Highlights
Project snapshot
- Structures enterprise product innovation into a guided 9-step AI workflow from briefing to action planning.
- Combines brand-aware ideation, synthetic research, retrieval, and creative generation inside one platform.
- Uses async media pipelines with Supabase, Redis, BullMQ, and Python services for long-running jobs.
Overview
Enterprise AI for product innovation teams
Creator AI is an enterprise AI platform for product ideation, market intelligence, and creative asset generation, built primarily for food and beverage brands.
The system organizes innovation work into a guided workflow so strategy, research, ideas, and assets can move through a repeatable process instead of disconnected experiments.
Problem
Research and ideation were fragmented and low-context
- Research, ideation, and creative production lived in disconnected workflows.
- AI outputs often lacked brand context and reusable organizational memory.
- Trend and competitor analysis were too slow for fast-moving innovation cycles.
Solution
A structured workflow with retrieval, generation, and governance
- Created a 9-step AI workflow covering briefing, insights, research, look and feel, ideation, details, trends, strategy, and actions.
- Combined structured retrieval, synthetic research, and creative generation inside the same product experience.
- Added multi-tenant governance so enterprise teams can keep brand context, assets, and research organized at scale.
Core Features
Capabilities for enterprise product teams
Guided Innovation Workflow
- Nine-step process from briefing to action planning
- Brand-aware AI ideation
- Presentation-ready output generation
Research and Retrieval
- Synthetic market research
- Hybrid search and retrieval
- Data silos for PDFs, scraped data, and research assets
Creative Asset Generation
- Packshots and video generation
- Reusable 'Looks' templates
- Multi-model creative orchestration
Enterprise Controls
- Multi-tenant governance
- Shared research and output storage
- Workflow support for teams, not single-user prompts
Architecture
Next.js APIs backed by queues, storage, and Python services
Client UI
→ Next.js API
→ Supabase / Redis / BullMQ
→ AI providers + Python services
→ Stored assets, research, outputs
Technical Highlights
Multi-service AI execution designed for production workflows
- Built as a multi-service monorepo with 63 API routes.
- Uses async media generation pipelines for long-running creative tasks.
- Coordinates multiple providers, including OpenAI, Gemini, Ideogram, and Replicate, across specialized workflow stages.
Impact
Faster innovation with stronger brand consistency
- Accelerates product innovation cycles for enterprise teams.
- Produces presentation-ready outputs instead of isolated AI experiments.
- Centralizes research, brand context, and generated assets in one governed system.