Standing AI teams that run whole business functions around the clock
Agent optimization layer that automatically optimizes agent workloads to extend context windows and reduce costs
Stage
Not given
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Founded
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Based in
NZ
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Pricing model
Freemium
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Pricing
Free: 200 turns, 1 running team, up to 5 agents. Pay as you go: US$20 buys 2,000 turns. Starter: US$29/month with 2 running teams, up to 15 agents, 5,800 agent turns monthly. Business: US$99/month with 5 running teams, up to 50 agents, 19,800 agent turns monthly. Company: US$399/month with 20 runnin
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Key features
Shadow mode for verification before live operation
Learns from documents, help centres and past tickets
Hard spending caps per team and job
Works with 102+ integrations
Kill switch to stop any team
Approval workflows for risky actions
Team memory and learning across jobs
MCP server and REST API for AI agents
Encrypted credential storage per connection
26+ ready-made teams for different functions
Automatically removes redundant and stale context from agent workflows in real time
Reduces token usage by 37–67% across agent workloads
Maintains baseline pass rates and success rates without code changes
Extends context windows for longer-running workflows
Zero code changes required for integration
Continually monitors and learns agent workloads
What makes it different
Teams learn from your actual business documents and past work, not generic templates
Shadow mode proves capability before autonomous operation
You bring your own model key and pay providers directly, no markup
Jugg.ai
Induction