U.S. Patent No. 12,293,359

The Window Is Open

Five structural forces are converging in 2026. Centralized infrastructure can't scale fast enough. DePIN networks aren't enterprise-ready. The market needs a hybrid platform built for this exact moment.

$254B
AI Inference Market by 2030
~50%
Cost Reduction vs. Cloud
$1.2T
Cumulative TAM (2025–2030)
01 — The Moment

Five Structural Forces
Converging in 2026

This isn't a prediction — these forces are already measurable. Each one alone creates opportunity. Together, they create inevitability.

Force 01
Inference Dominance
AI inference now accounts for 80–90% of an AI model's total cost of ownership. Training is a one-time expense. Inference is the recurring operational cost that scales with every user, every query, every decision. By 2027, inference overtakes training as the dominant AI workload.
$106B → $254B by 2030
Force 02
The Budget-Breaking Problem
Enterprises worldwide are discovering they can afford to build AI models but cannot afford to run them. AWS, GCP, and Azure pricing has created a crisis where inference costs stifle innovation. Google itself branded 2025 "the age of inference" — acknowledging the problem their own pricing helped create.
80–90% of TCO = Inference
Force 03
Power Grid Bottleneck
Data center electricity demand doubles from 448 TWh to 980 TWh by 2030. In Virginia, data centers already consume 26% of grid capacity. New hyperscale facilities take 3–5 years to build. The grid cannot be expanded fast enough — the physical constraint is non-negotiable.
100+ GW gap by 2030
Force 04
Connectivity Explosion
Data center bandwidth surged 330% from 2020–2024. 35 billion connected devices by 2030, with projections of 2–5 trillion AI agents by 2036. Every AI inference request requires network bandwidth — the connectivity layer is the invisible multiplier behind every other demand curve.
330% bandwidth surge
Force 05
Ease-of-Use Drives Adoption
AI adoption isn't driven by LLM chat interfaces — it's driven by simple, shareable experiences. South Korea's adoption surge was triggered by viral image generation, not enterprise deployments. Conversational interfaces that "just work" will steepen the adoption curve faster than any infrastructure investment.
~17% → 30%+ adoption incoming
02 — The Incumbent Problem

Why Clouds and DePINs
Can't Solve This Alone

The market sits between two broken models. Public clouds are too expensive. DePIN networks aren't enterprise-ready. Neither serves the full stack.

Public Cloud
AWS / GCP / Azure
Budget-breaking inference costs and inefficient bundled pricing penalize optimization.
  • VRAM bundled with compute — pay for 80GB even if you need 20GB
  • Inference is 80–90% of TCO — costs scale linearly with every user
  • No edge presence — 50–200ms cloud round-trip latency
  • 3–5 year facility build times can't match demand growth
DePIN Networks
Render / Vast.ai
GPU-only focus, volatile token payments, and no enterprise billing create adoption barriers.
  • GPU-only — no integrated edge, WiFi, connectivity, or storage
  • Volatile token payments — non-starter for enterprise CFOs
  • Incentivize hardware quantity over quality of service
  • No hybrid compute — can't orchestrate cloud + edge workloads
RevoFi
The Financially Intelligent Cloud
Purpose-built to sit between both — enterprise-grade reliability at distributed economics.
  • Unbundles VRAM — per-GB-second billing rewards efficiency
  • ~50% cheaper than AWS at baseline for inference
  • Stable RDC billing (not volatile tokens) for enterprise adoption
  • Hybrid compute: A100 server + 1,000+ Jetson edge fleet
AI Inference Market Trajectory
The market RevoFi is built to capture — $106B → $254B by 2030
Competitive Positioning
RevoFi bridges the gap between cloud reliability and distributed economics
03 — The RevoFi Answer

Three Pillars of
Competitive Moat

Any competitor can buy A100s and Jetsons. RevoFi's advantage isn't hardware — it's the architecture, the billing model, and the IP that makes it all work together.

🛡️
Granted U.S. Patent
U.S. Patent No. 12,293,359 covers the core architecture — not pending, not applied, granted. Continuation claims in process covering six additional claim sets extending protection through ~2042.
Patent #12,293,359
⚡
VRAM Unbundling
The world's first WaaS provider to unbundle GPU compute (FLOPS) from GPU memory (VRAM). Per-GB-second billing rewards developers who build efficient, quantized models — the opposite of every cloud and DePIN competitor.
~50% Below AWS
🔀
Hybrid Compute Continuum
The "Jetson-Triton Compute Continuum" — far-edge devices (1,000+ Jetsons) orchestrated with near-edge compute (A100 server). Neither cloud-only nor device-only competitors can serve the full workload spectrum.
Edge + Cloud

The Defensible Position

RevoFi's moat is not any single feature — it's the integration of all three. A patented architecture that unbundles VRAM for transparent per-second billing, orchestrated across a hybrid compute fleet that spans from local edge devices to centralized A100 inference. No incumbent has this combination. No DePIN competitor has approached this level of enterprise-grade billing sophistication.

The team's deep expertise in the NVIDIA stack — Triton, TensorRT, DeepStream — and proven solutions to complex problems like N-to-1 gRPC connection scaling makes this a technical moat reinforced by operational expertise that cannot be replicated by simply purchasing hardware.

04 — Market Sizing

The $1.2 Trillion
Opportunity

RevoFi's addressable market spans Edge AI Inference, Enterprise WiFi, DePIN services, and AI Retail Computer Vision. Cumulative 2025–2030 TAM exceeds $1.2 trillion.

TAM / SAM / SOM — Cumulative 2025–2030
Total Addressable Market
$1.2T
Edge AI $300B + Enterprise WiFi $200B + DePIN $600B + AI Retail CV $60B
Serviceable Addressable Market
$360B
Edge AI $90B + Enterprise WiFi $60B + DePIN $180B + AI Retail CV $18B
Serviceable Obtainable Market
$1.35B
0.75% initial capture of SAM, scaling to 2–3% by 2030. Edge AI $675M + Enterprise WiFi $450M + DePIN $1.35B + AI Retail CV $135M
05 — Why 2026

The Timing Advantage

The market is no longer hypothetical. It is mature, funded, and actively searching for the exact solution RevoFi is building.

💰
Billions in VC Flowing to Edge AI
In 2024–2025, billions in venture capital have been raised by startups specializing in ultra-low-power edge AI solutions. The investment thesis is validated by capital markets — not just by analysts.
🏢
Enterprises Actively Seeking Alternatives
Enterprises are experiencing "budget-breaking" inference costs in production. They're past the pilot phase and actively searching for cost-effective, specialized hybrid platforms — exactly what RevoFi provides.
⚡
DePIN Infrastructure Is Maturing
Messari projects the DePIN sector at $3.5 trillion potential by 2028. The rails for decentralized infrastructure are being built now — and RevoFi has the enterprise-grade approach others lack.
🧠
AI Adoption Is at the Knee of the Curve
Global consumer AI adoption sits at ~17%. When adoption grows from 17% to just 30% — still under half the UAE's rate — inference demand roughly doubles. Every percentage point compounds through every cascade layer.
06 — Traction

Built, Not Promised

This isn't a whitepaper and a roadmap. Hardware exists. Patents are granted. Revenue flows. Partners are signed.

Granted
U.S. Patent
No. 12,293,359
$2M+
NVIDIA Hardware
Inventory
$1M
Signed Cluster
Purchase Orders
500+
MSP Agreement
Pipeline
37
Ecosystem
Services
8× A100
80GB GPUs Active
(G292 Server)
$3.64M
Y1 ARR
Target
5
Named Channel
Partners
10
Industry
Verticals

Active Partners

Tri-Fi / 100Zero · Interchain Live · GivBux · Tekari UK · Aacadia Payments  |  Collaborations: NVIDIA · Vantiq · Chainlink

The Data Proves the Gap.
RevoFi Fills It.

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