🎬 Scenepilot

AI-powered production management infrastructure for film and media teams.

Scenepilot is an AI-powered production management platform designed to help film, television, and media production teams plan, coordinate, and manage their productions from a centralized workspace.

It combines production management workflows with AI-assisted planning, team collaboration, notifications, organization management, and intelligent production support.

What the Project Does

Scenepilot provides a centralized digital workspace where production teams can manage the operational side of a media production.

Instead of relying on disconnected spreadsheets, messaging applications, documents, and manual coordination, Scenepilot brings important production workflows into a single platform.

The long-term vision is to provide an AI-native operating system for media production, where production teams can use intelligent agents to assist with research, planning, coordination, and decision-making.

1. The Problem It Solves

Film and media production involves coordinating many moving parts simultaneously:

Production teams
Projects and organizations
Schedules
Tasks
Communication
Research
Production planning
Team permissions
Notifications
Production documents
Operational decisions

These workflows are often distributed across multiple tools.

This creates several problems:

Information becomes fragmented across different platforms.
Production managers spend significant time coordinating routine tasks.
Teams have difficulty maintaining a single source of truth.
Important notifications and updates can be missed.
Production information is difficult to organize and retrieve.
Planning and research require significant manual effort.

Scenepilot addresses this by providing a unified production workspace with AI capabilities built directly into the workflow.

The goal is not simply to digitize existing production processes, but to make them more intelligent, collaborative, and automated.

2. Key Features

🏢 Organization Management

Manage production organizations and their members from a centralized workspace.

Organization workspaces
Member management
Role-based access
Team invitations
Organization settings
Member status management

🔔 Production Notifications

Keep teams informed about important activity.

Notification center
Unread notification tracking
Invitation notifications
Team activity updates
Notification refresh
Accept/decline workflows

👥 Team Collaboration

Give production teams a shared environment for coordinating their work.

Team members
Organization roles
Permissions
Collaboration workflows
Centralized production information

🤖 AI-Powered Production Assistance

Scenepilot is designed around AI-assisted production workflows.

Future AI capabilities include:

Production planning
Research assistance
Intelligent recommendations
Production analysis
Automated task generation
Context-aware production assistance

📋 Production Management

Centralize production-related operational information.

The platform is designed to support workflows such as:

Project management
Production planning
Task coordination
Team management
Scheduling
Production research
Operational tracking

🔐 Secure Authentication & Authorization

Scenepilot is designed with authenticated production workspaces and permission-aware functionality.

Users can access resources based on their organization membership and assigned permissions.

3. Screenshots / Demo

a live demo will be added as the platform reaches production-ready milestones, but for now here are some pictures of progress made:

Landing Page

Sign-up page

Sign-in page

Dashboard

Invitation modal

Notification panel

4. Tech Stack

Scenepilot is built using a modern full-stack TypeScript architecture.

Technology	Purpose
Next.js	Full-stack React application framework
React	User interface
TypeScript	Type-safe application development
Tailwind CSS	UI styling
MongoDB	Application database
MongoDB Atlas	Cloud database infrastructure
Google Gemini	AI capabilities
Node.js	Server-side runtime
Lucide React	Interface icons
GitHub	Source control and collaboration

Core Architecture

Frontend
   │
   ▼
Next.js / React
   │
   ├── UI Components
   ├── Application Pages
   ├── Organization Management
   ├── Notifications
   └── Production Workflows
          │
          ▼
     Server / API Layer
          │
     ┌────┴────┐
     ▼         ▼
 MongoDB    Gemini AI
     │         │
     ▼         ▼
Production   AI-powered
Data         workflows

5. Architecture

Scenepilot's follows a modular full-stack architecture designed to support the gradual introduction of AI agents and production automation.

High-Level Architecture

                         ┌──────────────────────┐
                         │      Scenepilot      │
                         │      Web Client      │
                         └──────────┬───────────┘
                                    │
                                    ▼
                         ┌──────────────────────┐
                         │      Next.js         │
                         │ Application Layer    │
                         └──────────┬───────────┘
                                    │
                    ┌───────────────┼────────────────┐
                    │               │                │
                    ▼               ▼                ▼
             Authentication   Production       Organization
             & Authorization   Workflows        Management
                    │               │                │
                    └───────────────┼────────────────┘
                                    │
                                    ▼
                         ┌──────────────────────┐
                         │      Data Layer      │
                         │       MongoDB        │
                         └──────────┬───────────┘
                                    │
                                    ▼
                         ┌──────────────────────┐
                         │      AI Layer        │
                         │   Google Gemini      │
                         └──────────────────────┘

Design Principles

Scenepilot is being developed around several principles:

Modularity

Production capabilities should be independently maintainable and extensible.

AI-native workflows

AI should assist users inside existing production workflows rather than exist as an isolated chatbot.

Centralized production context

The platform should maintain useful context about projects, teams, tasks, and production operations.

Scalability

The architecture is designed to support additional production services and AI agents as the platform evolves.

Security

Authentication, authorization, environment configuration, and database access are treated as core infrastructure rather than afterthoughts.

6. How to Run It Locally

Prerequisites

Make sure you have installed:

Node.js 20+
npm
Git
MongoDB / MongoDB Atlas account
Google Gemini API access

Clone the Repository

git clone https://github.com/YOUR_USERNAME/YOUR_REPOSITORY.git

cd YOUR_REPOSITORY

Install Dependencies

npm install

Configure Environment Variables

Create a local environment file:

cp .env.example .env.local

Then configure the required values.

See the Environment Variables section below.

Start the Development Server

npm run dev

The application will be available at:

http://localhost:3000

Run Linting

npm run lint

Run TypeScript Validation

npx tsc --noEmit

Create a Production Build

npm run build

Start the Production Server

npm start

7. Environment Variables

Scenepilot uses environment variables for sensitive configuration.

Create a .env.local file in the root of the project.

Example:

NEXT_PUBLIC_APP_URL=http://localhost:3000
MONGODB_URI=
AUTH_SECRET=
GOOGLE_CLOUD_PROJECT_ID=
GEMINI_API_KEY=
PARALLEL_API_KEY=

Important: Never commit .env.local or production secrets to GitHub.

A sanitized .env.example file should be maintained in the repository so developers know which variables are required without exposing credentials.

Environment Security

The following should never be committed:

.env
.env.local
.env.production
API keys
Database credentials
Private tokens
Authentication secrets

8. Database Setup

Scenepilot uses MongoDB as its primary application database.

MongoDB Atlas can be used to provide the cloud database infrastructure.

Create a MongoDB Database

Create a MongoDB Atlas account.
Create a cluster.
Create a database user.
Configure network access.
Obtain the MongoDB connection string.
Add the connection string to .env.local.

Example:

MONGODB_URI=mongodb+srv://<username>:<password>@<cluster>/<database>

The application uses the MongoDB connection configuration to access production data.

Database Responsibilities

MongoDB is intended to store application data such as:

Users
Organizations
Organization members
Notifications
Production projects
Production-related application data

As the application grows, additional collections and indexes can be introduced for specific production workflows.

9. Authentication

Authentication protects access to production workspaces and user-specific resources.

The authentication architecture is designed around:

User
 │
 ▼
Authentication
 │
 ▼
Authenticated Session
 │
 ▼
Organization Membership
 │
 ▼
Role / Permissions
 │
 ▼
Authorized Resources

Authorization is particularly important because production organizations may contain multiple users with different responsibilities and access levels.

Authorization Model

The platform is designed to support organization-level access control, including:

Organization membership
User roles
Permission-aware actions
Protected production resources
Team administration

The exact authentication provider and implementation should be documented here once the authentication layer is finalized.

10. Deployment

Scenepilot is designed to be deployed as a modern Next.js application.

Recommended Deployment Architecture

                  GitHub
                     │
                     ▼
                CI / Build
                     │
                     ▼
              Next.js Hosting
                     │
          ┌──────────┴──────────┐
          ▼                     ▼
      MongoDB Atlas         Gemini API
          │                     │
          └──────────┬──────────┘
                     ▼
                StudioOS

Production Deployment

A typical deployment process is:

npm ci
npm run lint
npx tsc --noEmit
npm run build

Then deploy the resulting Next.js application through the selected hosting platform.

Production Environment Variables

Production secrets should be configured through the hosting provider's environment-variable management system rather than committed to the repository.

11. Roadmap

Scenepilot is being developed incrementally toward a complete AI-powered production operating system.

Phase 1 — Core Platform

Phase 2 — Production Management

Phase 3 — AI Production Assistant

Phase 4 — Autonomous Production Agents

Phase 5 — Production Intelligence

Phase 6 — Production Ecosystem

12. Future Improvements

The long-term vision for Scenepilot extends beyond traditional production management software.

🧠 Autonomous Production Operations

Scenepilot could evolve from a tool that helps production teams manage work into an intelligent system capable of actively coordinating production operations.

AI agents could:

Monitor production progress
Identify potential issues
Recommend corrective actions
Research production requirements
Generate planning documents
Coordinate repetitive workflows
Surface important information automatically

🎥 Production Intelligence

Future versions could analyze production data to provide insights into:

Schedule risks
Resource allocation
Production bottlenecks
Task dependencies
Budget-related risks
Team workload
Production performance

🔌 Production Integrations

Scenepilot could integrate with the tools production teams already use, creating a connected production ecosystem rather than forcing teams to abandon existing workflows.

🌎 Scalable Production Infrastructure

The long-term goal is to build infrastructure that can support productions ranging from independent projects to larger professional media organizations.

Vision

Scenepilot aims to become more than another project-management application.

The vision is to build an AI-powered operating system for media production—a platform where production teams can manage their people, projects, workflows, information, and decisions while AI handles increasingly complex operational tasks.

Build the infrastructure. Let AI handle the complexity. Let production teams focus on creating.

Project Status

🚧 Active Development

Scenepilot is currently under active development. Features, architecture, and APIs may change as the platform evolves.

Contributing

Contributions, suggestions, and technical discussions are welcome as the project matures.

If you find an issue or have an idea for improving Scenepilot, please open a GitHub Issue describing:

The problem
The proposed solution
Why the change would benefit production teams

License

This project is currently under active development.

See the LICENSE file for licensing information.

Author

Ukpai Bishop

Building AI-powered software infrastructure for modern production workflows.

GitHub

Name		Name	Last commit message	Last commit date
.github		.github
app		app
components		components
lib		lib
models		models
public		public
types		types
.dockerignore		.dockerignore
.env.example		.env.example
.gitignore		.gitignore
AGENTS.md		AGENTS.md
CLAUDE.md		CLAUDE.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
eslint.config.mjs		eslint.config.mjs
middleware.ts		middleware.ts
next.config.ts		next.config.ts
package-lock.json		package-lock.json
package.json		package.json
postcss.config.mjs		postcss.config.mjs
tsconfig.json		tsconfig.json

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