AI-ready integration platform for data and systems
AI-ready integration
Integrate systems and run AI-ready data pipelines
Connect applications, APIs, and files. Transform data and deliver it to AI agents or downstream systems.
Tray Data Engineering with Tray SQL Transformer
Process millions of records in a single database operation instead of row-by-row execution. Run SQL directly inside your integration workflows and deliver AI-ready data pipelines to agents and downstream systems.
Why teams choose Tray for integration
Agile integration development
Build and evolve integrations faster with a modern builder for connecting, transforming, merging, and enriching data.
Single platform for integration and AI
Unify integration and AI in one governed environment across agents, MCP services, and downstream systems.
High-performance data engineering
Power data pipelines with the Tray SQL Transformer that processes data in a single database operation instead of row-by-row iteration.
How integration works in Tray
Build, transform, and govern AI-ready data pipelines across systems, databases, data warehouses, MCP tools, and agents within the Tray AI Orchestration Platform.
Trigger workflows from app events, webhooks, schedules, or S/FTP file drops supporting enterprise system integration across applications and data platforms. Use native connectors to SaaS applications, databases, LLMs, APIs, and data warehouses such as Snowflake, Databricks, BigQuery, and Redshift. Map fields and define how data moves within the workflow.
Shared platform
Integration within the Tray AI Orchestration Platform
Data integration runs on the same foundation as process automation, API management, and agent development. Integrations can be exposed as managed MCP tools via the Tray Agent Gateway so agents can take governed action using transformed data across systems. Security, audit trails, and logging are centralized, so teams manage integrations, data pipelines, and agent-driven actions in one platform.
Capabilities teams rely on for data integration
In-flight processing with Tray SQL Transformer
Data engineering includes a native virtual database with ANSI SQL support for processing, joining, and aggregating bulk data within integration workflows in a single database operation, built for high-volume data pipelines.
Broad app and database connectivity
Prebuilt connectors across SaaS applications, databases, and cloud data platforms such as Snowflake, Databricks, BigQuery, and Redshift, along with universal API access and support for on-prem systems.
Data hygiene and transformation inside workflows
Cleansing, deduplication, aggregation, enrichment, joins, and complex reshaping are performed using SQL Transformer, JSONata inline functions across any data type, and visual data helpers.
Flexible output for AI and database platform
Deliver JSON objects for APIs and AI agents or write to supported file formats for downstream systems and data platforms within the same workflow.
Support for AI data and knowledge workflows
Ingest structured and unstructured data, including documents such as PDFs, build knowledge stores, and manage embeddings using native Vector Tables to support agent-driven workflows.
Built-in file storage
Use a centralized location to store, manage, and process files, supporting data transformation, file aggregation, and managed file transfer (MFT).
Scalable runtime and governance
Serverless, parallel processing architecture with execution logs, error handling, environment separation, and centralized observability.
Learn more about Enterprise Core.