Nebulus

Nebbi our PM Agent

Inspiration

Nebulus was inspired by a failed startup.

We realized the problem was not just building the product. With modern AI, coding is easier than ever. The real bottleneck is everything around it:

planning
outreach
finance
legal
coordination

Founders do not just need a coding copilot. They need an execution layer.

What it does

Nebulus is an agentic AI system designed to help founders operate end to end.

At a high level, it works like an AI co-founder:

autonomous agents share context
agents coordinate work across the business
founder intent gets turned into action

Instead of only generating responses, Nebulus helps move a company from idea to execution.

Key features

Automation with visibility
Agents can generate plans, break work into tasks, and coordinate execution across workflows.
Real-time text updates
Users can see progress as the system works, instead of waiting for a single final output.
Voice interaction
Founders can talk to Nebulus naturally, making it feel more like working with a real co-founder than a chatbot.

How we built it

Nebulus is built as a multi-agent system with a shared-context architecture.

Tech stack overview

Frontend: responsive interface for real-time text updates and voice interaction
Backend: orchestration layer for task routing, state management, and agent coordination
AI layer: specialized LLM-based agents for planning, outreach, finance, and legal support

System design

The backend translates founder intent into tasks, routes those tasks to the right agents, and keeps state synchronized across the workflow.

The overall architecture is built around:

shared context
real-time updates
multi-agent coordination
human approval for critical actions

Challenges we ran into

The biggest challenge was integration.

Building one strong agent is hard. Building multiple agents that can reliably coordinate is much harder.

Some of the hardest problems were:

passing context between agents
maintaining shared state
preventing agents from conflicting with each other
keeping the experience coherent for the user

Real-time updates also added complexity. We wanted users to see the work happening live, not just receive a final answer. Making that experience smooth and reliable was one of the hardest parts of the project.

Accomplishments that we're proud of

We are most proud of how practical Nebulus feels.

A lot of AI products look impressive in a demo but are hard to use in real workflows. Nebulus is grounded in a real founder problem:

too many responsibilities
too much context switching
not enough coordination

We are also proud that it feels easy to use despite the complexity under the hood.

Nebulus supports:

multiple coordinated agents
real-time updates
voice interaction

while still feeling intuitive and usable.

What we learned

We learned that the hardest part of agentic AI is not just intelligence. It is orchestration.

Getting multiple agents to operate over shared context, stay aligned with user intent, and produce useful work is as much a systems problem as an AI problem.

We also learned that trust matters as much as autonomy. Users want speed, but they also want: