Multi-agent AI operating system where a CEO agent breaks down business goals and delegates tasks to six specialist agents, with shared memory and a live business dashboard.
Early-stage founders and small teams juggle sales, marketing, support, research, finance and hiring with little headcount. Single-purpose AI tools each cover one function, do not share context, and still leave a person to coordinate everything and track business health manually.
Built a 7-agent AI operating system on FastAPI, Next.js and LLM APIs. A CEO agent decomposes high-level goals into tasks and delegates them to specialist Sales, Marketing, Support, Research, Finance and Hiring agents. Agents share persistent memory in Redis and PostgreSQL so context carries across tasks. A digital-twin dashboard tracks MRR, revenue, burn rate and runway. The system is containerised with Docker and deployed on AWS EC2.
Delivered a working multi-agent system deployed on AWS EC2 and tested by 4-5 users. One goal entered by the user is decomposed and executed across six business functions, with live visibility of MRR, revenue, burn rate and runway in a single dashboard.
7 coordinated agents covering 6 business functions; deployed on AWS EC2 and tested by 4-5 users.