Headline Benchmark Results
D1 · MR. ELF Multi-Agent Parallel Eval
5.0×
Speedup vs. Sequential
5 evaluation agents running simultaneously on H100. Latency: 2.505s sequential → 0.501s parallel. All 5 decision agents confirmed active.
D2 · NPP Routing Engine + Fractal Dispatcher
16.7×
Average Speedup · 50 Fractal Agents
50 fractal agents dispatched across 3 scenarios. Stage classification accuracy: 100% (N1/V3/M8 correctly identified). Configurations: N1P3, V3S1, M8S1.
D3 · MOE2M Simulation-Lite Environment
37
Planetary Gaps Identified · Sessions 1–3 Live
Sessions 1–3 running as active constraint environments. AutoDEEM drift detection live with automatic correction routing. Architecture locked.
D1 · Latency Benchmark Data
| Test |
Mode |
Agents |
Latency |
Speedup |
H100 GPUs Active |
Status |
| MR.ELF Baseline |
Sequential |
1 |
2.505s |
1.0× |
1 |
✓ Baseline |
| MR.ELF Parallel v1 |
Parallel |
5 |
0.501s |
5.0× |
5 |
✓ Complete |
| MAVEN eval only |
Parallel |
1 |
0.488s |
5.1× |
1 |
✓ Complete |
| Full 5-agent dispatch |
Parallel |
5 |
0.501s |
5.0× |
8 |
✓ Complete |
| Stress test · 10 runs |
Parallel |
5 |
0.518s avg |
4.8× |
8 |
✓ Complete |
D2 · NPP Routing Engine + Fractal Dispatcher Benchmarks
| Scenario |
Fractal Config |
Agents |
Sequential |
Parallel |
Speedup |
Stage Classified |
Correct |
| Needs Assessment · Governance |
N1P3 |
12 |
8.2s |
0.49s |
16.7× |
N1 · NOTICE |
✓ |
| Concept Vetting · System Build |
V3S1 |
20 |
11.6s |
0.69s |
16.8× |
V3 · VALIDATE |
✓ |
| Financial Management · System |
M8S1 |
18 |
11.0s |
0.66s |
16.7× |
M8 · MEASURE |
✓ |
| Combined Average (50 agents · 3 scenarios) |
50 |
10.3s avg |
0.61s avg |
16.7× |
3/3 correct |
100% |
Sequential (50 agents)
10.3s
Fractal Agent Matrix · 60 Specialist Configurations
NPP Stage (N1–S12) × MR. ELF Agent (MAVEN · REX · ELI · LEX · FLO) = 60 specialist configurations.
Highlighted cells = active in D2 benchmark runs.
Bright = Active in D2 benchmarks · Dim = Available, not yet run
GPU Utilization · 8× H100 80GB HBM3
| Metric |
Value |
Notes |
| Node Configuration |
8× H100 80GB HBM3 |
Brev.dev DGX Cloud instance |
| Total VRAM |
640 GB |
HBM3 confirmed |
| Peak GPU Utilization (D1) |
~82% avg across 5-agent dispatch |
Measured during parallel eval burst |
| Peak GPU Utilization (D2) |
~91% avg across 50-agent fractal run |
Measured during M8S1 scenario |
| VRAM Consumed (D2 peak) |
~186 GB / 640 GB |
29% utilized · headroom for D3 |
| Inter-GPU Communication |
NVLink active |
High-bandwidth agent state sharing |
D2 · Stage Classification Results (100% Accuracy)
Input: "governance gap, compliance rules, needs definition"
N1
NOTICE · Needs Assessment
✓ Correct Classification
12 agents dispatched · N1P3 config · 16.7× speedup
Input: "concept validation, mechanism vetting, system build"
V3
VALIDATE · Concept Vetting
✓ Correct Classification
20 agents dispatched · V3S1 config · 16.8× speedup
Input: "pricing logic, capital structure, revenue model"
M8
MEASURE · Financial Management
✓ Correct Classification
18 agents dispatched · M8S1 config · 16.7× speedup
D3 · MOE2M Simulation-Lite · 12-Session Status
Sessions 1–3 running as active constraint environments with telemetry output. 37 planetary gaps identified across 3 scenarios. AutoDEEM drift detection live with automatic correction routing. Sessions 4–12 build begins Day 25.
SESSION 01
Needs + Governance Constraint
● Live
SESSION 02
Research + Validation Loop
● Live
SESSION 03
Vetting + Drift Detection
● Live
SESSION 04
Empirical Data Simulation
◎ Building
SESSION 05
Legal + Policy Constraint
◎ Building
SESSION 06
Observational Intelligence
◎ Building
SESSION 07
Partnership Ecosystem
— Planned
SESSION 08
Financial Management Sim
— Planned
SESSION 09
Efficiency + Scale
— Planned
SESSION 10
Talent + Capacity Model
— Planned
SESSION 11
Capital Creation + Trade
— Planned
SESSION 12
Sustainability + Legacy
— Planned
D3 Overall ProgressArchitecture locked · Sessions 1–3 live
D1 · Multi-Agent Parallel EvalComplete
D2 · Routing Engine + Fractal DispatcherComplete
Overall Sprint Progress (Day 21/60)35%
60-Day Sprint Timeline · Current Status
Day 11 — May 11, 2026
Node Live + D1 First Benchmark
8× H100 80GB HBM3 confirmed · 640GB VRAM. MR. ELF multi-agent parallel evaluation: 5.0× speedup (2.505s → 0.501s). All 5 decision agents simultaneously active.
✓ Complete
Day 12 — May 12, 2026
D1 + D2 Complete · D3 Architecture Locked
D2: NPP Classifier + Fractal Dispatcher — 50 agents across 3 scenarios, 16.7× average speedup. Correct stage classification N1/V3/M8. Fractal configs N1P3, V3S1, M8S1 validated.
✓ Complete
Days 13–20 — May 13–26, 2026
Phase 2 Foundation · Team Build · Platform Wiring
OfficeBeacon team build in motion. Platform wiring: DEEM Ex, MULTITUDE, AutoDEEM dashboard, Stripe checkout. D3 MOE2M Sessions 1–3 live as constraint environments. 37 planetary gaps identified.
✓ Complete
Day 21 — May 27, 2026 · TODAY
D1 Benchmark Report Delivery to NVIDIA
Quantified H100 utilization, latency benchmarks, throughput data, and fractal agent matrix visualization submitted to NVIDIA Innovation Lab team.
◎ This Report
Days 22–42 — May 28 – Jun 17, 2026
Phase 2 · MOE2M Sessions 4–6 + Fractal Matrix + AutoDEEM Dashboard
Build 5: MOE2M Sessions 4–6 live. Build 6: 60-config fractal agent matrix UI. Build 7: AutoDEEM loan default use case demo. Build 8: DEEM Ex Stripe checkout. Build 9: AutoDEEM drift dashboard full industrial command center.
Phase 2
Days 43–60 — Jun 18 – Jul 05, 2026
Phase 3 · Enterprise Demos + NVIDIA Renewal Brief
3 vertical enterprise demos (lending, smart city, AI factory). MOE2M Sessions 7–12 stub. H100 stress tests. NVIDIA renewal brief with quantified architecture diagrams.
Phase 3
Phase 2 Commitments · Days 22–42
Build 5 · Priority 1
MOE2M Sessions 4–6 Live
Empirical Data, Legal/Policy, and Observational Intelligence sessions as active constraint environments with telemetry output and agent feedback loops.
Due: Day 30 · Jun 05, 2026
Build 6 · Priority 2
Fractal Agent Matrix UI
60-configuration subagent grid (N1–S12 × MAVEN/REX/ELI/LEX/FLO) running on H100. New tab in MR. ELF interface with live dispatch telemetry.
Due: Day 35 · Jun 10, 2026
Build 7 · Priority 3
AutoDEEM Loan Default Demo
Live supervisory demo: drift report generation, FLO/LEX/REX agents in action, NPP mapping dashboard. First enterprise vertical proof point.
Due: Day 38 · Jun 13, 2026
Build 9 · Priority 4
AutoDEEM Industrial Dashboard
Full command center upgrade: amber threat-pulse system, real-time 60-config agent status, NPP heatmap with live drift scoring, correction routing queue.
Due: Day 42 · Jun 17, 2026
DEEM Technologies is building the governance operating system for AI factories.
AutoDEEM is the always-on supervisory layer that detects drift, routes corrections through fractal agents, and preserves institutional memory across every AI workload —
before the model runs, during execution, and after each output.
D1 proves parallel agent execution on H100. D2 proves routing intelligence at scale.
D3 proves simulation governance at planetary scope. This is the architecture NVIDIA needs for AI factory governance.
