Enrichment thatreasons, not calculates.
Maestro doesn't derive static fields. It reads your data and reasons over it — turning raw products, orders, and customers into deep, living context. And because it's agentic, it enriches whenever it fits, continuously, never on a batch schedule.
inferred by reasoning · not present in the raw fields
Calculated fields describe the past. Reasoning explains what to do next.
Traditional enrichment computes static scores and segments from what already happened. Maestro reads the same data and reasons over it — inferring intent, context, and the next right move that no formula can produce.
Calculated fields
static · rule-based
- RFM score = 4.2
- Segment: “High value”
- Churn probability: 0.63
- Days since last order: 41
- Lifetime value: $1,240
Numbers you still have to interpret. They tell you that something is true, never why — or what to do about it.
Maestro reasoning
contextual · living
- Barrier-repair routine anchored on CeraVe; reorder window closing — cross-sell serums + SPF now.
- Premiumising from budget to mid-tier haircare; open to discovery, responds to ingredient stories.
- Household expanded (baby products entered basket) — lifecycle shift, not just a spend increase.
- Replenishment rhythm slipping 6 days late — early drift signal, still recoverable.
Context you can act on. Every attribute carries intent, timing, and the next right move — the signal a raw catalog and a scoring model can't contain.
One chain of reasoning, from product to person
Enrichment isn't a single step. It's a cascade — each layer built on the one before it, until a raw catalog and a purchase history become a living, decision-ready customer.
It starts with the product
Maestro enriches each product with reasoning
Before anything else, Maestro reads every product and reasons over it — inferring category, audience, use case, brand positioning, and consumption rhythm. These are contextual, semantic attributes the reasoning layer produces, not calculated fields you send.
Products meet people
It builds a living product × customer relationship
Enriched products don't sit in a table — Maestro connects them to each customer's real behaviour. What they buy, in what combination, at what intervals, and in what sequence becomes an evolving relationship between the catalog and the person.
A person takes shape
From that relationship, it generates a customer profile
Out of the enriched product × customer relationship, Maestro generates a customer profile — a synthesized view of who this shopper is: their motives, household, lifestyle, and relationship with your brand. It's created, not queried from a static CRM field.
The loop deepens
Then it enriches that new profile with data
The newly generated profile becomes its own subject of enrichment. Grounded in the enriched product × customer relation, Maestro layers on intent, lifecycle state, and behavioural momentum — a continuously evolving profile that feeds every downstream decision.
Watch raw data become contextual intelligence
Pick a category and an input. Everything on the right is inferred by Maestro's reasoning layer — none of it lives in the raw record.
Raw catalog input
Personal CareEnriched by Maestro
CeraVe Moisturizing CreamSemantic attributes
Usage Frequency
Consumable Type
Primary Concerns
Usage Context
Compatibility
Price Band
Seasonality
Reasoning layer — the signal your catalog doesn't contain
Replenishment Signal
Routine Role
Cross-Sell Logic
Retention Risk
Maestro enriches whenever it fits
There is no nightly job, no batch window, no schedule to wait for. Maestro is agentic — it decides when enrichment is needed and does it the moment a signal arrives, so context is never stale.
Batch enrichment
Runs on a fixed schedule. Between runs, decisions rely on context that's already out of date. New behaviour waits in a queue.
Agentic enrichment
Triggered by the event itself. The instant an order, product change, or behavioural shift arrives, Maestro re-reasons the affected context — nothing waits, nothing goes stale.
New order lands
Behavioural state re-interpreted.
Product upserted
Catalog re-reasoned in place.
Basket combination shifts
Relationship graph updates.
New customer appears
Profile generated on the spot.
Behaviour drifts
Intent + lifecycle re-scored.
Enrichment is the fuel for every decision
Reasoned, always-current context doesn't just sit in a profile — it makes every Maestro agent sharper, faster, and easier to trust.
Sharper cross-sell
Because products carry role and cross-sell logic, Maestro matches the next right product to each customer — not the statistically popular one.
Precise replenishment timing
Every product knows its depletion rhythm and every customer their reorder cadence, so refill prompts land in the window — not too early, never too late.
Decisions with a reason
Enriched context is the input to every Maestro agent. Each decision traces back to intent, lifecycle, and behaviour — reasoning, never a black-box score.
No new data pipeline to own
Enrichment runs internally on the data you already send. Attributes stay inside Replenit and power the engine — nothing to model, store, or maintain on your side.
Cold-start, warmed fast
Send 12-24 months of history at integration and the reasoning layer builds nuanced profiles immediately — enrichment begins the moment data lands.
Always current context
Continuous re-enrichment means every downstream decision reasons over the customer as they are today — not a snapshot from last week's batch run.
Give your decisions data that actually understands your customers
See how Maestro reasons over your catalog and order history to build living, decision-ready customer intelligence — on top of the stack you already run.