Every system tells a different story.
POS, ERP, e-commerce and planning all describe the same week with different numbers. Reconciliation eats the analyst’s morning.
01Data Layer
Your retail data,
finally speaks one language.
Unify every system in your retail stack — product, location, time — at any granularity. One canonical model, ready for every decision.
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The data problem
Fragmented data breaks every decision.
Every retailer has the same data scattered across the same dozen systems — none of which agree with each other.
Attributes never match.
A product is a “SKU” here, a “reference” there, a “code-article” in finance. Joining anything requires custom mapping that breaks every quarter.
Granularity is always wrong.
Sales by store-day exist somewhere. Stock by SKU-store at noon exists somewhere else. The decision you need is always at a granularity nobody computes.
How it works
Inside the Data Layer.
Three stages. One canonical output.
01IngestActive
Bring every system into Solya.
Native connectors for the retail stack — ERP, POS, OMS, WMS, e-commerce, finance — plus a typed API for anything custom. Schema drift, rate limits, late files: handled.
- 30+ native retail connectors out of the box
- Streaming and batch, file-based or API
- Backfills and reprocessing with one click
01 · Ingestlive
ERP
POS
OMS
WMS
E-com
Finance
↓ STREAM
Solya ingestion
6 systems · 1.2M events / day
02PrepareActive
Turn messy data into clean decisions.
Reconcile catalogs, de-duplicate stores, align time grains, repair gaps. Every transformation versioned, every record traceable to its source.
- Catalog reconciliation across systems
- Stock and sales unified at SKU·store·day
- Per-field provenance, every value traceable
02 · Preparereconciling
Catalog match
ERP · ART-2417→POS · sku_241798%
ERP · ART-9001→POS · sku_9001100%
ERP · ART-3144→POS · sku_3144-v284%
Items
42,318
Stores
42
Gaps
17
03DeliverActive
One source of truth for every team.
A canonical retail model — item, store, customer, stock, sales — exposed as typed APIs, materialized views, and feature streams for the intelligence layer.
- Typed SDK + GraphQL + warehouse views
- Live updates on the same schema, no drift
- Audit log of every read and write
03 · Deliverlive
GET/v1/items/2417REST
POST/graphqlGraphQL
SQLwarehouse.items_v2Views
Same schema · same definitions
Capabilities
The foundation for every retail decision.
Six things the data layer gives you on day one.
Native retail connectors
ERP, POS, OMS, WMS, e-commerce, finance, planning. Plug and run.
Canonical retail model
Item, store, customer, stock, sales — one schema across your whole network.
Continuous reconciliation
Late files, schema drift, conflicting masters: handled without analyst time.
Per-field provenance
Every number you see traces back to its source system and timestamp.
Streaming + batch
Real-time for ops, batch for analytics. Same data, same definitions.
Typed APIs
TypeScript SDK, GraphQL, warehouse views — pick what fits each consumer.
What you can do with it
All case studiesThe data foundation for every retail team.
Real teams already running on the data layer — replacing CSV exports, weekly reports and reconciliation meetings.
Fit into the runtime
The foundation of the Solya runtime.
Data feeds intelligence, intelligence drives orchestration, orchestration delivers apps. Everything stacks.
Retail was never built for AI.
We’re rebuilding it.
“Solya’s data infrastructure did in one month what our last data project failed to do in five years.
Stop watching the dashboard.
Start running the decisions.
A 30-minute walkthrough on your own data shape. We’ll show what Solya would decide for your network this week.