AI Advisor Board
AI Advisor Board simulates a leadership meeting by assigning LLM agents to roles such as Sales, Customer Success, Product, and Research. Each director contributes domain expertise, challenges assumptions, and drafts a unified recommendation using structured prompts and critique loops.
The Problem
Executives need to synthesize perspectives from multiple stakeholders quickly, but real meetings are expensive and constrained by scheduling.
The Solution
Built autonomous directors with shared memory and turn-based debate. Each round the agents surface risks, customer sentiment, and data-backed insights before converging on an action plan.
The Outcome
Produces actionable briefs in minutes, highlighting risks, objections, and follow-up actions. Early pilots reduced prep time for leadership syncs by 70%.
Key Features
- Role-based multi-agent coordination
- Deliberation rounds with critique and revision
- Memory subsystem for cross-session context
- Scenario simulation and what-if analysis
- Exportable executive summaries
Technology Stack
Interested in this project?
I'd love to discuss the technical details, challenges overcome, or similar projects I could build for you.
View Live AppLet's discuss this project