One Model for Text and Time-Series
Faster Search, Better Detection, One API.
Ship Cross-Modal retrieval, analysis, and pattern recognition with a single vector space.
One Model For Real-World Data.
InertialAI's Multi-Modal embeddings let you process and analyze both Time-Series and text data simultaneously.
Why It Matters
In a world increasingly filled with sensors, the ability to derive meaning from this data using sensor-based AI models is paramount.
“These models show the first inklings of a more general form of artificial intelligence, which may lead to powerful foundation models in domains of sensory experience beyond just language”
— Christopher Manning, Stanford Artificial Intelligence Laboratory (SAIL)
See InertialAI In Action
Explore example use cases across text, time-series, and cross-modal tasks.
Text Understanding
Smart search and document insight
Semantic Q&A
“Side effects of compound XR-401?”
“Mild nausea and headache in 8% of subjects. No severe adverse events observed.”
Clinical_Trial_Report_Vol_3.pdf • 97%
Topic Modeling
500 support tickets analyzed
Login IssuesBillingFeatures
Text Understanding
Smart search and document insight
Semantic Q&A
“Side effects of compound XR-401?”
“Mild nausea and headache in 8% of subjects. No severe adverse events observed.”
Clinical_Trial_Report_Vol_3.pdf • 97%
Topic Modeling
500 support tickets analyzed
Login IssuesBillingFeatures