Legacy ETL jobs are brittle, slow, and require expensive engineering maintenance. DataXpress unifies ingestion, transformation, and AI enrichment into a single autonomous streaming pipeline.
Drag and drop data sources, transformation steps, and output destinations. No code required. Complex pipelines in minutes.
Every record that flows through DataXpress can be enriched by AI — entity extraction, sentiment, classification, embeddings — applied in real time.
Connect Kafka, Kinesis, or Pub/Sub. DataXpress processes events as they arrive — millisecond latency from source to insight.
Every transformed record is automatically embedded and stored in a vector index alongside its relational form. Query semantically or structurally.
Ask questions in plain English across your entire data estate. DataXpress translates intent to query and returns structured results instantly.
Continuous statistical monitoring on all data streams. DataXpress alerts you to anomalies, drift, and data quality issues before they reach dashboards.
Add any data source — structured, streaming, or batch. 40+ native connectors.
Visually assemble transformation logic and AI enrichment steps without code.
Each record passes through AI agents for entity extraction and embedding.
Transformed data lands in DataXpress vector-native storage ready for queries.
Use natural language, SQL, or APIs to query your data estate instantly.
Real-time transaction enrichment and anomaly flagging across high-frequency payment streams.
Full behavioral event pipeline from Kafka streams directly into AI-queryable vector stores.
Multi-source operational data unified for live inventory tracking and predictive bottleneck resolution.
Feeds structured vector indices directly into Quantsilica for instant reasoning.
Sandbox code runs query DataXpress datasets directly during live experimentation.
Ingests global job platform streams into ResumeFlow career matching engines.