Compute-every-time baseline
60 model calls / 60 equivalent requests01 Compute Authorization and Governance Engine
The model didn’t stop.
The waste did.
Pulse CAGE — Compute only when it earns authorization.
“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.
02 Side-by-side measured result
Same useful outcomes.
Fewer authorized executions.
model executions avoided
on this local synthetic workloadCAGE governed lane
27 model calls / 60 equivalent requests03 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.
- 01
Identify
Bind the request to tenant, mission, model, version, authority, and policy.
- 02
Evaluate
Determine whether a verified result or artifact remains admissible.
- 03
Decide
Authorize fresh compute, verified reuse, deterministic bypass, or rejection.
- 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.
- Policy result
- All authorization and equivalence bounds satisfied
- Compute disposition
- Prior verified result admitted
- Evidence
- Decision inputs + policy outcome + resource impact
06 NVIDIA local evidence
MEASURED — LOCAL NVIDIA TEST Randomized RTX 3080 inference experiment.
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.
Cepheus-1-108Q
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
- 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- 01Local reproduction
- 02Multi-GPU validation
- 03Millions of shadow decisions
- 041% controlled traffic
- 055–25% rollout
- 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

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
737-781-647211 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.”
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.
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.