The inventory layer
Turn ERP data into actionable insight with a Standard Inventory Model.
The inventory truth that runs your business is scattered across disconnected ERPs, depots and spreadsheets. We capture it, normalise it into one Standard Inventory Model, and build solutions with AI that turns raw records into insight and accelerate decision making.
ERP / WMSOperational stock data
SuppliersCatalogues & part feeds
DepotsLocal counts & movements
SpreadsheetsScattered, stale, manual
→
inmydata
Standard Inventory Model
∑
→
AgentsAsk anything about stock
DecisionsReal-time, trusted
ReportingOne source of truth
CompoundingLearns through use
Connects to the systems your business already runs
QADSAPOracleMicrosoft DynamicsNetSuiteInforSnowflakeDatabricks
The problem
Most inventory decisions are made on data no one trusts.
For decades we've computerised stock records brilliantly — in isolation. The single, reconciled picture of what you actually hold, where, and under which name has never lived in one system. Until now.
Data Quality - Poor and inconsistent data quality, categorisation and translations
Inaccurate Inventory - Stock levels do not match reality causing poor decisions and lost inventory
Overstocking - Excess Inventory ties up cash, increases storage costs and can lead to obsolete stock
Slow Inventory Turnover - Products sit on shelves for far too long, increase carrying costs and reducing profitability
Supply Chain Disruption - Delays from suppliers, shipping issues, or geopolitical events create uncertainty in stock availability
Poor Warehouse Organisation - Staff spend too much time locating products, increasing picking errors and labour costs
Returns Management - Returned Items are often slow to inspect, restock or dispose of affecting inventory accuracy
Inventory Shrinkage - Theft, damage, administrative mistakes and supplier fraud reduce available inventory.
Long Lead Times - Extended supplier lead times require larger safety stock, increasing inventory investment.
Batch and Expiry Management - Particularly in Food, Pharmaceuticals and healthcare tracking expiry dates is essential to minimise waste and ensure compliance
Manual Processes - Spreadsheets, paper based systems and staff turnover increase human errors due to lack of knowledge transfer
Your data is locked away.
ERPs, legacy systems, depot databases and supplier feeds. Getting inventory data into a form AI can use — securely, in real time, with a shared definition of a "part" — is where most projects die.
Your records never agree.
The same item carries five part numbers across five systems. Units, currencies and classifications drift. What is written down is scattered, duplicated and stale.
We solve both. One Standard Inventory Model — queryable, reconciled, and built to get smarter through use.
◆
Mapping AgentAligns source schemas to the model
running⊕
Matching AgentResolves duplicate & equivalent SKUs
running⚖
Reconciliation AgentFlags & resolves conflicts
running✦
Interpretation AgentExplains every change in plain language
running
Inventory AI that learns through use
A model that improves the more your business runs on it. Specialised agents capture how your teams reconcile stock, then apply that judgement automatically — and explain every decision they make.
- ✓ Agents for mapping, matching, reconciliation and interpretation
- ✓ Always-on — the model never drifts out of date
- ✓ Every action is explainable, versioned and auditable
- ✓ Human-in-the-loop review for low-confidence decisions
How it works
From scattered records to a single source of truth.
01 · CONNECT
Plug in your systems
Pre-built connectors for SAP, Oracle, Dynamics, NetSuite and Infor. Live or batch.
02 · NORMALISE
Agents unify the data
Agents cleanse, dedupe and map every record into one canonical structure.
03 · MODEL
Build the Standard Inventory Model
A single, trusted model spanning every system, depot and region.
04 · INTERPRET
Decide with clarity
Explainable insight flows back into your ERP, agents and BI tools.
Sources
Sits on top of the systems you already run.
QADQAD
SAPS/4HANA · ECC
OracleFusion · EBS
Dynamics365 · F&O
NetSuiteERP
InforM3 · LN
SnowflakeWarehouse
DatabricksLakehouse
Power BIReporting
#
TableauReporting
KafkaStreaming
REST / APICustom
CSV / EDILegacy
Track record
Built on over two decades of data infrastructure. Rebuilt AI-first.
Data infrastructure since 2003. AI systems since 2022. We don't experiment — we build with AI every day, in production, and help you put a trusted inventory model at the centre of your business.
20+
years in data infrastructure
48M
records unified into the model
99.1%
conflicts resolved automatically
8×
faster post-merger data unification
"We had five ERPs from a decade of acquisitions and no single view of stock. inmydata gave us one trustworthy Standard Inventory Model in under a quarter — every team finally works from the same numbers."
Diana Marsh · Group VP Supply Chain, Fortune 500 manufacturer
Let's talk about what you're building.
Whether you've a clear project in mind or you're exploring where a Standard Inventory Model fits, we're happy to talk. No pitch decks, no pressure.