Mission Control for AI Agent Fleets

X-ray vision across your AI fleet

Observe. Persist. Command.

Named after the Norse god of wisdom, Mimir gives you fleet snapshots, memory diffs, session continuity, and cross-pollination reports. Built on OpenClaw. Proven in production.

Start with a Fleet Snapshot See the Proof

Proven in production managing a 4-agent fleet • Born from real operations, not a whiteboard • Open source core

The problems we solve

Real pain points from managing real AI fleets.

One agent discovers a breakthrough—it never reaches the rest

Knowledge stays siloed. No way to compare what agents know or surface cross-pollination opportunities.

Every new conversation starts from zero

Context evaporates. No handoff between sessions. Re-explain the same thing every time.

Scattered dashboards, no single source of truth

No unified view of agent health, memory, skills, or config. No way to compare across the fleet.

Three products. One platform.

Observatory. Session Continuity. Fleet Dashboard.

AVAILABLE NOW

Agent Observatory

"X-ray vision across your AI fleet"

✓ Fleet Snapshots — compare memory, skills, config, health
✓ Memory Diff, Skill Diff, Config Diff
✓ Cross-Pollination Reports — what agents can learn from each other
✓ Transfer Queue with approval workflow

AVAILABLE NOW

Session Continuity

"The save game button for AI work"

✓ Structured handoffs — never lose context
✓ Active work queues
✓ Resurfacing via daily reports, Telegram, cron
✓ Zero re-explanation

COMING Q2 2026

Fleet Dashboard

"Your cockpit for managing AI agents"

→ Visual Kanban for task management
→ Agent health cards, status, maturity scoring
→ Cost trends and ROI analytics
→ Transfer approval workflow

The "holy shit" moment

February 9, 2026. One command revealed gaps we didn't know existed.

What we found:

6.8×

Memory gap between agents

michaels-assistant: 244 files (66MB) vs devops: 36 files (268KB)

⚠️

Critical config gap

Missing memoryFlush causing context loss in devops agent

🔌

Missing plugin since Feb 4

memory-core plugin absent from devops — no wonder handoffs were failing

Cross-pollination opportunities

Skills and memory from michaels-assistant that could benefit the entire fleet

Time to discovery: 2 minutes

Time to fix: 8 minutes

Command: bash fleet-snapshot.sh

# Fleet Snapshot Output (excerpt)

michaels-assistant
  Memory: 244 files, 66MB
  Skills: 22 active
  Config: memoryFlush=true, memory-core=enabled
  Status: ✓ healthy

devops
  Memory: 36 files, 268KB  ⚠️ 6.8× less than fleet median
  Skills: 21 active
  Config: memoryFlush=missing, memory-core=disabled since Feb 4
  Status: ⚠️ degraded

# Cross-pollination opportunities:
→ Transfer 10 procedural memories from michaels-assistant
→ Sync memoryFlush config
→ Re-enable memory-core plugin
        

This discovery led to the product. From operational problem to deployed solution in ~2.5 hours. Born from the loop: Operate → Discover → Build → Ship.

How Mimir works

CLI-first. One command. Instant clarity.

Snapshot

Collect from every agent

Diff

Memory, skills, config

Analyze

Find gaps & opportunities

Transfer

Approve & propagate

Improve

Fleet gets smarter

Why Mimir?

Different from LLM observability. Different from manual management.

Capability	Mimir	Manual Management	LLM Tools (LangSmith, Helicone)
Fleet-wide comparison	✓ One command	Manual, time-consuming	—
Memory & skill diffs	✓ Built-in	Impossible at scale	—
Cross-pollination reports	✓ Automatic	—	—
Session continuity	✓ Structured handoffs	Copy-paste chaos	—
Trace LLM calls	Coming soon	—	✓
Built for agent platforms	✓ OpenClaw native	—	Framework-agnostic

Start free. Scale when ready.

Open source core. No credit card required.

Free

Open source CLI

✓ Fleet Snapshots
✓ Memory, Skill, Config Diffs
✓ Cross-Pollination Reports
✓ Session Continuity (basic)
✓ CLI tools

View on GitHub

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Team

Custom

For teams managing fleets

✓ Everything in Free
✓ Fleet Dashboard (Q2 2026)
✓ Team collaboration
✓ Advanced analytics
✓ Priority support

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Enterprise