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EyesInAI·Loading live benchmark data
That is the operating principle, not a slogan. Every night the bench stress-tests every model we serve; every product on the platform picks up the result the next morning. Nothing here runs on vibes, defaults, or last quarter’s pricing.
Running today
All four are live. Everything below links to the real thing — no mockups, no waitlists.
The measured routing gateway. Every request goes to the least-expensive model that still passes your tasks — measured 7–10× cheaper than routing on autopilot, with a receipt.
A hosted assistant built from your website — bilingual, voice-capable, grounded in your data, behind hard spend caps. Serving costs measured in fractions of a cent per conversation.
Your assistant and its live business data inside Claude Desktop — one scoped, revocable token. The AI you already pay for does the talking; we serve the data.
The measurement loop under it all — nightly stress-tests across every major provider, the public leaderboard, real per-task costs. Not for sale; it is the proof the other three stand on.
Shipping next
The build cadence below is real — check the ship log at the bottom of this page. These are the next moves, in the order the workbench has them.
Your portal shows the receipt — real conversations, real serving cost, and the measured savings versus a fixed premium model. Now it arrives as a monthly statement too: flip the toggle in your portal and the numbers land in your inbox on the 1st of each month, like a utility bill you actually enjoy opening.
Connect puts your business data inside Claude Desktop today — scoped, revocable, audited. The same connector is headed for ChatGPT and Gemini, so whichever AI your team already pays for, your assistant and your live data are in the room. One token system, every desktop.
We tore down the incumbents the way we do everything — by measuring. The teardowns are now live: EyesInAI versus Jotform AI Agents and Retell AI, feature by feature, dollar by dollar, every claim sourced to their own docs. Receipts included — see /compare/jotform and /compare/retell.
Every assistant turn is assembled from things we don’t fully control — what a visitor types, what a document contains, what your corpus holds — and then sent to a model provider. Shieldyard inspects that outgoing prompt first and catches credential-shaped data before it can land in someone else’s logs. It is a per-assistant, layer-by-layer control: each layer switches on independently and starts in watch-only mode, so you can see exactly what it would have caught on your own traffic before it changes a single answer. Pattern matching only — no extra model call, no added cost per turn. When it finds something we record that it happened, never the value itself.
The turn log is becoming a conversation view — every visitor session grouped end-to-end, machine traffic split out from real usage, so "how is my assistant doing?" gets answered with actual conversations, not raw counts. The same honesty we apply to benchmarks, applied to your traffic.
The ship log
Want the numbers behind the badge? The leaderboard rebuilds every night — see today’s run →