Decide · Metrics
One source of truth for every number — that your AI can actually use.
"What's our active members?" shouldn't have three answers. Flash defines each business metric once, certifies the caliber, and computes it on one engine — so a dashboard, an API call, and an AI agent never disagree.
GMV
$198,862
Active members
purchase · 90d
Open rate
delivered basis
Redemption rate
code-level
"Why did active members dip last month?"
→ picks the certified active_members caliber, breaks it down by store & channel — never invents a number.
The problem
The same metric means three different things in three tools.
Definitions drift
GMV, churn, redemption rate — each gets redefined in every report, so two teams quote two numbers and nobody knows which is right.
AI invents numbers
Point an LLM at raw tables and it writes SQL against columns it doesn't understand — confident, untraceable, and often wrong.
Custom metrics are risky
Letting analysts query raw tables means cross-tenant leaks and hand-rolled filters — one wrong WHERE clause from a data incident.
How it works
A governed catalog, one engine, and metrics AI can call safely.
80+ business metrics across seven categories, each with a single definition, plain-language guidance, and one computation path — read by every surface from the same source.
Sales & Revenue
GMV, net GMV, orders, AOV, refund & discount rate.
Customer Value & Retention
Active members, retention, churn-risk, LTV signals.
Membership & Lifecycle
New / total / marketable members, tier moves, opt-in rate.
Points & Rewards
Issued, redeemed, expired, breakage, outstanding liability.
Email & Messaging
Sent, delivered, open / click / bounce / unsubscribe rate.
Web & Portal
Page views, sessions, portal blocks, UGC, abandoned cart.
Attribution & Growth
Referrals, ambassadors, D2C channel orders, coupons.
+ your own
Add custom metrics with a structured editor or guarded SQL — dry-run first.
One definition · every surface reads the same number
ONE DEFINITION
active_members
Certified caliber, owner-locked. Changed only through a reviewed PR — git is the approval trail.
Dashboards
same number, same caliber
Reports & API
same number, same caliber
SoTag in Slack
same number, same caliber
MCP AI agents
same number, same caliber
Certified, owner-locked calibers
A certified metric is locked to its owner; changing its caliber goes through a reviewed PR, so the definition has an approval trail instead of quietly drifting.
Custom metrics, safe by construction
Build with a no-SQL structured editor, or write SQL that can only read security-barrier metric_safe_* views — team-isolated by the database, not by your WHERE clause.
Ask in plain language
Ask a question; Flash picks the right governed metric, applies its certified caliber, and breaks it down by store, channel or tier — grounded, never guessed.
Why it's different
BI tools let everyone redefine the number. A semantic layer doesn't make it AI-safe. Flash does both.
Dashboards let every report invent its own caliber — so the numbers drift. Modeling layers define metrics but don't make them tenant-safe or AI-callable. Flash governs the definition andmakes the same metric the only way AI agents and dashboards can read it.
Typical approach
BI / spreadsheet metrics
Every report redefines GMV or churn — three tools, three numbers.
Flash, by design
One certified caliber, owner-locked, versioned — change it once, everywhere updates.
Typical approach
dbt / LookML semantic layers
Define metrics, but leave AI access and tenant isolation to you.
Flash, by design
The same governed metric is exposed as an MCP tool and isolated by security-barrier views.
Typical approach
Raw-SQL AI copilots
Write queries against tables they don't understand — and hallucinate.
Flash, by design
AI can only call governed metrics; it returns the caliber-correct number or says it can't.
AI & innovation
The semantic layer is what makes Flash's AI trustworthy.
SoTag in Slack and MCP agents don't query your tables — they call the same governed metrics your dashboard reads. So the number an agent quotes is the number on your screen, by construction.
Governed tools, not raw SQL
Metrics are exposed to AI agents as governed MCP tools — scoped, tenant-isolated, and caliber-correct — so agents act on the same truth as your team.
One engine, identical everywhere
Every built-in metric now computes on one DB-driven engine — so 'ask the AI' and 'open the dashboard' can't return different numbers.
Grounded or it abstains
If a question maps to no governed metric, the AI says so instead of fabricating a query — trust over a confident wrong answer.
What changes for the business
One number per metric, an approval trail behind it, and AI answers you can actually trust.
80+
governed metrics across 7 categories
1 caliber
per metric — certified & owner-locked
1 engine
every dashboard, API & agent reads the same
0 raw SQL
AI calls governed metrics, never your tables