Railengine ingests data, applies masking and transformation pipelines, and writes the processed output into a query‑optimized datastores
Detects and removes sensitive data such as PII (email, SSN) and infrastructure secrets (keys, passwords).
Converts data into vectors for raw vector or cosine-similarity search.
Prepares data for full-
text search, filtering,
and faceting.
Stores data for fast and real-time data retrieval.
Stores data for historical record-keeping and long-term retrieval
Data is ready to trigger workflows,
agent runs, or Slack/email alerts.
Connects your data to agents and SaaS tools for real-time workflows.
Query-ready access to ingested and transformed your data.
Semantic retrieval over your
data using similarity search.
Fast full-text search and filtering across your datasets.
Provides agents instant access to context-rich, searchable enterprise knowledge, enabling developers to launch advanced RAG workflows, automation, and agent runs while leveraging pre-built SaaS Data Connectors for seamless integration
Trigger an agent to immediately refresh its semantic index, so it always operates on the latest enterprise knowledge.
Trigger agents to update issues, annotate PRs, sync documentation, or enrich CRM records based on new data.
Ingest sensor data and trigger agents to detect anomalies, predict failures, or automate device actions as soon as data is processed.
Rail Engine delivers structured and searchable data perfectly primed for agent development. With Railtracks, developers can use this data to build advanced, code-first agents that act, reason, and automate real workflows.
