Case study · AI Search Visibility Platform
Haylow.ai
Haylow.ai is an AI search visibility platform. It measures how brands appear in AI-generated answers: mentions, sentiment, citations and competitor visibility.
- React.js
- Node.js
- Express.js
- PostgreSQL
- AI APIs
01
Problem & context
People increasingly ask AI assistants for recommendations. Brands need to know whether they are mentioned, how they are described and which sources the answers cite.
02
My role and contribution
My work
- Built the integrations with 4 AI providers.
- Built the backend workflows for response processing and persistent data management that feed visibility analytics and competitor reporting.
Scope
Haylow.ai was built by a team. The parts of the product beyond the provider integrations and these backend workflows were not my work.
03
Technical implementation
Provider integrations
Integrations with 4 AI providers, run from the Node.js/Express.js backend.
Response processing
Backend workflows that process provider responses into structured data.
Persistence
PostgreSQL storage that analytics and competitor reporting read from.
04
Workflow
- Brand queries
- 4 AI providers
- Response processing
- PostgreSQL
- Visibility analytics
Simplified illustration of the flow, not the production schema or architecture.
05
Engineering decisions
Providers stay behind the backend
Provider calls run server-side, so API keys, prompts and failure handling never reach the browser.
One pipeline for every provider
Each provider integration feeds the same processing and storage workflow, so results can be compared across providers and over time.
06
Technologies used
- React.js
- Node.js
- Express.js
- PostgreSQL
- AI APIs
The interface shown above is an original mock-up with placeholder data, not a product screenshot.