Search
Semantic search for jobs
Harness the power of advanced AI embeddings to revolutionise how you search through job data. This endpoint transforms your search query into high-dimensional vector embeddings, then intelligently matches it against our entire job database using semantic similarity algorithms.
How it works:
- AI Query Understanding - Your search terms are processed through neural embedding models that understand context, intent, and meaning
- Vector-Based Matching - The system compares your query against vector representations of all job content in real-time
- Intelligent Ranking - Returns results ranked by semantic similarity, not just keyword matching
Why this matters:
- Find jobs about "plumbing repairs" even when searching for "fixing pipes"
- Discover relevant work orders that use different terminology but share the same intent
- Uncover hidden patterns and connections in your job data that traditional search would miss
This isn't just search—it's AI that truly understands what you're looking for and delivers the most relevant results, even when the exact words don't match.
get/search/job/embedding.json
Query parameters
qstring required
Example:replace hot water system
Search query string
limitinteger
Maximum number of results to return (max 50)
similarity_thresholdnumber float
Minimum similarity score (0.0 to 1.0)
Response
Embedding search results
Example response
{
"results": [
{
"type": "job"
}
],
"searchType": "embedding"
}