For research labs & universities
Every prompt your lab sends a hosted model is a data point about what your lab is working on. Noolog puts frontier-grade reasoning on hardware you own — so the result stays yours until you decide to publish it.
OpenAI announced that an internal model produced a finite-time singularity proof for the 3-D Navier–Stokes equations — a Millennium Prize problem. NYU mathematician Tristan Buckmaster then said publicly that he and a collaborator had been working the same direction, that their unpublished material had passed through OpenAI's Codex, and asked whether that usage steered the lab's push.
OpenAI said its researchers and agents "did not see any of their work through any means until they released it publicly" — and, in the same statement: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models."
OpenAI statement, 8 September 2026, as reported by VentureBeat, TechCrunch and MIT Technology Review. Buckmaster himself: "I do not know whether our data was used." Twenty-five Fields Medalists have since signed an open letter on attribution.Whatever the outcome of that dispute, the terms of the deal are now written down: the sharpest reasoning on the market, and your research direction as the price. A lab cannot un-send a prompt. It can stop sending them.
One open model on one GPU is not a substitute for a frontier lab. Several of them, fused, is. Noolog runs open models on your own hardware, has them read and score each other's answers, and hands you the one that survived — with the objections kept on record.
Same models, alone vs. fused: a 50% baseline pushed to 80% — arXiv 2601.16863, peer-reviewed.
A single model gives you one answer and a confident tone. A fused mind gives you the spread: how much the minds agree, which claim each of them contested, and who changed position after reading whom. For research that is the signal — the disagreement is where the open problem is.
The record is tamper-evident by construction. When priority is argued, you hold the receipts.
How the root of trust works →Most groups do not have a sysadmin with GPU time on their hands. Peeramid Labs — the team behind Noolog — takes the whole thing from a quote to a running box in your server room, and trains your group to use it.
Which workloads, which models, what must never leave the network. A one-page plan your grant office can read.
We spec and source the hardware — consumer GPUs where they suffice, enterprise where they do not — and handle the paperwork.
Noolog, the models, your identity provider and your tools — Lean, Jupyter, the HPC queue — wired in on site.
Onboarding for the group, a tuned mind for your field, and support after handover. You own the box and the keys.
Own the hardware and there is no per-seat fee, no metered inference, and no one upstream reading the prompts.
Talk to Peeramid Labs →