Data Pipelines for AI, RAG & Machine Learning
Keep AI, RAG, and machine learning workflows supplied with fresh, trusted data from databases, SaaS apps, and event streams.
Together AI
Together AI built a near-real-time inference analytics pipeline with Estuary in about one week, giving engineering and business teams continuously fresh data for platform economics, SLAs, and investigations.
Read the Together AI storyFuel AI with the Right Data, at the Right Time
Bring operational data from sources such as Salesforce, HubSpot, databases, and event streams into AI workflows, then deliver prepared data to warehouses, applications, and vector databases such as Pinecone.
Fresh Data for AI Workflows
Match data freshness to each AI workload, from low-latency inference and RAG updates to scheduled training and analytical pipelines.
Low-latency CDC and streaming for freshness-sensitive AI workflows
Scheduled batch delivery for training and cost-sensitive workloads
Continuous synchronization across operational and analytical data
AI-Ready Data Preparation
With Estuary, data preparation for AI becomes effortless. Built-in transformations and schema evolution allow you to align incoming data with your model requirements, minimizing preprocessing time.
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Transform data with SQL, Python, or TypeScript
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Automated schema evolution for evolving AI datasets.
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Unified pipelines for consistent, high-quality data ingestion.
Optimized for Retrieval-Augmented Generation (RAG)
Power RAG applications with real-time, unified data pipelines. Estuary integrates effortlessly with vector databases like Pinecone, ensuring your AI systems can access and retrieve the most relevant information in milliseconds.
Direct materialization to vector databases for RAG workflows.
Low-latency data feeds to enhance query accuracy and speed.
Reliable updates ensure AI models use the latest data.
AI Data Pipeline Use Cases
RAG and semantic search
Keep vector indexes synchronized as operational data changes.
AI inference and applications
Deliver fresh features and operational context to latency-sensitive applications.
Machine learning pipelines
Prepare and deliver structured data for training, evaluation, and feature workflows.
AI analytics and monitoring
Continuously move model, inference, and operational events into analytical systems.
Broad Integration Ecosystem
Estuary connects to a wide range of data sources, including Salesforce and HubSpot, to centralize and streamline your AI data preparation. Materialization connectors for specialized tools like Pinecone further simplify AI integration. Explore 200+ connectors →
Native connectors for CRM, marketing, and operational data.
Real-time transformation and enrichment for AI readiness.
Flexible architecture to support future AI tools and platforms.