Turn Your SQL Query History Into A Portable Semantic Model
Neuron Pipeline mines the thousands of queries your analysts have already written and distills them into one platform-neutral semantic model: metrics, relationships, business rules, and data domains, delivered as a single OSI v1.0 YAML file
$ docker run -v ./query_history:/data neuron-pipeline:1.0
semantic_model.osi.yaml
OSI v1.0 · one file, fully reviewable
46
business KPIs scored
OSI v1.0
open standard output
24 hours
from history to semantic model
0 bytes
of your data leaves your machine
Your Real Data Logic Already Exists
Neuron Extracts It
Every organization’s real data logic lives in its SQL query history, buried in thousands of ad-hoc queries, dashboards, and analyst scripts. Neuron Pipeline extracts that knowledge automatically, in five stages:
Processing
Cleans and structures your raw query history into a consistent, analyzable foundation
Lineage
Maps table-to-table and column-to-column data flow, and discovers the metric definitions your teams actually use
Catalog
Builds a complete data catalog: tables, columns, dimensions, facts, and data domains
KPI Analysis
Scores 46 business KPIs about your analytics practice: query reuse, knowledge concentration, efficiency gaps
OSI Export
Combines everything into one OSI (Open Semantic Interchange) v1.0 semantic model
the standard
Open Semantic Interchange v1.0
A platform-neutral format for semantic models... Learn more at open-semantic-interchange.org
Define Once, Deploy Everywhere
Your one YAML file translates into all major semantic platforms:
Ask Your Data In Plain English
Get Back Ready-To-Run SQL
Landing in the next release, the same image will ship the Neuron Agent. After your run, build a knowledge base from your own output, then ask plain-English questions — it returns a complete, documented SQL query built from your proven query patterns, business rules, and metrics.
Grounded In Your Data
It never invents tables or columns — every query is built from your own proven query patterns
Cited, Line By Line
Every part of the query points to where it came from: a real past query pattern, business rule, or metric
States Its Assumptions
If your question is vague, it tells you the assumption it made instead of guessing silently
Stays On Your Machine
Your data never leaves your computer — only the question text goes to the AI
Pre-matching knowledge base…
Pre-match: 8 neurons · 2 rules · 5 metrics
[routing] Haiku done → Opus synthesis…
-- Provenance: Neuron_1234 · BR-1195 · MET-0042 WITH patient_starts AS ( SELECT patient_id, MIN(start_date) AS first_start FROM fct_therapy_starts -- Source: Neuron_1234 GROUP BY patient_id ) SELECT COUNT(*) AS new_patients_2025 FROM patient_starts WHERE first_start >= '2025-01-01';
Built To Be Trusted With Your Query History
Runs 100% Locally
The pipeline is a Docker image that runs on your machine. Your query history never leaves your computer
One File Out
The only output is your semantic model YAML: clean, reviewable, portable
No Setup Pain
Docker Desktop + one copy-paste command. A full Quick Start guide is included
Optional AI Enrichment
Works fully offline with --no-llm; add an OpenAI or Anthropic API key for AI-powered business-rule extraction and metric descriptions
Three Steps, No Sales Call
Enter Your Email
Enter your email and choose your platform
Download The Image
Download the Docker image (~150 MB) and the Quick Start guide
Run One Command
Run one command on your query history export and get your semantic model YAML within 24 hours
Start Mining Your Query History Today
Your files
These unlock when you submit the form