Building AI Apps with
Greenhouse Data: Vector Search
for Smarter Insights
Making Greenhouse data AI-ready and accessible for smarter apps by seamlessly connecting Greenhouse, Zilliz Cloud, and fivetran.
What is Greenhouse and What's Its Data Like?
Greenhouse is an applicant tracking system and recruiting software designed to optimize the hiring process. It manages structured data like candidate profiles, interview schedules, and application status, along with unstructured data such as resumes and interview feedback. Greenhouse provides tools for sourcing candidates, conducting interviews, and onboarding new hires, making it a comprehensive solution for improving recruitment effectiveness and hiring success.
Challenges for Building AI Apps with Greenhouse Data
Unstructured Data
Much of Greenhouse’s data is unstructured and multimodal. Standard database queries struggle with such text-heavy information, making it difficult to unlock its full potential.
Data Silos
Greenhouse data often exists in isolation, making it challenging to integrate with other enterprise systems or data sources.
Scalability
Massive amounts of user interactions are logged daily, and processing and querying this data in real time requires robust infrastructure, especially when building AI-driven applications.
Personalization
AI apps require deep insights into customer behavior to offer personalized experiences. However, standard searches and SQL queries don’t adequately surface the relationships and similarities hidden in Greenhouse data.
Fueling Greenhouse AI Apps with Vector Search for Smarter Insights
Making Unstructured Data Searchable
Vector search enables AI to explore unstructured Greenhouse data like text and images by comparing the meaning and context of each data point. This allows your AI apps to uncover actionable insights that were previously buried in complex records.
Going Beyond Keywords with Semantic Search
With vector similarity search, your AI apps are no longer limited to basic keyword matching. Vector search solutions like Zilliz Cloud perform deep, context-aware searches, identifying patterns and similarities across Greenhouse data that traditional methods can’t reach.
Uncovering Hidden Relationships
Vector search finds subtle trends and connections within unstructured data. By identifying these hidden patterns, your AI apps generate more accurate predictions, smarter recommendations, and better overall results.
Scalability for Real-Time AI
Designed for speed and scale, vector search engines like Zilliz Cloud can process massive Greenhouse datasets in real-time. Whether it’s handling billions of records or delivering instantaneous insights, vector search ensures your AI applications can perform at peak efficiency.
Connect Greenhouse, Zilliz Cloud, and fivetran to Unlock Instant, AI-Ready Insights
The seamless integration of fivetran and Zilliz Cloud takes the complexity out of building AI-powered apps using unstructured data from Greenhouse and any other sources. With just a few clicks, you can deploy fast, efficient, and scalable search solutions, empowering your AI applications to deliver smarter insights.
1.
Unstructured data from Greenhouse flows to fivetran.
2.
fivetran pre-processes and transforms the data into vector embeddings using OpenAI embedding services.
3.
The Zilliz Cloud connector channels the processed vector data into the Zilliz Cloud vector database in real time, ensuring instant availability for AI-powered tasks.
4.
Zilliz Cloud performs vector similarity searches to find relevant information to user queries.
5.
LLMs leverage the provided contextual information to generate meaningful, context-driven insights.
How to Build AI-powered Search for Every Data Source with Fivetran and Zilliz Cloud
4 min watch
Try This Integration for Free
Make your data AI-ready by connecting Greenhouse, fivetran, and Zilliz Cloud.
Frequently Asked Questions
New to Zilliz Cloud integrations? You're not alone. Here are some answers to common questions about how Zilliz Cloud works with Greenhouse and fivetran.
What is a vector database?
Why integrating Greenhouse, fivetran, and Zilliz Cloud for your GenAI apps?
What types of Greenhouse data can I store and search in Zilliz Cloud?
What is Zilliz Cloud?
What is Fivetran?