About
An AI benchmark for the procurement era.
Built by 珈特科技 in Taipei. Phase 0 dogfood live; Phase 1 (15-model cohort, 3-judge ensemble, 60-task pack) ships Q3 2026.
Why this exists
Most AI benchmarks publish a leaderboard number and ask you to trust it. Some tell you which judge model they used. A handful release the prompts. None — at the time we started — give you a cryptographic chain back from the score on your screen to the bytes the model returned to the bytes we anchored at midnight UTC.
That chain is the only thing a procurement officer can put in a vendor review. So we built it.
Who this is for
- AI infra teams who route between models in production and need to know — without ambiguity — when a silent vendor swap broke their pipeline.
- Enterprise procurement who can no longer rubber-stamp "GPT-5 is better than Claude" without a defensible paper trail.
- Researchers who want to replay a benchmark six months from now and get the same evidence chain, even if the model is deprecated.
Roadmap
Apr 2026
phase 0 · live
Evidence chain end-to-end (R2 + Neon + edge verify) · single-provider smoke baseline
May 2026
phase 0 · scale
繁中 coding pack 60 tasks · daily cron stable · 14-day Merkle streak
Jun 2026
phase 1 · open
3-judge ensemble · 15-model cohort · public leaderboard live · pricing snapshot
Jul 2026
phase 1 · vertical
Silent-update probe public · 繁中 invoice OCR pack · accounting partner samples
Aug 2026
phase 1 · workspace
Tenant-private packs · evidence reports · alert engine · RBAC
Sep 2026
phase 1 · advisor
Routing Advisor · Shadow Simulator · incident attribution
Oct 2026
phase 1 · ga
Cosign + Merkle · Stripe billing · 2-3 paid pilots
The team
Built by 珈特科技 (GetInfo Tech) in Taipei. Same team behind SayVox (real-time voice translation) and GetMSG (enterprise .msg viewer).
Talk to us
If you have a workload you think GetAI should benchmark, write to perry@getinfo.com.tw.
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