Drop a developer's proposal in. Get an independent first-principles engineering review back, with claim-vs-reality deltas across power, cooling, schedule, cost, and regulatory.
Your uploaded proposal is held in memory only during the review run. The source document is discarded once the report is generated. Only the parsed parameters and resulting report are persisted.
No tooling to learn. No team to onboard. The output is what your internal engineering team would produce, in the time it takes to read a memo.
PDF, DOCX, PPTX, email thread, photo, or URL. The parser handles RFP responses, BOD attachments, and one-page pitches alike.
⏱ 5 secOne question at a time. Big fonts, plain English. Pre-filled from the proposal — change anything, skip what's right.
⏱ 30 secSame first-principles engine that ships hyperscaler-grade engineering. Cross-checked against current commodity lead times and ISO queue data.
⏱ 90 secOne-page exec summary, twelve-section detail, public URL, PDF, embeddable widget. Forward to your VP. Or keep it private.
⏱ InstantIf you sign LOIs, evaluate developer proposals, or sit on a procurement committee, this is for you.
Internal engineering is overwhelmed. McKinsey takes 8 weeks. You're forced to evaluate the rest on developer reputation and gut feel.
Customers want commitments now. You don't have an in-house engineering team the size of AWS's.
CoreWeave, Microsoft, and a sovereign cloud all sent proposals for your next training run. Compare them with credible engineering math, this week.
Mandate from the head of state. Public scrutiny. Western consultants flown in at extreme expense. You need a defensible engineering plan you own.
Building owned AI capacity in a vendor ecosystem you don't natively understand.
The faster you can de-risk a proposal for them, the more often they call you back — and the more deals you close.
Every finding traces to a specific engineering reference. The methodology is published, versioned, and revisable. We tell you when we're confident — and when we're not.
Read the full methodology →Yes — for AI data center buyers, forever. Capacity planners at hyperscalers, neocloud founders, AI-lab infra leads, sovereign program directors, and enterprise AI teams use Livio Grid Review at no cost. We fund the engine via the supply side: developers, EPCs, and brokers pay for downstream Grid features.
Run as many reviews as you want. No cap. No credit card.
By default, your uploaded document is held in memory only for the duration of the review run. The source document is discarded once the report is generated; the report itself stores parsed parameters, not the source text. No login, no email collection, no tracking.
If you want a public share link, you opt in. If you want to delete the report after 30 days, there's a toggle for that.
Every numeric finding is paired with a confidence interval. When site-specific data is sparse, the engine surfaces a range and a "verify with utility" flag rather than a confident wrong answer. Every finding traces to a specific NEC / NFPA / IBC / ASHRAE reference.
No engineering tool is final-word. Grid is your fast first pass — your engineers should still apply local knowledge to refine.
Only if you share it with them. Reviews default to private — a public share URL is opt-in. If you do share with the developer, the report becomes a productive starting point for a v2 conversation: they can submit a revised proposal directly to the same review URL, and Grid will produce a v1-vs-v2 delta automatically.
Yes — that's grid.golivio.com/buyers. Author your spec once, distribute it to your developer and broker shortlist, get bids back scored against your baseline.
No signup. No payment. No saved data unless you ask.
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