Inference Efficiency Control Plane
AI Infrastructure
Fully Realized
TAEON is a software layer that maximizes the efficiency of your GPUs. No model changes. No API changes. No new hardware.
Full stack, all levers on. Latest measured result on H200 NVL.
The problem
Datacenters Have The Silicon
But The Control Layer Is Missing.
GPUs are tuned for peak throughput, but real inference traffic is bursty — they burn near-peak power for a fraction of the useful work. The result: 30–50% of the watts a GPU draws during inference produce zero additional tokens.
Static power management
Slurm, BCM and DCGM set one power limit at job submission and hold it. No notion of prefill versus decode, no online learning, no thermal foresight. Operators pick conservative defaults — and everyone pays for the headroom.
Phase-blind execution
Inference has two opposite phases: prefill is compute-heavy, decode is memory-bound. GPUs run both at the same clocks, so decode pays for compute it never uses. The control layer has no idea which phase it is serving.
Repeated work, repeated cost
Deterministic chat, FAQ traffic and RAG with shared system prompts hit the GPU with the same questions again and again. Out-of-the-box serving has no output cache, no in-flight dedup, no awareness that the answer already exists.
The Hidden Cost
AI Growth Comes At A Cost
TAEON Solves This Problem
The product
A stack of compounding efficiency levers.
Each lever is a product on its own. Each is config-driven and opt-in. Together they're a platform — and they stack multiplicatively.
Power Governor
Physics-based clock and power control that finds and holds the efficiency knee per GPU, model and load. Safe, Balanced and Batch modes — you pick the operating point.
Smart Routing
Classifies every request by phase shape and routes prefill-heavy and decode-heavy traffic to separately-tuned inference pools. Each pool runs at its own efficiency knee.
Output Caching
Caches deterministic completions keyed by request hash, with per-tenant isolation, TTL, byte-LRU and disk snapshot. Multiplies the whole stack on repeated queries.
Off-peak Shaping
A time-of-day knob that relaxes the throughput-floor SLA during quiet hours so the governor can reach deeper efficiency knees. Configurable and daemon-native, per tenant.
Predictive max_tokens
Callers ship oversized max_tokens while real outputs are short. A per-tenant rolling-quantile predictor caps the over-specification, freeing KV-cache slots and admitting more concurrent decoders.
TAEON Pro — full stack
Every lever on, compounded under the always-win guards. The headline result: a measured efficiency and throughput gain that no single lever reaches alone.
How it works
Physics-based control, not guesswork.
An eight-layer pipeline turns raw telemetry into a continuously-optimal operating point — anticipating thermal state & energy inefficiencies instead of reacting to them.
Physics-Based
An RC thermal model and predictive controller anticipate the GPU's thermal state rather than reacting to it — the difference between a thermostat and an autopilot.
Online Learning
The efficiency knee drifts with model, batch size and temperature. TAEON climbs to it continuously and caches the answer, so every new customer starts near-optimal on day one.
Patented Core
The runtime calibration and predictive power/clock control method — identifying thermal parameters during live operation with no offline procedure
Proof
Results across the hardware that matters.
Tokens-per-joule gain holds across every vendor, generation and model we have tested. Power-Governor-only baseline; the full stack compounds on top.
Datacenter Results
- tok/s held · < 0.3% drift
- 0 thermal-throttle events
- 0 failed interventions
Testing methodology
Alternating-block A/B to remove measurement bias from every reported number.
The economics
You keep most of the value TAEON creates.
Pricing is a fraction of the value created per GPU. For a single H200-class GPU, the recurring value dwarfs the price — and it scales with your fleet.
Energy saved
20–35% of inference electricity becomes recurring, measurable opex savings — directly on the line item that hurts most.
Capacity unlocked
+23% throughput is roughly one extra GPU of capacity for every four you own — at near-zero marginal cost, when you can't get more megawatts.
Sustainability
Lower kWh and water per token — an increasingly hard procurement criterion, and one you can report with measured numbers.
The team
Executive Team
A small, focused team with deep systems and inference expertise.
Gene Swank
CEO
Gene spent 15 years as a software engineer and CTO in the high tech space before turning founder. A serial entrepreneur and international best-selling author, he has bootstrapped ventures from inception to global powerhouses and scaled startup studio Propellant Labs past $200M in portfolio value. At TAEON, he pairs that systems depth with proven company-building.
LinkedIn →
David Dowling
COO
Former CMO of a $100M business and Head of Business Development at a startup that went public at $1B+. Faculty at UCLA Anderson. Co-founder of Propellant Labs, a global startup accelerator. David brings the commercial pattern recognition to take TAEON from validated technology to paying customers.
LinkedIn →Your Hardware, Your Workload
Schedule A Pilot
We run a A/B benchmark on your own GPUs and hand you the measured gain