HiveMind

Inspiration

Understanding customers is the heart of every successful business. But discovering real customer insights is expensive and slow. Traditional market research methods such as focus groups require significant budget and time. Our team asked a simple question: What if companies could test ideas with realistic customer personas instantly? This idea led to the creation of HiveMind AI Persona, a platform that simulates real customer perspectives using AI.

What it does

HiveMind is an AI-powered market research platform that uses synthetic personas to simulate customer feedback instantly.Instead of waiting weeks for research results, teams can test ideas with AI personas and receive insights within minutes. HiveMind provides three core capabilities:

1. Design Feedback Teams can upload product designs, UI screens, or campaign materials and receive feedback from multiple AI personas representing different customer segments.
2. Insight & Recommendation The system analyzes responses and generates structured insights and recommendations to help teams improve their ideas.
3. Persona-based Artwork Suggestions HiveMind can also suggest marketing visuals or artwork that better match the target persona.

How we built it

The platform runs on AWS cloud infrastructure, using CloudFront for content delivery and Amazon S3 for artifact and object storage. It follows a cloud-native microservices architecture with containerized services (Docker/Kubernetes) including hm-orch-insight-flow-mgmt for orchestration and hm-core-platform-mgmt and hm-core-insight-mgmt for processing and platform management. Data is stored in MongoDB (ins-engine-store), while Apache Kafka enables event-driven communication and asynchronous processing between services. The system also integrates n8n (ins-engine-n8n) to power Agentic AI workflows, enabling autonomous agents to execute automated tasks, orchestrate processes, and interact with the platform. A web portal (ins-engine-webportal) provides the user interface for managing and monitoring insight workflows.

Challenges we ran into

Building realistic AI personas is not easy. One of the biggest challenges was ensuring that the responses generated by AI personas closely resemble real human feedback. To validate this, we compared AI persona responses with real market research data provided

Accomplishments that we're proud of

We validated HiveMind by comparing AI persona responses with real user research data. The result showed that AI persona responses matched human insights by up to 80%.

What we learned

Through building HiveMind, we learned that AI personas can significantly accelerate product and marketing decision-making.

What's next for Untitled

In the next phase, we plan to expand HiveMind into a full AI-powered market research ecosystem, including: • End-to-end market research automation • Integration with social listening platforms • Advanced persona generation from real customer datasets

Built With

• amazons3
• apache
• cloudfront
• docker
• kubernetes
• mongodb
• n8n
• nova2lite
• nova2omni
• nova2pro