Projects · Cloud & hybrid
Database AI & Analytics
Intelligent search, recommendations, and analytics layers built on PostgreSQL, MongoDB, and vector stores like pgvector / Pinecone. Multiplexer Solution wires LLM-assisted insights, semantic search, and warehouse pipelines into your existing apps without forcing a rebuild. Deliverables include retrieval pipelines, evaluation harnesses, and dashboards business teams actually use.
Overview
The Database AI & Analytics offering helps teams turn raw operational data into searchable, actionable surfaces. We layer semantic search, recommendations, and AI-assisted summaries on top of your existing PostgreSQL, MongoDB, or warehouse without forcing a platform rewrite.
Engagements include retrieval pipeline design, embedding strategy, evaluation harnesses, and dashboards business owners can self-serve.
Scope & deliverables
- Vector indexes (pgvector / Pinecone) with chunking and hybrid retrieval recipes
- LLM-assisted query interfaces with safe templating and citations
- Warehouse pipelines via dbt / Airflow with quality tests and freshness SLAs
- Business dashboards in Metabase / Superset / Looker tailored to roles
Outcomes & metrics
- Reduction in support-ticket lookup time via semantic search
- Higher recommendation CTR on product or content surfaces
- Faster decisions with self-serve dashboards replacing weekly emails
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