The accountability partner for founders that stress-tests ideas, builds personalized business plans, and grades your work PASS or FAIL
The agent-native Growth OS that turns your AI agent into a disciplined growth hacker
Stage
Startup
Not given
Founded
2026
Not given
Based in
AE
US
Pricing model
Freemium
Not given
Pricing
Free trial: 75 credits per day for 7 days, no credit card required. GRILLR Pro: $24.95 per month with 250 credits per day. GRILLR Max: $84.95 per month with 1,000 credits per day.
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
Personalized step-by-step business plan
Idea stress-testing with sharp questions
PASS or FAIL grading on submitted work
Visual business canvas with connected nodes
Market research and competitor checks
Dated tasks with deadlines
Check-ins and streak tracking
Investor-ready deliverables and exports
Website hosting and publishing tools
Multiple active projects support
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
Structured accountability system that demands proof before marking tasks complete
Tailored execution plans based on your specific constraints and business model
Available 24/7 without ego or hourly rate unlike human mentors
Free core accountability loop with no credit card required to start
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