Think inside your AI world.
the BI stack through Unl
A modern BI stack is the semantic layer’s finest hour: net revenue means one governed thing, and every dashboard agrees. What it still cannot tell you is whether a given number is good enough — because acceptability is a bar you set, not a metric it models.
The BI stack through Unl reads the modelled metric your tools already govern — the same dashboards, reports and semantic definitions — against the bar you have ratified, so a number comes back cleared-or-not with the reason named, instead of a governed chart you still have to grade.
What the BI stack holds
A BI stack (Looker, Tableau, Power BI and their kin) governs and renders the shared metric layer:
- A governed semantic layer of shared metric definitions
- Modelled dashboards and drill-downs across dimensions
- Scheduled reports and distributions
- Consistent query results every tool agrees on
What the naked read gives you
A naked read hands back the governed dashboard: net revenue retention is 98%, rendered flawlessly and identically for everyone. Accurate, and silent on whether 98% clears your line — because the line is a decision, not a column in the model.
The frame judges the data it is given; it does not verify the source’s accuracy.
What changes when the BI stack is read measured
Say you’re an analytics lead and have ratified one bar this quarter: net revenue retention must hold at or above 100%, because below it the board’s expansion-led growth story is true in name only.
“Are we clearing the retention bar?” returns, measured: no — net revenue retention is 98%, two points under the 100% line you set, so this quarter’s growth is acquisition-led, not expansion-led. The semantic layer supplied the governed 98%; the bar, the verdict and the reason came from what you ratified — the criteria layer the BI stack was never built to hold.
And back again
When you and the board agree to relax the line to 98% for one seasonal quarter, that refinement is settled in Unl — and the next read judges retention against the line you now hold, not the one from last quarter.
The answer comes back measured against what you already decided, and why.
The lane is live and open to this tool today: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.
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Questions people ask
Can my BI tool tell me if a number is good enough?
A BI stack renders a governed metric — net revenue retention is 98% — identically for everyone, which is genuinely valuable and still only description. Whether 98% clears your line is a bar you ratified, not a column the semantic layer models. Through Unl the modelled number arrives measured against that bar, so the answer is cleared-or-not with the reason, not a chart to grade.
What is the difference between the semantic layer and the criteria layer?
The semantic layer standardises what a metric means, so ‘retention’ is one governed calculation everywhere — the BI stack’s real achievement. The criteria layer holds the standard that metric must meet, and why, which no BI tool models. Measured context is that missing layer: the governed number, read against the bar you set.
Does Unl change my dashboards or the governed model?
Unl reads through the BI stack, and can write back on your explicit gesture — it never acts as a side effect of a read.
What this is
Think inside your AI world — you stay in command
Unlimitless (Unl to friends) holds what you've settled, reads what your tools are showing, and catches what's changed out in the world — and hands your AI whatever bears on the work, the moment it's needed, without you asking. The right thing, in front of the model, unprompted, with you in command of the call. So you keep moving toward what you set out to build, on top of everything you've already decided.
It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector. Quick to connect, in a couple of steps.
Unlimitless is open now to invited Alpha. Apply for the Beta waitlist to come in ahead of the full launch:
Alpha is invite-only · free at launch.