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Integrations

InertialAI provides integration packages that connect the inertial-embed-alpha embedding model directly to popular data platforms. These packages implement each platform's native interfaces, so you can add InertialAI's multi-modal embeddings to your existing infrastructure without writing custom HTTP clients or embedding pipelines.

Available Integrations

Vector Databases

IntegrationPackageStatusDescription
Chromainertialai-chroma · GitHubAvailableDrop-in EmbeddingFunction for ChromaDB. Supports text-only, time-series-only, and multi-modal inputs.
Pineconeinertialai-pineconeComing soonManaged vector database for high-scale production similarity search.
Weaviateinertialai-weaviateComing soonOpen-source vector database with a GraphQL query interface and built-in ML model integrations.
Qdrantinertialai-qdrantComing soonOpen-source vector search engine with rich filtering support and on-premise deployment options.
Milvus / Zillizinertialai-milvusComing soonCloud-native, billion-scale embedding retrieval.

Time-Series Databases

IntegrationPackageStatusDescription
InfluxDBinertialai-influxdbComing soonPersist raw time-series data in InfluxDB while simultaneously embedding it with InertialAI for downstream AI tasks — a natural fit given InertialAI's focus on sensor data.

Why Use an Integration Package?

Integration packages handle the entire bridge between InertialAI's embeddings API and your storage layer:

  • Drop-in compatibility — implement each platform's native embedding interface, so existing tooling works without modification.
  • Multi-modal input support — embed plain text, raw time-series, or text paired with time-series data in the same collection.
  • Secure credential handling — API keys are read from environment variables and are never persisted to disk.
  • Request lifecycle management — authentication, payload formatting, response parsing, and error propagation are handled for you.

Getting Started

The Chroma integration is available today. If you do not have a Chroma instance running yet, see the Chroma Docker deployment guide to get one up in minutes.

To generate embeddings directly via InertialAI's API without an integration package, see: