Stop guessing before you commit to AI infrastructure.
AI infrastructure decisions — GPU clusters, cloud vs on-prem, 3-year TCO — involve hundreds of millions of dollars and years of lock-in. Oplexa gives you a validated quantitative model for every decision, delivered in 60 seconds. No consultant, no vendor bias, no waiting.
Pick the tool that matches your decision.
Each tool runs a validated quantitative model for a specific infrastructure decision. Submit your parameters — get a board-ready report in 60 seconds. No vendor bias, no consulting markup.
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TIER 1 • LIVE
HBM Fit
Before you lock in your GPU cluster hardware, validate that your HBM bandwidth actually matches your model size, batch configuration, and workload profile. Identifies memory bottlenecks that cost millions to fix post-procurement.
FOR: Hyperscalers Enterprise AI teams
PRICE
$2,500
COMPETITION
None
DEMAND
~4,000/mo
TIER 1 • COMING SOON
AI Cluster TCO
The real cost of a GPU cluster is never just the hardware. Model your full 3-year total cost of ownership — power, cooling, networking, software licensing, support, and depreciation — before procurement decisions are made.
FOR:
Hyperscalers
Enterprise
Investors
PRICE
$10,000
COMPETITION
Weak
DEMAND
~5,500/mo
TIER 1 • COMING SOON
GPU Cloud Build vs Buy
On-premises GPU vs cloud rental is one of the highest-stakes decisions an AI team makes. Get a side-by-side cost comparison with break-even timeline, 3-year cost delta, and utilization sensitivity — not a vendor's estimate.
FOR:
Enterprise AI teams
Investors
PRICE
$15,000
COMPETITION
Vendor
DEMAND
~2,500/mo
TIER 2 • COMING SOON
GPU Power & Cooling Estimator
Model data center power draw, cooling capacity, and PUE efficiency before you sign a colocation or build contract. Identifies costly over/under-provisioning before it's locked into your infrastructure plan.
FOR:
Hyperscalers
Enterprise AI teams
PRICE
$7,500
COMPETITION
Weak
DEMAND
~3,200/mo
TIER 2 • COMING SOON
Inference Cost Optimizer
Compare per-token inference cost across GPU types, cloud providers, and quantization levels. Find the cheapest setup that meets your latency SLA — before you commit to a production architecture.
FOR:
Enterprise AI teams
Investors
PRICE
$5,000
COMPETITION
Moderate
DEMAND
~6,000/mo
TIER 2 • COMING SOON
AI Vendor Lock-in Risk Score
Quantify vendor dependency risk across your AI stack - cloud APIs, proprietary hardware, and model providers. Get a migration cost estimate and diversification roadmap before lock-in becomes a liability.
FOR:
Enterprise AI teams
Investors
PRICE
$8,000
COMPETITION
None
DEMAND
~4,100/mo
From your inputs to a board-ready report.
Every tool follows the same 3-step process — works the same whether you’re validating HBM bandwidth, modeling cluster TCO, or comparing build vs buy.
Enter your parameters
Fill in the structured intake form — model size, cluster configuration, budget constraints, or workload type depending on the tool. No calls, no briefings, no RFPs.
Validated model runs
Our quantitative models run against your exact inputs — bandwidth curves, TCO projections, build vs buy cost deltas. Every assumption is documented. Zero vendor influence.
Act on the report
You receive a structured PDF with charts, sensitivity tables, and a clear decision recommendation — formatted for CFO sign-offs, board presentations, and investment memos.
No vendor bias. No consulting markup. Just numbers.
Oplexa has no hardware partnerships, no upsell agenda, and no interest in steering your decision toward any vendor. Every tool is built on independently validated quantitative models — and every assumption in the report is documented.
Questions before you start?
Everything you need to know before running your first analysis.
It depends on your decision. Validating GPU cluster hardware → HBM Fit. Full 3-year cluster cost → AI Cluster TCO. On-prem vs cloud → GPU Cloud Build vs Buy. Power and cooling sizing → GPU Power & Cooling Estimator. Reducing inference cost → Inference Cost Optimizer. Vendor dependency risk → AI Vendor Lock-in Risk Score. Still unsure? Book a consultation.
Every report includes: an executive summary with a clear decision recommendation, a detailed model output with the numbers behind the recommendation, sensitivity tables showing how the answer changes under different assumptions, and charts formatted for board presentations and investment memos.
GPU Power & Cooling Estimator, Inference Cost Optimizer, and AI Vendor Lock-in Risk Score are currently in model validation. Click 'Join waitlist' on any tool card and you'll be the first to know when they go live. We don't send marketing emails — just a single notification when the tool is ready.
Vendors have hardware to sell — their TCO models are optimized to make their product look favorable. Consultants charge hundreds of thousands and take weeks. Oplexa tools are neutral, quantitative, and deliver in 60 seconds. Every assumption in our models is documented and visible in your report.
Our models are built on publicly validated infrastructure data, real-world GPU benchmark data, and peer-reviewed cost modeling methodologies. Every model assumption is documented in the report — so you can audit every number. We update models when GPU generations, cloud pricing, or infrastructure costs change.
Yes — reports are structured specifically for that purpose. They include executive summaries, sensitivity analysis, and clear recommendations formatted for board consumption. That said, our reports are based on quantitative models and public data and do not constitute investment advice.
Make your next infrastructure decision with data.
Pick the tool that matches your decision. Submit your parameters. Get an institutional-grade report in 60 seconds — and walk into your next meeting with numbers no one can argue with.