Ai Integrator
Services

Integration of leading public Ai solutions from vendors such as Microsoft Azure Ai, AWS Ai Services, Google Cloud Ai, OpenAI, Anthropic, and other market-leading providers. We manage the entire integration lifecycle including vendor evaluation, licensing negotiation, deployment configuration, API integration, security hardening, and performance optimisation to ensure seamless operation within your enterprise environment.

Deployment and integration of private, proprietary Ai models tailored to your specific industry, data, and use cases. This includes on-premises model hosting, private cloud deployment, custom model fine-tuning, secure data pipelines, and integration with sensitive enterprise data sources while maintaining strict data sovereignty, privacy controls, and regulatory compliance requirements.

Seamless integration of Ai capabilities with your existing enterprise systems including ERP (SAP, Oracle, Microsoft Dynamics), CRM (Salesforce, Dynamics 365), databases, data warehouses, business intelligence platforms, workflow systems, and legacy applications. We ensure bidirectional data flow, real-time synchronization, proper error handling, and maintain system integrity throughout the integration process.

Alignment of Ai solutions with your current and future target operating models. We integrate Ai capabilities into existing business processes, workflows, organisational structures, governance frameworks, and decision-making hierarchies. This includes process redesign, change management support, training delivery, performance monitoring, and continuous optimisation to ensure Ai enhances rather than disrupts operations.

Integration across hybrid cloud, multi-cloud, and on-premises environments. We design and implement architectures that leverage the optimal deployment model for each Ai capability, whether that's public cloud for scalability, private cloud for sensitive workloads, or on-premises for regulatory requirements. This includes API gateway management, data residency compliance, network security, and unified monitoring across all environments.

Implementation of advanced CI/CD pipelines for Ai and ML models with comprehensive MLOps and AIOps capabilities. We continuously integrate, deploy, test, and monitor ML models throughout their lifecycle, ensuring optimal performance and reliability. Our approach includes automated model training pipelines, versioning and registry management, automated testing frameworks, performance benchmarking, A/B testing, canary deployments, model drift detection, real-time monitoring and alerting, automated retraining triggers, and intelligent rollback procedures. This ensures your Ai solutions evolve continuously with minimal disruption while maintaining high quality and performance standards.

Integration of comprehensive security controls, compliance frameworks, and governance mechanisms into all Ai implementations. This includes identity and access management, data encryption (at rest and in transit), audit logging, regulatory compliance automation (GDPR, HIPAA, SOC2, etc.), ethical Ai controls, bias detection and mitigation, and incident response procedures tailored to Ai-specific risks and requirements.

End-to-end delivery of Ai programmes and projects from initial design through to production deployment and ongoing support. We provide experienced programme managers, solution architects, integration specialists, and change management experts who work alongside your teams to ensure successful delivery. Our approach includes agile methodologies, stakeholder engagement, risk management, quality assurance, and knowledge transfer to build internal capability.

Integrate AI solutions with sustainability at the forefront using our Green AI Benefits Calculator to measure and optimize environmental impact throughout implementation. We evaluate energy-efficient model architectures, optimize compute resource utilization, implement carbon-aware scheduling, and select green cloud regions to minimize carbon footprint. Our approach provides quantifiable sustainability metrics demonstrating reduced energy consumption, lower emissions, and improved resource efficiency - supporting your ESG objectives while delivering high-performance AI capabilities.