Built for teams

Your team's knowledge.
Available to every AI they use.

Memxus Workforce gives your organization a shared memory layer for Claude, ChatGPT, Cursor and Slack — and any app your team uses that needs to remember (Notion, Linear/Jira, Gmail, Salesforce/HubSpot, Intercom, Zendesk, Google Drive, Confluence, GitHub). Decisions, client context, architecture choices — saved once, recalled by every employee.

10 seats minimum. No credit card required to start.

Memxus Cloud (shared workspace memory)

Decision: Migrate to Postgres in Q3 2026

Saved once — recalled everywhere

Employee A — Slack

@eng: We’re migrating to Postgres in Q3.

Memxus: Saved to workforce memory ✓

Employee B — Claude

Q: What database are we moving to?

A: Based on workspace memory: Postgres in Q3.

Employee C — ChatGPT

Q: Why are we choosing Postgres?

A: Workspace memory: decision for reliability + SQL.

Employee D — Cursor

Suggesting: Postgres connection config

Reason: using workspace memory context.

One shared memory. Every app.

Where MEMXUS sits in your stack

Not another chatbot — the shared layer between your team’s AI tools and the context they need to remember.

Diagram showing team AI tools saving memory through MEMXUS Workforce (remember), cloud storage, and other tools recalling that memory (recall), with dashboard control.

Persistent memory

Cloud memory

Save from anywhere

Claude
ChatGPT
Slack
Cursor
MEMXUS Workforce

Portable team memory layer

MCPAPIOAuth

Recall anywhere

Claude (Employee_B)
Cursor (Employee_C)
Gemini (Employee_D)
remember·recall

Your memories

Persistent · Workspace-isolated · Editable

Dashboard · Notebook

View, edit, delete anytime

Remember (save)
Recall (use elsewhere)

ROI your team can measure.

Shared memory compounds across every developer and every AI tool.

Time savings across the team

150–200 hrs recovered per dev/year

  • 30–45 min/day lost re-explaining context between Claude, ChatGPT, and Cursor
  • With Memxus: ~0 min — context travels with every team member
  • 10 devs → 1,500–2,000 hrs/year; $75,000–$100,000 in recovered time at $50/h

Token savings at scale

Up to 90% fewer tokens

  • Selective, semantic recall vs full-context approaches for the whole team
  • Shared memory means no duplicate context pasted across dozens of daily sessions

Cross-team consistency

40–60% fewer context bugs

  • Fewer bugs from incomplete or inconsistent context between sessions and teammates
  • Architecture decisions and client context stay aligned for every employee

Team onboarding

2–3 days vs 2–4 weeks

  • New members productive from day one via the team memory workspace
  • Conventions, client history, and project decisions available instantly

Without Memxus

6,000 tokens

Each dev pastes the full project brief every session

With Memxus

1,200 tokens

Shared workspace memory recalled on demand

$30/seat/mo — a fraction of what one dev recovers in time alone.

Estimates based on typical team sizes, context sizes, and public list prices. Actual savings depend on headcount, model usage, and how much context your team repeats across tools.

Built for every team that uses AI

Engineering

Architecture decisions that stick. Every dev gets consistent answers from their AI.

Decision: We use tRPC for all API routes.

Sales

Every rep knows every client. Handoffs without losing context.

Acme Corp: decision maker is Sarah Chen (CTO).

Customer Success

Full client history at every touchpoint.

GlobalCo: blocked on SSO — follow up with IT.

Onboarding

New hires productive from day one through their AI tools.

Convention: 2 reviews required on every PR.

Enterprise-grade security

Workspace isolation

Every org’s data completely isolated.

Role-based access

Owner, Admin, Member roles.

Audit logs

Every action logged with user and timestamp.

Encryption

AES-256 at rest. TLS 1.3 in transit.

Simple pricing. No surprises.

$30 / seat / month

Minimum 10 seats · Annual plan $25/seat

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