Data Migration

Make Your DataAgent-Ready

Build RAG pipelines, vector stores, and knowledge bases from any data source. Let AI agents query your data intelligently.

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Data Migration Capabilities

Transform siloed data into AI-queryable infrastructure.

RAG Pipeline Creation

Build retrieval-augmented generation pipelines that let AI agents query your data contextually

Vector Embedding Generation

Generate semantic embeddings for intelligent search and similarity matching

Knowledge Base Structuring

Organize unstructured data into queryable knowledge graphs and bases

Real-Time Sync Connectors

Keep your AI systems synchronized with source data through streaming connectors

Data Migration Process

1

Discovery

Map data sources, schemas, relationships, and access patterns

2

Analysis

Assess data quality, identify transformation requirements

3

Transformation

Build connectors, generate embeddings, structure knowledge bases

4

Validation

Test data integrity, query performance, and agent accessibility

5

Deployment

Deploy connectors with monitoring and sync management

What You Get

Complete data infrastructure that AI agents can query, search, and reason over.

  • Agent-ready data connectors
  • RAG pipeline infrastructure
  • Vector stores and embeddings
  • Knowledge base APIs
  • Real-time sync mechanisms
  • Query optimization layers

Agent-Ready Infrastructure

Your data becomes instantly queryable by any AI agent through standardized connectors, vector search, and knowledge APIs.

Typical timeline: 2-6 weeks
Complexity: Medium

Supported Data Sources

PostgreSQLMySQLSQL ServerOracle DBMongoDBS3/GCS/Azure BlobData warehousesMainframe systemsFile systemsSharePointConfluence

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