net_expansion_rate
Expansion, revenue, churn, and usage change by segment, product line, and dashboard owner.
Governed AI analytics
The AI analyst product can finally rely on.
Ask a business question and get the answer your data team would stand behind: the metric definition, the right joins, accepted SQL, source evidence, and approved caveats checked before it answers.
People leave. The context behind trusted numbers should not.
metric definitionsright joinsaccepted SQLapproved caveats
Where is expansion revenue accelerating?
Answer ready
+18.6%
Enterprise expansion is up 18.6%, led by annual-plan upgrades after the packaging change. Promo cohorts are excluded.
metric definitionnet_expansion_ratereviewed by Finance
trusted joinsaccount_id3 accepted paths
accepted SQLquery #219reused pattern
approved caveatpromo cohortexcluded
SQL preview
inspect
select account_id, expansion_month, sum(expansion_arr) / nullif(sum(starting_arr), 0) as expansion_ratefrom analytics.account_expansionwhere segment = 'enterprise' and promo_cohort = falseWhy self-serve analytics breaks
Bad answers usually start before SQL.
The metric, segment, join, launch caveat, and prior fix are scattered across dbt, dashboards, notebooks, Slack, and someone's head. Uncypher pulls that business context into the answer path first.
Same metric, different answer
Known fixes get rediscovered
Product changes rewrite the data
Caveats disappear after the meeting
Question
Which expansion accounts are actually healthy?
SQL #219
A teammate already found the right filter or join. Everyone else still repeats the work.
annual packaging
Packaging, pricing, and workflow changes can make yesterday's query wrong today.
promo cohort excluded
The important assumption stays in a thread, a notebook, or a person who may not be around next quarter.
Context missingneeds review
2 definitions3 join paths1 promo caveat
Verified answer flow
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Uncypher turns a messy ask into a governed answer path: choose the right metric, check trusted sources, preview the SQL, and attach the caveat before anyone uses the number.
Before the answer runs
metric selected
sources checked
SQL previewed
caveat attached
Ask
Start with the business ask
Resolve
Choose the metric and grain
Verify
Show proof before the number
Which segment should growth prioritize next?
AskResolveVerifyRemember
Answer ready
+18.6%
Enterprise expansion is strongest in annual-plan upgrades.
Resolver trace
metricnet expansionreviewed
segmententerprisematched
sourceannual upgradesverified
caveat checkedPromo cohort excluded before the answer becomes reusable.
Governed context layer
A living map of how your company measures the business.
Uncypher connects metrics, joins, accepted SQL, product rules, owners, caveats, and review decisions so the answer arrives with its proof, not as another unsupported number.
metric definitions and owners
entities, joins, and trusted filters
accepted SQL patterns
product rules that change meaning
caveats, conflicts, and review decisions
answer pathexpansion priority
metricexpansion_rate
entityaccount_id
ruleannual packaging
sqlquery #219
Self-serve, with control
Business gets speed. Data keeps the guardrails.
Business
Business leaders
Ask the follow-up as soon as the number looks wrong, then see the assumptions behind it.
plain-English analysis
segment and caveat visibility
shareable answer trail
Data
Data teams
Codify the checks your team already performs and decide what becomes reusable.
review queues
SQL and product-rule provenance
approved reusable patterns
Expansion
+18.6%
Expansion isolated to annual-plan upgrades after packaging changes.
Trust trail
metric definitionreviewed
SQL previewaccepted
product rulechanged
contextreusable
Works with your stack
Bring the sources analysts already trust into the answer.
Warehouse
dbt
GitHub
Notebooks
Dashboards
Governed analysis layer
Sources attached to every answer
Review states before reuse
Permissions respected
SQL preview before execution
metric
reviewed
query
accepted
product rule
confirmed
context
reusable
Govern AI analytics
Make every answer carry the reasoning with it.
Uncypher turns repeated data questions into approved context your company can inspect and reuse: definitions, joins, SQL patterns, product rules, caveats, and the decisions behind them.