Neuron by Momenta Analytics

Neuron by Momenta Analytics is a semantic-layer builder that mines an organisation's SQL query history to recover the institutional knowledge that lives inside SELECT statements, then packages it into a machine-readable model that AI copilots, RAG pipelines and BI tools can rely on. Instead of asking analysts to hand-author a metrics catalog or waiting for a warehouse team to backfill dbt definitions, Neuron runs a five-stage pipeline (Processing, Lineage mapping, Catalog building, KPI analysis, OSI export) across the query logs from Snowflake, Databricks, BigQuery or a Postgres warehouse and produces a documented library of KPIs, business rules, JOIN patterns and cross-schema dependencies with confidence scores attached. Typical outputs include a metrics library where each KPI ships with its inferred SQL formula, a WHERE-clause pattern library grouped into roughly fourteen business domains, and a lineage graph that shows how tables actually get combined in production versus what the ERD says. The exported semantic package plugs into dbt, into RAG chatbots that need reliable table-and-column grounding, and into text-to-SQL agents that would otherwise hallucinate metric definitions. Common workflows: standardising conflicting metric definitions across teams before rolling out an AI analyst, capturing a departing analyst's tribal knowledge before offboarding, giving a new LLM-powered BI assistant a trustworthy context pack so it stops inventing joins, and generating a first-pass dbt semantic layer without a months-long documentation project. Engagements are consultative rather than self-serve: a Momenta team connects the sources, runs the automated analysis, walks stakeholders through the assessment scoring, and hands over validated context packages.