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Product

Semantic Search and Enrichment

Every tool response is automatically enriched with business context from complementary services. One enriched call does the work of five or more. Bidirectional cross-enrichment is the architectural difference between Plexara and MCP servers that merely wrap an API.

Before and After

What Cross-Enrichment Means Concretely

A single enriched response replaces multiple round trips. The agent receives complete business context without making additional tool calls.

Without Plexara

5+ sequential tool calls

Call 1Describe table schema
Call 2Fetch column descriptions
Call 3Look up data owner
Call 4Check quality scores
Call 5Get deprecation status
ResultAgent assembles context manually

With Plexara

1 enriched response

Call 1Describe table through Plexara
ResultSchema + descriptions + owner + quality + deprecation + glossary terms + lineage

Four Directions

Bidirectional Across Every Service

TrinoDataHub

Query results enriched with catalog metadata: column descriptions, owners, tags, glossary terms, lineage, quality scores, and deprecation warnings.

DataHubTrino

Catalog search results enriched with query engine availability: which datasets are queryable, their resolved table paths, and which Trino connections can reach them.

S3DataHub

Storage objects enriched with catalog metadata: what the object contains, who owns it, its lineage within data pipelines, and any associated quality signals.

DataHubS3

Catalog entities enriched with storage availability: which objects exist in S3, their sizes, last modified dates, and presigned URL access patterns.

Efficiency

Fewer Calls, Better Context

1

Tool call instead of 5+

+15.4pts

Overall accuracy lift in our published benchmark

0

Redundant metadata fetches per session

Enrichment consolidates what would be multiple round trips into single responses. Session-aware deduplication tracks what context has already been provided and avoids repeating it within the same conversation.

The accuracy figure is measured, not estimated. Our published benchmark holds the model constant and ablates the platform: overall accuracy on the same tasks rose from 83.1% to 98.5% with the semantic layer in place.

Tool visibility filtering hides tools the user is not authorized for, further reducing the number of tool descriptions in the agent context window. Fewer tools means fewer tokens consumed by tool metadata on every request.

None of this is hardwired to specific products. Enrichment talks to the catalog, query engine, and object store through the provider interfaces described on the architecture page, so a backing service can be swapped without touching how enrichment works.

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Memory

Persistent knowledge across sessions that makes your AI smarter over time.