Coming soon

Memkist Local.
Your data never leaves.

The whole platform — sync, document intelligence, AI assistant, workflows and AI-client access — running on an appliance inside your own building. For teams whose files are not allowed to leave.

The appliance

One box. The whole system.

Storage, database and compute, preconfigured. Rack it, provision your workspace, and your team syncs, searches and asks — with every byte staying behind your own firewall. A true on-premises AI platform — no cloud, no egress, no compromise. The same discipline as the cloud edition: labels on landing, walls on every read, metered AI, human-approved actions.

That includes the AI boundary: point Memkist Local at your own model endpoint and usage is still metered per purpose and visible in the local console. "On-prem" is not a license to fly blind.

Spec at a glance

DeploymentOn-premises appliance
Data residency100% local · no cloud sync
PlatformSync · Search · AI assistant · Workflows · AI tools
AI modelPrivate endpoint on your network
AccessDesktop · Web · connect your AI apps
AvailabilityComing soon

What stays local

Everything with your name on it.

Fully on-premises

Every byte — storage, parsing, search and agent runs — stays on the appliance, behind your own firewall. Fully air-gapped deployments supported. No egress, no third party in the data path.

Same agent platform

The AI assistant, memory, workflow compiler and MCP server run locally — the same behaviour as the cloud edition, on your hardware.

Private model endpoint

Point the platform at an in-house LLM on your network. AI usage stays metered and auditable, entirely on your infrastructure.

Drop-in appliance

A single box with storage, database and compute preconfigured. Rack it, provision your workspace, start working.

Cloud edition, meanwhile

You don't have to wait.

The cloud edition is the same platform, available today — its per-seat pricing is being finalised and will be published soon. Start in the cloud, move to the appliance when it ships — no rebuild, no re-training, same platform.

Questions about Local?

Residency requirements, hardware sizing, air-gapped deployments, your own model endpoint — write to us and get answers from the people building it.