Enterprise System Integration
AI systems are only as useful as the data they can access and the systems they can act on. We build the connective tissue — bidirectional integrations between your AI stack and your ERP, DMS, CRM, and legacy platforms.
ERP & DMS Connectors
Bidirectional integrations with SAP, Oracle, Microsoft Dynamics, SharePoint, OpenText, and custom DMS platforms. AI agents can read, write, and trigger workflows in your business systems without manual data re-entry.
API Gateway & Protocols
RESTful APIs for web-facing services and gRPC for high-performance internal communication. Built-in rate limiting, request queuing, circuit breakers, and retry logic — production-grade from day one.
SSO & Identity Integration
Integration with your existing identity providers — Active Directory, LDAP, Azure AD, Okta, SAML 2.0, OpenID Connect. Users authenticate once, and AI services respect your organisation's access model.
Audit Logging & Compliance
Every API call, data access event, and AI decision is logged with full context: who, what, when, from where. Tamper-evident logs suitable for GDPR, HIPAA, SOX, and internal compliance requirements.
The Integration Challenge
Enterprise AI does not exist in isolation. An AI agent that can reason about procurement decisions is only useful if it can actually read purchase orders from your ERP, check inventory levels, and create new orders when conditions are met. A document intelligence pipeline is only valuable if extracted data flows directly into your accounting system without manual re-entry. A RAG knowledge base is only effective if it can access documents stored across SharePoint, Confluence, and your custom DMS.
The integration layer is where most enterprise AI projects succeed or fail. A technically impressive model that cannot connect to your business systems is a demo — not a production tool. We build the integration layer as a first-class component of every AI deployment, not as an afterthought.
Systems We Integrate With
Integration Patterns
- —Synchronous request-response: REST or gRPC APIs for operations where the AI needs an immediate answer — looking up a customer record, checking inventory, validating a document against master data. Request timeouts, circuit breakers, and retry logic are built in.
- —Event-driven (async): Kafka or RabbitMQ message streams for high-volume, loosely coupled workflows. When a new invoice is processed, an event is published. Downstream consumers (ERP posting, notification service, audit logger) process it independently. This pattern handles throughput spikes gracefully.
- —Batch processing: Scheduled jobs for operations that do not require real-time execution — nightly report generation, weekly model retraining triggers, monthly compliance data exports. Batch jobs run during off-peak hours and include failure recovery and restart capabilities.
- —Webhook and callback: For systems that support outbound notifications — when a status changes in your ERP or a new document arrives in your DMS, a webhook triggers the AI pipeline. This eliminates polling and ensures near-real-time responsiveness to upstream events.
Security and Compliance
Every integration point is a potential security surface. We implement defence in depth across all connectors: TLS 1.3 for all data in transit, OAuth 2.0 or service account credentials with least-privilege scoping for API authentication, request signing for tamper detection, and comprehensive audit logging that records every data access event with full context (who, what, when, from where, why). For regulated industries, audit logs are stored in tamper-evident format and retained according to your compliance requirements — GDPR (data access records), HIPAA (PHI access logs), SOX (financial system audit trails). All integration components run within your network perimeter alongside the AI services they connect.
Technology Stack
Integration protocols and messaging infrastructure