Your Team's Hidden Knowledge
Compounded, Unlocked, And Lasting
We extract institutional knowledge from your SQL query history and turn it into structured, AI-ready context. Delivered in weeks, not months
The Promise of Fast, Trustworthy Analytics Keeps Breaking
Every analytics tool, every AI copilot, every “talk to your data” product promises the same thing: ask a question, get a trustworthy answer, fast. It keeps breaking because the context is missing
Human Analytics
Slow, but trusted
AI Analytics
Fast, but requires human review to be defensible
The Context Infrastructure for Data and Analytics
Our core product, Neuron, analyzes SQL query history to extract, structure, and surface the institutional knowledge your organization has already built
The Momenta Impact
Faster Human Analytics
A governed library of metrics and business rules. Analysts reuse proven logic instead of rebuilding it. New hires onboard in weeks, not months
Trustworthy AI
Validated definitions structured for machines. When you "talk to your data," the AI draws from your approved logic not a generic model
Operational Resilience
Departures, migrations, reorgsthey become execution, not crisis. Knowledge is captured in the system, not trapped in someone's head
The Invisible 80%
Most tools start with schema the visible 20%. The other 80% lives in SELECT statements: CASE expressions, window functions, derived calculations that exist only in query history
We extract what no one else can reach
What We Do
Connect
Share your query history and your schema
Analyze
We read every query, find patterns, and map what your team knows. Fully automated
Assess
We score your analytics health across 46 indicators and flag what's at risk
Review
One session with your team to validate what we found
Deliver
Your complete context layer, ready for your tools and your AI
What You Receive
Metrics Library
Every KPI with SQL formulas, confidence scores, and variant detection
Business Rules Library
WHERE clause playbook 14 domains, 7 filter types
Data Relationship Map
JOIN patterns, cardinality, cross-schema dependencies
Neuron Library
Machine-readable master 14 file types, ~190 fields per metric
AI-Ready Context Package
Snowflake YAML, Databricks JSON, dbt YAML, OSI, RAG docs
If you provide your LLM your query history and schema, would it behave like your best analyst, or confidently repeat your worst habits?
Send us your query history and we will tell you in 3 days
Questions Teams Ask Us
Common questions about the Neuron context layer, our engagement process, and how we fit into your existing data stack