What is the AI Semantic Bridge?
The AI Semantic Bridge is a middleware platform by CatalystCo that converts application data into vectorized semantic embeddings for LLM retrieval and contextualization.
The AI Semantic Bridge is a middleware platform by CatalystCo that converts application data into vectorized semantic embeddings for LLM retrieval and contextualization.
Supports databases, document stores, APIs, and file systems via connectors, including PostgreSQL, S3, Google Drive, and common REST endpoints.
Processes data in configurable environments, supports on-premise and VPC deployments, encrypts data at rest and in transit, and integrates with role-based access controls.
Compatible with Pinecone, Milvus, Weaviate, FAISS, and other S3-backed or self-hosted vector databases.
Yes — it handles text, images, and structured metadata, extracting embeddings and aligning multimodal contexts for retrieval-augmented generation.
Uses configurable preprocessing, chunking, deduplication, and supports multiple embedding models with monitoring for drift and quality metrics.
Designed for horizontal scaling with distributed ingestion, batching, and backpressure controls to handle millions of documents and high query throughput.
Incremental and real-time ingestion pipelines, webhooks, and change-data-capture options keep the semantic index synchronized with source systems.
Includes dashboards, logging, tracing, and metrics for ingestion latency, embedding throughput, vector store health, and query performance.
Organizations can begin with the open-source SDK, deploy a reference architecture, or request a managed onboarding from CatalystCo to integrate AI Semantic Bridge into their pipeline.