Canonical: https://molo17.com/solutions/ai-rag/ Markdown mirror: https://molo17.com/solutions/ai-rag/index.md Title: AI & RAG solution · Gluesync · MOLO17 Description: Keep the stores behind retrieval and agent workflows synchronized with operational systems, and expose Core Hub pipelines and SQL to MCP clients under the caller Solution · AI data supply # Give AI systems current enterprise data Keep the stores behind retrieval and agent workflows synchronized with operational systems, and expose Core Hub pipelines and SQL to MCP clients under the caller's own permissions. [Explore AI data supply](#how-it-works) [Talk to our team](/contacts/?topic=data-architecture) 1. 01 Synchronize the retrieval store 2. 02 Send only what belongs 3. 03 Connect agents through MCP The challenge ## Models answer from whatever you last exported Retrieval quality depends on how recent the underlying store is, and most AI data supply is still a scheduled dump out of the systems that hold the record. 01 / Staleness ### Exports date immediately A nightly extract into a retrieval store means answers reflect yesterday's inventory, pricing, or case status. 02 / Fragmentation ### Context lives in several engines The records a model needs are spread across relational, NoSQL, and file-based systems with different access paths. 03 / Governance ### Agent access outruns permissions Wiring an assistant straight into production databases spreads credentials and sidesteps the roles already defined. How it works ## Synchronize the stores, then expose them safely Gluesync keeps AI-facing stores current with change data capture, shapes records on the way through, and lets MCP clients reach Core Hub without new privileges. 1. 01 Feed ### Synchronize the retrieval store Continuous CDC keeps document databases, object storage, and analytical targets aligned with the operational source. 2. 02 Shape ### Send only what belongs Row filters, field functions, and user-defined functions decide which records and fields ever leave the source. 3. 03 Expose ### Connect agents through MCP The embedded Core Hub MCP server presents pipeline, monitoring, and SQL tools to MCP clients over standard transports. Gluesync capabilities ## A supply line for retrieval and agent workflows Gluesync keeps the data current and queryable for the layer that builds your embeddings and prompts, rather than generating them itself. 01 ### Core Hub MCP server An embedded Model Context Protocol server runs inside Core Hub and exposes pipeline, observability, and SQL tools to MCP clients. - SSE and streamable HTTP transports - Caller's bearer token and RBAC enforced - Read-only and allow-list modes [Core Hub MCP server](https://docs.molo17.com/gluesync/latest/gs-modules/corehub-mcp.html) 02 ### Continuously synchronized stores Land current records where your retrieval layer already reads them, from document databases to object storage. - MongoDB and Couchbase targets - Parquet in S3, ADLS Gen2, and Cloud Storage - Composed document keys [MongoDB agent](https://docs.molo17.com/gluesync/latest/agents/mongodb-intro.html) [Custom document keys](https://docs.molo17.com/gluesync/latest/core-hub/custom-document-keys.html) 03 ### Payload shaping and filtering Decide at the pipeline level which rows and fields reach an AI-facing store, at both snapshot and CDC time. - Inclusive row-level filters - Field functions on values - User-defined functions [Data filtering](https://docs.molo17.com/gluesync/latest/core-hub/data-filtering.html) [User-defined functions](https://docs.molo17.com/gluesync/latest/core-hub/user-defined-functions.html) Related solutions ## Continue exploring Gluesync use cases [ Solution · Lakehouse ingestion ### Data Lake Write snapshots and continuous changes into Amazon S3, Azure Data Lake Storage Gen2, and Google Cloud Storage as Parquet, CSV, or JSON—without adding analytical load to production databases. Explore Data Lake →](/solutions/data-lake/)[ Solution · Unified customer data ### Customer 360 Bring CRM, ERP, and NoSQL records about the same customer into one continuously updated view—by replicating them into a shared target, or querying them in place through Query Forge. Explore Customer 360 →](/solutions/customer-360/)[ Solution · Federated data access ### Federated Queries Run read-only SQL across isolated Gluesync agents through one JDBC endpoint—without first copying raw data into a central warehouse. Explore Federated Queries →](/solutions/federated-queries/) ## Point your models at data that keeps moving Start a trial or talk with MOLO17 about the stores, filters, and access model behind your AI workloads. [Request a free trial](/get-gluesync/) [Talk to our team](/contacts/?topic=data-architecture)