Inventory accuracy
63%
Multi-store retail runs on 63% accurate stock data. Every decision downstream inherits the error.
Polestar, 2024
[ Waitlist · Design partners only ]
Agentic retail intelligence
The agentic retail intelligence POS system.
Kwanta is a POS powered by advanced analytics and AI agents — purpose-built for fashion, cosmetics, and specialty retailers. Run it as your primary POS, or embed the analytics layer into the stack you already have.
Piloting with retailers in Kazakhstan & Poland
Mir Kosmetiki Partner #2 Partner #3 Partner #4
The retail intelligence gap
Dashboards don’t decide.
The industry baseline is a category in pain. Kwanta exists to close it.
Cart abandonment
49%
Half of omnichannel shoppers bail on friction — most of which a real-time signal layer would catch.
Polestar, 2024
Say agents are essential
75%
Three in four retailers now believe agentic AI is required to stay competitive.
Polestar, 2024
Piloting or evaluating
96%
The bus is leaving. 43% already in pilot, 53% actively evaluating. The question is not if — it is who ships first.
Polestar, 2024
Why now
The retail OS is unbundling.
Legacy retail software — the ERP-plus-POS layer most multi-store operators run — centralized inventory and reporting a decade ago. That problem is solved. The next wedge is prescriptive intelligence: what to reprice today, which SKU to reorder, which promo will cannibalize next month’s margin.
Fashion, beauty, and specialty operators have been served generic retail software for 20 years. Their disciplines — assortment depth, seasonality, promo cadence, SKU-level loyalty — never got purpose-built intelligence. Kwanta is that layer.
We start at the POS because it’s where every decision eventually has to land. Capture the signal there, model it once, let agents act on it — by SKU, by store, by segment, by campaign.
What Kwanta does
One layer. POS in, decisions out.
POS + data foundation + agent orchestration
Retail telemetry cleaned at the point of sale and exposed to every agent. Category intelligence, SKU-level economics, and shopper-level signal — modeled once, shared everywhere.
Analytics-ready data from day one
Every transaction, promo, stock move, and loyalty event lands structured. No data project needed before you get your first answer on SKU-level margin or category mix.
Always-on next-best-action
By SKU. By store. By shopper segment. By campaign. Decisions the agents can propose, and — where you allow — autonomously execute.
1
layer for category, pricing & promo
24/7
always-on digital analysts
6
specialized agents
Save hours every month — start with a click.
No spam · Fashion & cosmetics retailers only
Agent roster
Six agents. One operating rhythm.
Each agent owns a discipline the retailer normally hires, buys a dashboard for, or ignores. Together they form a continuously running commercial team.
Category manager
Assortment observer. Monitors planogram performance, identifies SKU-to-SKU relationships, and recommends category rotations in hours — not quarterly reviews.
RGM
Channel optimizer. Rebalances inventory and adjusts promotions by store and segment daily. Dynamic pricing suggestions with a margin floor you set.
MMM / Media
Attribution model for offline × digital. Incrementality-tested media mix so the marketing spend that actually moved the P&L is the spend you scale.
Daily analyst
Stock tracking and demand signal. Surfaces emerging trends and low-stock alerts before a human would open a dashboard.
Finance analyst
Margin and working-capital analyst. Reads the store P&L daily, flags drifts, recommends the next three actions in order of dollar impact.
Client manager
Customer experience agent. Sequences, loops, and promos composed in-language. Runs lifecycle campaigns with persistent context — not a chatbot, a relationship layer.
Models
Six models, running behind the agents
Every agent draws from a shared library of retail models, tuned for multi-store fashion, beauty, and specialty operators.
ElasticityCannibalizationHaloIncrementalityPromo efficiencyLoyalty analytics
For the retailer
Outcomes you can put in the P&L.
Kwanta is sold on what it changes in the business — not on features. Four places the system reliably moves the number.
Sharper pricing
Elasticity-aware prices by SKU × store, without the pricing committee.
Smarter promotions
Promo efficiency and incrementality measured continuously — not after the quarter.
Cleaner categories
Assortment decisions backed by halo and cannibalization, not gut feel.
Loyalty lift
Segmented sequences in the customer’s language, operated by the Client manager agent.
Built for every category
Purpose-built for fashion, beauty, and specialty retail.
“Kwanta replaces the guesswork in pricing, promo, and category. For the first time we see what each SKU is actually doing — in one place.”
MK
Mir Kosmetiki
Design partner · Multi-store cosmetics retailer, Kazakhstan
Founders
Retail operators. Data engineers. One team.
Kwanta is built by people who have spent years running multi-store retail P&Ls and shipping production data platforms. We know why the last attempt failed.
AI
BA
Get on the waitlist.
We are selecting the first 10 design partners in KZ and Poland. If you run multi-store fashion, cosmetics, or specialty retail and you want the agents before your competition does, tell us.