Local, encrypted, deterministic job memory — for professionals and the agents you build
startup teams · dev squads · project managers · consultants · agencies · freelance duos
Give your team a single, encrypted, on-premise memory layer — shared across AI clients, indexed deterministically, with per-person access control. No cloud sync. No vendor lock-in.
Your team's secrets stay on your infrastructure. Ghampus watches shared memory grow, walks the playbooks you trained together, and checks in before anyone had to ask. Activity → Skill runs lets leads see paused multi-step SOP progress; proactive skill-dispatch matches overnight context to trained triggers. Surfaces collaborator writes on editor shares; per-step model routing standardises on the cheapest model that meets each step.
Every architecture decision, product call, or client agreement is stored once and recalled by any team member's AI — with full provenance.
Ingest meeting notes, action items, and retrospective outputs. Ask "what did we decide about the auth layer in Q3?" and get the exact answer.
Slack threads, GitHub ADRs, Jira tickets, and Confluence pages all feed one shared memory. Your AI already knows the full context before you ask.
Consultants and agencies keep a separate engram per client. Switch projects and your AI knows the right context immediately.
The core feature for teams: generate scoped bearer tokens (editor for contributors, viewer for stakeholders) scoped to specific engrams. Each teammate connects their own AI client with their token — full access to shared memory, zero access to anything outside their scope. The Team Admin panel shows live active sessions per token.
Teams tier unlocks shared engrams, the Team Admin panel, Autonomous Skills & SOPs for onboarding, Job Memory Kits for fast setup, and the Memory Studio graph view. Everything a growing team needs to work smarter with AI.
See plans →Looking for the full picture — all use cases, how it works, AI clients, privacy details, and more?
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