception GPU isolation for ISO 19014 & IEC 61508 functional safety.

0.00 MB VRAM

Autonomous machines allocate onboard GPUs exclusively to real-time perception, obstacle detection, and vehicle controllers. Running secondary models onboard risks thermal throttling or safety path contention.

QuantAIM Core AI runs without instantiating CUDA, ROCm, or Metal runtimes. By restricting operations to host vector registers, we guarantee zero impact on vehicle perception safety loops.

Enterprise Solutions

Tailored Deployments Across Heavy Fleet Ecosystems

Specific integration topologies engineered for Tier-1 industrial autonomy programs.

Quarry & Surface Mining Cat Command / FieldAI

Cat Command Haulage Telemetry Reduction

Autonomous 793F/797F haul trucks generate gigabytes per cycle across repetitive quarry paths. QuantAIM deploys at the site transfer depot or within Cat Digital VPCs, filtering out 70%+ of static dust and gravel logs in under 1 hour to feed site-specific Field Foundation Models (FFM).

→ Reduces hot S3 lake intake by 350+ TB per active mine site
Urban Commercial AV Waymo Driver / GCP

Waymo Driver Multi-Sensor Ingestion Filter

Eliminate the cloud compute tax of running multi-node GPU clusters to slice uncurated 29-camera and LiDAR logs. QuantAIM gates nominal highway loops and red-light idling directly in GCP intake buckets, feeding high-entropy corner cases (H ≥ 0.40) directly to world models.

→ Cuts petabyte-scale GPU preprocessing burn before labeling
Constrained Comms Industrial & Ag

Off-Grid Machinery Telemetry Gate

Agricultural tractors and remote hydraulic excavators operating over low-bandwidth satcom links cannot transmit raw sensor feeds. QuantAIM executes on the machine's industrial host CPU, ensuring only true edge anomalies transmit over satellite.

→ 100% elimination of redundant satcom egress bandwidth fees
Air-Gapped Tactical Tactical Defense / Prime

Tactical Unmanned Systems Triage

In electronic warfare or comms-denied environments, QuantAIM operates completely air-gapped under --network none. Automatically indexes mission-critical reconnaissance telemetry directly at the edge without external dependencies.

→ Zero network footprint; zero risk of RF or data leakage
Developer & Security Specifications

Integration Specs & Architectural Targets

Everything systems architects and technical leads need to inspect, verify, and execute.

Deployment Specification // CLI & OCI OCI-COMPLIANT ARTIFACT

Execute directly inside your VPC using Docker, Podman, or containerd. Mounted strictly as read-only (:ro) with complete network isolation:

docker run --network none --read-only \
  --security-opt=no-new-privileges:true \
  -v /mnt/telemetry/raw_uncurated_lake:/input:ro \
  -v /mnt/fast_nvme/quantaim_triage_curated:/output:rw \
  quantaim-core-engine:2026.1 \
  --entropy-threshold 0.40 \
  --max-latency-p95 35ms
Hardware Benchmarks // Empirical Targets 15-DAY EVALUATION SCHEDULE

Our 15-day smoke test validates deterministic performance against strict empirical hardware thresholds:

Section 4.1: Compute Isolation
GPU VRAM Allocation == 0.00 MB
Verified by system nvml/proc hardware counters.
Section 4.2: Payload Reduction
Storage Write Reduction ≥ 70.0%
Nominal frames committed to cold parquet.
Section 4.3: Latency Determinism
p95 Latency < 35 milliseconds
Measured across 100k continuous frame passes.
Section 4.4: Functional Safety
Critical Anomaly Recall == 100.0%
Zero dropped edge events (H ≥ 0.40).
Telemetry Artifact // audit_summary.json SYSTEM AUDIT SPECIFICATION

At completion of the 100k frame triage pass, the runtime automatically emits a cryptographically hashed JSON audit artifact for your DevSecOps pipeline:

{
  "schema_version": "2026.1",
  "dataset_frames_evaluated": 100000,
  "execution_duration_sec": 3252.84,
  "hardware_metrics": {
    "gpu_vram_allocated_mb": 0.00,
    "cpu_simd_instruction_set": "AVX-512_F_BW_DQ",
    "network_egress_bytes": 0
  },
  "triage_summary": {
    "nominal_frames_gated": 72410,
    "high_entropy_anomalies": 27590,
    "payload_write_reduction_pct": 72.41,
    "p95_frame_latency_ms": 28.4
  },
  "acceptance_pass": true
}
Empirical Proof

Hardware-Level Benchmark Results

Audited metrics on 100,000 raw autonomous haulage frames running on standard AMD EPYC 9654 host processors.

0.0 MB
GPU VRAM Allocated
72.4%
Write Reduction
28.4 ms
p95 Frame Latency
100.0%
Safety Anomaly Recall
ROI Evaluation Model

Fleet Ingestion Savings Calculator

Calculate your annual cloud ingestion and compute burn reduction using host SIMD telemetry gating.

Active Autonomous Fleet Size: 250 Machines
Daily Operating Hours / Unit: 16 Hours
Calculation assumes average autonomous multi-sensor telemetry generation rate of 250 GB/hr per machine across Camera, LiDAR, and CAN interfaces.
Projected Annual Telemetry Volume
365.0 Petabytes
QuantAIM 70% In-VPC Purge
255.5 PB Purged
Estimated Annual Cloud & Compute Savings
,132,000 USD
Zero-Risk Empirical Benchmark

Deploy the 15-Day In-VPC Smoke Test

Evaluate QuantAIM on 100,000 uncurated multi-sensor frames inside your private VPC. Governed by empirical hardware criteria.

Institutional Verification

Corporate & Security Clearance

Entity & Lineage
QuantAIM AI Inc.
Atlanta, GA • United States
U.S. Pat. Pend. 64/148,570
Security & Isolation
Air-Gapped Standard
Docker / Podman / OCI Image
ISO 19014 / IEC 61508 Gating Safe
Export & Jurisdiction
EAR99 Classified
Domestic US IP Ownership
100% Founder-Owned Entity
Technical Inquiries
Founder & Architect
raj.dhanak@quantaim.ai