One canonical data model
Every connected system feeds one consolidated dataset, so reporting stops depending on which export someone used.
Systems integration that connects your business software
Sales sit in one system, stock in another, purchasing in a spreadsheet, and finance somewhere else again. We build the middleware that joins them into one data model every report can read from, and we run it for you afterwards.
Integration layer
The problem
Every system is right, and the totals still disagree
Each platform reports accurately on its own terms. The ERP knows its ledger, the warehouse knows its stock, the channels know their orders. None of them knows about the others, so any question spanning two of them ends in a spreadsheet.
Nothing dramatic goes wrong. There is just an export somebody dreads every Monday, a figure that is three days old before anyone acts on it, and a slow erosion of trust in numbers that never quite agree.
Point-to-point fixes make it worse over time. Connect five systems directly and you have twenty connections to maintain, each one breaking independently. A middleware layer replaces that with one model, built so it survives the next platform you add and the ERP you have not bought yet.
How it works
From disconnected systems to one data layer
We connect sources one at a time, prove each against real data, and leave you with infrastructure rather than a set of scripts.
01
Map how your data actually moves
Every system holding operational data, what it holds, who owns it, which one is the source of truth for each record type, and where the same thing is recorded twice. Most operations find at least one surprise here.
02
Design the integration layer
Canonical data model, sync patterns per source, error handling, and reconciliation rules. Batch, scheduled, real-time, or event-driven, chosen per system, not applied uniformly.
03
Build and connect
One connector per system, using scoped credentials you control. Direction is a design decision: read-only where safety matters, two-way where your operation needs data flowing back.
04
Test, migrate, go live
Integration testing against real data, historical migration where needed, then a phased cut-over instead of one big switch.
05
Run it, and keep it running
Monitoring, alerting, quarantine for anything that fails a rule, and ongoing support. The same team that builds it operates it.
What's included
Infrastructure, not a set of scripts
Built as a platform, so the second, fifth, and tenth system cost less than the first.
Sync that fits each system
One-way, two-way, or selective sync, in real time or on a schedule, chosen per system. Read-only where a system must stay untouched, two-way where the business needs to write back.
Entity and multi-company aware
Every record attributed to the correct legal entity, so multi-country and multi-company groups report correctly instead of approximately.
Nothing fails silently
Records failing a rule are quarantined and visible, never dropped. You learn about it from an alert, not from a wrong number three weeks later.
API layer and documentation
Where you need other systems or partners to consume the data, we expose a documented API instead of another export.
Your choice of hosting
Managed by us in the cloud, deployed into your own infrastructure, or hybrid, depending on your data residency and security requirements.
Security and access control
Scoped, revocable credentials held in a secrets manager, encryption in transit and at rest, least-privilege access, audit trails, and no personal data in logs.
Built to be handed over
Documented, tested, and structured so your own team can take it on if you ever want to.
Ready for AI
With every system feeding one clean dataset, AI assistants, summaries, and alerts work from reliable data instead of scattered exports.
What we connect
If it has an interface, it can be connected
01
ERP and finance
SAP, Microsoft Dynamics, Oracle, NetSuite, Odoo, Xero, QuickBooks, and in-house finance systems.
02
Warehouse and logistics
WMS platforms, third-party logistics providers, courier and freight forwarder APIs, and fulfilment services.
03
Retail and point of sale
POS platforms, store systems, and in-house retail applications across multiple locations.
04
E-commerce and marketplaces
Shopify, Magento, WooCommerce, BigCommerce, and marketplaces including Shopee, TikTok Shop, Lazada, and Amazon.
05
CRM, support, and marketing
Salesforce, HubSpot, Zendesk, Klaviyo, and the rest of the customer stack.
06
Data and reporting
Data warehouses, BI platforms, and analytics tools that need a clean, consistent feed.
07
Legacy and on-premise
Older systems, file-based exchange, SFTP, EDI, and databases that were never designed to be integrated.
08
Anything with an API
Custom connectors where no standard integration exists, built against whatever interface the system offers.
Where it helps
Where integration pays for itself
Multi-channel retail and commerce
Marketplaces, webstores, and physical stores reporting into one place, with stock and sales that reconcile.
Multi-entity and multi-country groups
Operations spanning several countries or companies, where every transaction has to land against the right entity.
Pre-ERP, mid-ERP, and post-ERP
Connect what you run today, rewire to the ERP when it arrives, and integrate around it afterwards without rebuilding the reporting layer.
Mergers and system consolidation
Two businesses, two stacks, one set of numbers required before anyone has agreed which platform wins.
Reporting and BI foundations
A clean, consistent dataset is the prerequisite for dashboards anyone trusts. Most BI projects fail here rather than at the dashboard.
Automation that spans systems
Workflow automation only works when the systems underneath can actually talk. Integration is what makes the rest possible, including the AI automation we build on top.
Real-world example
Ten systems, one data model
A multi-channel retail group operating across two countries, running marketplaces, a webstore, retail POS, two warehouses, a finance system, and a purchasing spreadsheet, with no single view of any of it.
Before
- Reports were built by exporting from each platform and merging by hand, so figures were days old on arrival.
- Stock positions disagreed between warehouse and POS with no way to explain the gap.
- Nothing attributed transactions to the correct legal entity, so country-level numbers were estimates.
After
- Every system feeds one entity-tagged model on an agreed schedule, unattended.
- Each source reports its own position, visibly, instead of a merged figure nobody can trace.
- Any number can be traced back to the source record and the sync that produced it.
What to expect
One data model every report reads from
10+
Systems in a single integration layer
1
Data model, not ten exports
24/7
Monitored and alerted
100%
Of figures traceable to a source record
FAQ
Questions, answered
What teams ask us most about systems integration.
Not unless you want us to. Integration usually means your platforms stay exactly as they are and keep doing what they do well. We connect them and consolidate what they hold.
Keep exploring
Related solutions
Let's build
Build the system underneath it all
Book a consultation. We'll map the systems you run today, show you where the data breaks, and set out what connecting them properly looks like.
connect@codexgate.comMalaysia · Hong Kong · Singapore