The agent-native Growth OS that turns your AI agent into a disciplined growth hacker
Stage
Startup
Not given
Founded
Not given
Not given
Based in
US
US
Pricing model
Paid
Not given
Pricing
Free 100M tokens for new users. $0.04 per 1M tokens for input tokens.
Free: 1 member, 1 project, unlimited free contributors and viewers. Solo: $19.90/month for 1 member with unlimited projects. Team: $39/month for up to 3 members, then $10/month per extra member, with unlimited projects and private projects.
Key features
384K token context window
Multimodal input support
100K tokens processed in less than a second
Structured output for direct code use
Subquadratic Sparse Attention algorithm for efficient compute
$0.04 per 1M tokens pricing
Customer content not used for model training
Data retention limited to 60 days
Complete experiment backlog with candidate ideas
Status tracking from idea to outcome
Shared experiment learnings across team and agents
ICE, PIE, RICE scoring frameworks with voting
Enforced experiment stages with mandatory results and learnings
MCP server for AI agent read and write access
Skills that teach agents the methodology
Plugin for Claude Code and Codex
Web app for team review and collaboration
OAuth security with granular permissions
What makes it different
First long-context decision model purpose-built for enterprise work
Frontier-level decision-making performance at 5-10x lower cost than frontier LLMs
Tied for #1 on Artificial Analysis Decision Index
Processes entire codebase or data room in single context window
Speeds agent reasoning from minutes to seconds
Agents cannot bypass the method: tests cannot close without measured results and written learnings
Enforced workflow prevents confident guesses and invented wins
Shared memory ensures experiments are never repeated and evidence is preserved
Agents read and write to the same record as teams under identical rules
Subquadratic
Hypotize