AI-Based Market Research Platform Using Synthetic Profiles

Client: A US investment group focused on growing tech-driven businesses across market research, customer analytics, and marketing

Industry: Market Research & Marketing

Scope: End-to-end design and development of a scalable AI-powered market research platform

Key technologies: Python, FastAPI, AI/ML framework, RESTful API, Google Cloud Platform, SaaS/PaaS components, Infrastructure as Code

Challenge

The client saw an opportunity to use AI and LLM technologies to turn research data into actionable business intelligence, faster. To achieve this, they needed a multi-purpose AI platform for developing and scaling market research tools.

Specifically, the platform had to: 

• Support internal teams, client subsidiaries, and external partners.
• Serve as a modular, scalable, and integration-friendly core for different research products and use cases.
• Use an AI and data science framework to guide product decisions.
• Offer a clear API layer for backend and front-end development.
• Maintain strong availability and performance through cloud infrastructure.
• Raise survey completion toward 80%+ and improve long-term member engagement.

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Solution

Neontri delivered a fully operational AI platform that gave the client a reusable foundation for building and scaling market research products.

Its architecture centres on a structured data pipeline that transforms research data into reliable inputs for AI models, analytics, and downstream applications, with validation and monitoring built into the workflow.

Key features of the AI market research platform included:

• Synthetic profile generation: AI algorithms create realistic profiles that reflect diverse social groups and enable more representative research.
• API-first architecture: Clear API standards allow internal teams and partners to build on the platform and connect new research applications.
• AI and data science framework: Observability, experimentation, and production deployment provide a structured foundation for MLOps.
• Cloud-based infrastructure: Managed cloud services support reliable performance as project demands grow.
• User experience focus: Designed to improve survey completion rates, leading to higher-quality data.

Technology

The solution is backed by a tech stack that supports scalable performance, strong observability, and seamless API integration:

• AI and data science: Custom AI/ML framework, Python, FastAPI.
• Infrastructure: Scalable cloud infrastructure, Google Cloud Platform (GCP).
• Architecture: RESTful API, SaaS and PaaS components, Infrastructure as Code.

Results

Neontri turned the client’s AI concept into a working market research platform with a clear path for further product development.

Key outcomes:

• Production-ready platform: New research products can be built on it without rebuilding the underlying technology from scratch.
• Simplified infrastructure management: Managed cloud services and Infrastructure as Code reduced the need for custom infrastructure setup.
• Stronger survey completion: Designed to move survey completion toward the client’s 80%+ target.
• Lower recruitment costs: Improved member retention reduced reliance on continuous respondent recruitment.

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