Automated retail intelligence, waiting when you start the week.
Agentic AI analyses your commercial performance for you — every lever, every week, automatically. What changed, why it changed, and what it means for the quarter, before the week begins.
Not a dashboard to interrogate. A position, already taken.
No BI team required · Live in one trading week · Currently piloting in AU and US
Quarter needs 3.1x current run rate; paid scale covers just 18% of this week's gap.
Another week at this rate adds $85K to the quarter shortfall
Refunds at 12.6% against a 25% target — no excess recoverable
Inventory at 96.4w cover vs 40w target
QTD Actuals
$325K
traded to date
Plan to Date
$750K
plan to the same point
QTD Gap to Plan
$-425K
actual vs plan-to-date
Projected Q-End
$845K
at current run rate
Quarter landing at current run rate
43% of plan
laminir · Weekly Brief · Confidential
Excerpt
Illustrative brief excerpt
What Laminir is
Pulse replaces the manual assembly. Agentic AI analyses every commercial lever for you and delivers one executive read before the week starts — the position, the tensions and the decisions, already framed. Ground's AI agents handle the buying and merchandising work that follows, each recommendation surfaced for your approval.
Strategic anchors connect every layer. Define your business direction once. They frame the weekly verdict in Pulse and constrain what Ground agents recommend.
Who it is built for
Apparel, accessories and footwear retailers.
Large enough to have real complexity across trading, buying and digital. Without a full planning function or BI team to make sense of it.
The problem
Answering it means waiting on multiple departments.
Trading
The revenue gap
Buying
The cover position
Digital
The paid numbers
Brand
The campaign response
Each with their own numbers. Each right about what they can see.
The aggregated view has to be assembled by hand.
Somebody spends days on it, often including Sunday night. And by the time it lands, the week is spent explaining the last one rather than deciding the next.
Laminir does the assembly. Every lever read together, every week, automatically — so the read is waiting when the week starts, and the time goes to the decision instead.
Beyond your own numbers
Your data tells you what happened. It doesn't tell you whether you're still relevant.
Laminir reads external market, trend and category signals alongside your trading data — so a soft week is read against what is actually happening in your category, not in isolation.
Trend direction
Signals are tracked by market and classified as emerging, accelerating or fading — so a category lifting elsewhere is visible before it shows in your own numbers.
Category relevance
Whether your range still sits where demand is moving. A category holding sell-through while the market accelerates around it is a relevance problem, not a trading one.
Read against the week
Signals are read alongside your trading position, so the brief can separate a demand problem from a range problem — and say which one you are actually looking at.
Demand windows
Your GTM calendar sits in the same read. A soft week ahead of a major activation carries a different decision than the same week with nothing planned behind it.
Anchored to strategy
An emerging trend is only worth chasing if it fits what the business committed to. Signals are framed against your strategic anchors rather than surfaced as noise.
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Why Laminir
Not a chatbot. Not a dashboard. An agentic decision layer your business has never had.
The compounding advantage
Upload your data. Set your strategic anchors. Receive your first brief.
Patterns emerge. Initiative progress is tracked across the quarter. Momentum changes how trajectory is read.
Quarter closes. Drift was caught at week six. Two problems were surfaced before they became material.
A full year of trading context. Seasonal patterns understood. When the board asks why a decision was made in March, the context is already there.
Laminir
See the whole picture. Act on what matters.
No data warehouse. No implementation project. No BI team.