01 Compute Authorization and Governance Engine

The model didn’t stop.
The waste did.

Pulse CAGE — Compute only when it earns authorization.

LIVE GOVERNANCE DEMONSTRATION
00:30 / SIDE-BY-SIDE

“The widening space between the lines is released compute capacity—and CAGE produces the receipt.”

Read video transcript

Baseline computes every request, so its compute line continues to rise. CAGE governs every request. During authorized exact repeats, the CAGE compute line flattens while useful outcomes continue increasing. Stale artifacts, cross-mission requests, wrong equivalence, and adversarial near-matches are rejected. When reuse is unsafe, CAGE authorizes fresh computation. The widening gap represents released compute capacity, backed by a decision receipt.

01 Fresh computation02 Verified reuse03 Deterministic bypass04 Reject → safe fresh compute

02 Side-by-side measured result

Same useful outcomes.
Fewer authorized executions.

Compute-every-time baseline

60 model calls / 60 equivalent requests
33

model executions avoided

on this local synthetic workload

CAGE governed lane

27 model calls / 60 equivalent requests

03 Why CAGE is not a cache

Reuse is a governed authorization decision—not a lookup shortcut.

Tenant

Mission

Model

Version

Authorization

Freshness

Equivalence

Correctness

Evidence

For each eligible request, CAGE authorizes fresh computation, verified reuse, deterministic bypass, or rejection followed by safe fresh computation.

Every decision produces an auditable evidence record explaining why work was executed, rejected, or safely avoided.

04 Authorization decision flow

Four gates between a request and expensive compute.

  1. 01

    Identify

    Bind the request to tenant, mission, model, version, authority, and policy.

  2. 02

    Evaluate

    Determine whether a verified result or artifact remains admissible.

  3. 03

    Decide

    Authorize fresh compute, verified reuse, deterministic bypass, or rejection.

  4. 04

    Prove

    Issue an auditable evidence record for the decision and resource impact.

05 Adversarial safety demonstration

Attack the reuse boundary.

Select a request condition. CAGE authorizes reuse only for the exact, currently authorized repeat.

DECISION RECEIPTRCPT-EXACT-001
VERIFIED REUSE
Policy result
All authorization and equivalence bounds satisfied
Compute disposition
Prior verified result admitted
Evidence
Decision inputs + policy outcome + resource impact
False reuse 0Stale reuse 0Cross-tenant reuse 0Invalid output 0

06 NVIDIA local evidence

MEASURED — LOCAL NVIDIA TEST Randomized RTX 3080 inference experiment.

120Total requests
60 / 60Equivalent requests per lane
60 → 27Baseline → governed model calls
55%Avoidance on repeat-heavy test
28.293sActive inference avoided
0.514 WhAllocated measured GPU-energy difference

False reuse 0

Stale reuse 0

Cross-mission reuse 0

Undetected invalid outputs 0

07 Physical-QPU evidence

MEASURED — PHYSICAL-QPU RUN Governed execution on a physical Rigetti QPU through Amazon Braket.

This is physical-QPU evidence. It is separate from the local NVIDIA GPU experiment.

Physical systemRigetti
Cepheus-1-108Q
Execution pathAmazon Braket
Physical-QPU tasks13
Shots executed12,416
Net shots avoided1,920
Net QPU jobs avoided1

False reuse 0

Stale reuse 0

Cross-mission reuse 0

Undetected invalid results 0

08 Scale scenario calculator

Model a projected scenario.
Do not mistake it for measured savings.

Each independently verified 1% avoidance rate represents 10 million potentially avoided executions for every one billion requests.

PROJECTED SCENARIO — NOT REALIZED SAVINGS

Net projected value$0
Annual executions avoided
0
Released GPU-hours
0
Equivalent continuous GPU capacity
0
Gross capacity value
$0
CAGE overhead
$0
Estimated GPU energy difference
0 kWh

Net verified savings = avoided GPU-hours × loaded GPU-hour cost + avoided energy × electricity rate − CAGE compute − registry/storage cost − verification cost − operating cost.

Energy is a projected device-only extrapolation using the local allocated ratio of 0.514 Wh per 28.293 active inference seconds. It excludes facility energy, cooling, PUE, WUE, water, and deferred hardware.

09 Shadow-mode pilot

Prove it without risking customer output.

CAGE proposes decisions but does not control output. Every proposed reuse is compared against a fresh execution.

Traffic assignment is independent of CAGE. Both lanes use equivalent models, hardware, concurrency, prompt distributions, timing, and service-level objectives.

Request a 60-Day Pilot
  1. 01Local reproduction
  2. 02Multi-GPU validation
  3. 03Millions of shadow decisions
  4. 041% controlled traffic
  5. 055–25% rollout
  6. 06Facility telemetry reconciliation

Pilot pass requirements

  • Zero cross-tenant reuse
  • Zero stale reuse
  • Zero undetected invalid output
  • Statistically bounded false-reuse risk
  • At least 99.9% meeting baseline quality policy
  • Positive net savings after CAGE overhead
  • No unacceptable p95 or p99 regression
  • Independently verified hashes and telemetry
Dustin Cummings, Founder of Pulse AI Technologies LLC

10 Founder

“Pulse exists to make compute accountable: authorize necessary work, safely reuse verified work, and preserve evidence for every decision.”

Dustin Cummings — Founder, Pulse AI Technologies

737-781-6472

11 Protected architecture

Measurable outside.
Protected inside.

“Pulse shares measurable behavior, experimental methods, claim boundaries, and evidence verification. Proprietary policy implementation, reuse-key construction, authorization internals, credentials, and private source code are disclosed only under an appropriate confidentiality agreement.”

Source codeInternal algorithmsReuse-key constructionCredentialsRaw private evidencePolicy internalsPrivate architecture diagramsAccount informationCustomer data

12 Contact and strategic evaluation

Request a governed avoided-compute evaluation.

Bring a frozen, representative workload. Pulse will measure the opportunity, attack the reuse boundaries, account for its own overhead, and return a hash-verifiable stop/go verdict.

Review the Evidence Call the Founder

FORM 01

Request a 60-Day Shadow-Mode Pilot

13 Claims and limitations

Evidence first. Boundaries always visible.

Local GPU results are from a small synthetic RTX 3080 experiment and are not production savings predictions.

Physical-QPU results came from Rigetti Cepheus-1-108Q tasks executed through Amazon Braket and are not NVIDIA GPU evidence.

Scenario calculator outputs are projections, not measured savings. Production claims require controlled shadow-mode validation.

Experiments used local NVIDIA hardware and a physical Rigetti QPU through Amazon Braket. No partnership or endorsement is claimed or implied.