Isolated pilots
The model produces results, but employees still move context and data manually.
AI integration & architecture
Integrate AI into existing systems and workflows.
Integrate AI with CRM, ERP, Microsoft 365, documents, telephony, and APIs while preserving security and operations.
01
For companies whose AI must work beyond a prototype.
AI integration connects models and applications with the data, identity, and systems where work actually happens. CodeXaureus uses APIs, events, and secure data access without replacing core systems unnecessarily.
For IT and business owners connecting AI to CRM, ERP, helpdesk, documents, or internal APIs while preserving system ownership and access control.
02
Common integration barriers
Inconsistent data
Sources, permissions, and data quality are not ready for dependable operations.
Unclear system ownership
No decision defines which system owns data, status, and approvals.
03
AI becomes part of the existing operation
Keep core systems authoritative
Add AI without unnecessarily replacing CRM, ERP, or helpdesk platforms.
Move context safely
Roles, data minimisation, and interfaces limit which information is available.
Reduce manual handoffs
Results and status reach the system where work continues.
Manage change
Versioned interfaces, tests, and observability reduce operational dependencies.
Scope
Integration services
Specific enough for a sound decision and bounded enough for dependable delivery.
System & data map
Sources, interfaces, flows, identities, permissions, and constraints.
Secure integration layer
APIs, webhooks, queues, retrieval, secrets, tenancy, and controlled tool calls.
Production operations
Load tests, fallbacks, monitoring, cost limits, versioning, and rollout.
05
Integration without big-bang risk
- 01
Map boundaries
Document sources, authoritative systems, roles, events, and data flows.
- 02
Define contracts
Specify APIs, data models, failure cases, and service boundaries.
- 03
Connect incrementally
Start with one bounded flow and test real load and exceptions.
- 04
Secure operations
Establish monitoring, retries, fallbacks, and incident owners.
06
Data control is decided before model choice
Depending on requirements, we design EU cloud, private, or near-on-premise architectures. Data minimisation, purpose limitation, access control, and logs follow the full data flow.
Common questions
Questions to answer before making a decision.
How is AI integrated into existing IT?+
Map the workflow, sources, identities, and desired actions first. Then build an integration layer using existing APIs, events, or secure adapters so core systems can remain stable.
Can AI be integrated without replacing core systems?+
Often, yes. A separate orchestration layer can read data, return results, and control approval while existing systems remain authoritative. Stable interfaces and bounded permissions are essential.
Which systems can be connected?+
Typical systems include CRM, ERP, helpdesk, Microsoft 365, document stores, websites, telephony, and internal APIs. Feasibility depends on interfaces, data formats, and security requirements.
How are model and API costs controlled?+
Through model routing, caching, context limits, volume controls, and cost monitoring. Cost per successful task is measured during the pilot and treated as a production metric.
Connect the systems
Where does your AI pilot stop before the real workflow?
We assess interfaces, data flows, and operating requirements and outline a bounded integration path.