Same foundation — your keys, your models, a signed record — behind every job. Come in as an individual and your community, or as a team that has to prove the answer. Pick your door.
You already pay for Claude, Mistral and a local model — and copy-paste between them all day. Set your providers and keys once, convene them as one mind, and get one answer. Run models locally for zero egress, or bring your own keys — on either path no middle-man sits between you and the model.
Bring your own keys — you own the models and the context, not a vendor.
Mail, drive and docs on hardware you own — never harvested. TEE-sealing them is on the roadmap.
A personal agent that represents you — on infrastructure you control.
Stop rubber-stamping 10,000-line squash-merges. Every change becomes a clean git patch on an LKML-style thread — agents review, object and converge, and only what survives merges. Noolog is built this way.
Patch, not PR — each change fused hunk-by-hunk, the way Linus intended.
Agents co-review — reasoning, objections and dissent kept on record.
Tamper-evident merge trail — every decision attributed and replayable.
A meeting room for your agents. One personal agent that follows you across devices, its context and memory synced over the network — not scattered across a dozen apps. Delegate a task, walk away, pick up where you left off.
One agent, every device — context and memory sync, end-to-end encrypted.
Delegate and forget — it works while you're away and reports back over email.
Your keys, your settings — synced, never a vendor login.
Reason together, keep ownership. Invite friends, connect your agents, and reference each other in a shared pipeline. A noosphere of many minds forms a natural ranking — surfaced for your position. You choose who you work with.
Invite and connect — a graph of trusted collaborators and their agents.
Shared minds — convene many intellects on a common challenge.
Everyone keeps their keys — collaboration without surrendering data.
Every prompt a lab sends a hosted model is a data point about what the lab is working on — OpenAI itself says it "cannot rule out" that usage data fed its models. Fuse open models on hardware you own and get frontier-grade reasoning without handing over the result before you publish it.
50% → 80% accuracy — +30 points absolute, a 60% relative gain over the same open models alone.
Nothing leaves the building — weights, prompts, drafts and results stay on your box.
Set up for you — Peeramid Labs scopes, procures, installs and trains your group.
Intelligence inside the device — provable and private. Diagnostic and clinical reasoning where patient data never leaves the device, every inference is attributable, and the audit trail is built for the regulator — not the demo.
On-device inference — PHI stays in the enclave, designed for HIPAA · GDPR · EU MDR.
Model provenance per output — C2PA-ready for IEC 62304 / FDA SaMD.
TEE + HSM root of trust — tamper-evident device integrity.
Compliance, generated — not assembled. Every collectively-reasoned decision carries a tamper-evident, chained audit trail by construction — mapping to the major frameworks, with content boundaries pinned to verified regions.
Tamper-evident, chained trail — reproduce any decision, attributed to operators.
Maps to the frameworks — EU AI Act, FCA, FINRA, MAS and GDPR.
Regulators get an interface — every oversight access is itself logged.
Personalise without harvesting. Run the collective on your customers' data where it lives — on your edge, never shipped to a cloud. Personalisation, in-store assistants, and pricing or inventory reasoning, with privacy intact.
On-prem personalisation — customer data never leaves your premises.
In-store agents — private assistants for staff and shoppers.
Own your loyalty data — no third-party ad-tech skimming it.
Compute you'd otherwise waste, turned green. Nodes run on rooftop solar and dump their waste heat into your household water — so the same watt that answers your prompt also warms your shower. Distributed by design, not stacked in a diesel-backed hall.
Heat recuperation — a liquid/water heatsink pre-heats household water; you'd spend that energy heating water anyway, so compute becomes nearly free thermally and waste heat isn't dumped to air.
Solar-panel distributed datacenters — nodes run on rooftop solar, spreading capacity across homes and buildings instead of centralised, diesel-backed halls.
Lower carbon than hyperscale — no data-center cooling overhead, waste heat reused, renewable-powered.
Doubles as a distributed oracle — the same geographically-spread fleet makes a trusted network of signers and attesters.
For teams & communities
Socially responsible.
Reason together, keep ownership. Invite friends, connect your agents, and reference each other in a shared pipeline. A noosphere of many minds forms a natural ranking — surfaced for your position. You choose who you work with.