Our services
AI in your DXP
We integrate AI assistance directly into content management platforms like Sitecore, Sanity, Optimizely, and Contentstack. Content editors receive AI support for match reports, product pages, and campaign copy, plus intelligent search, automated tagging, and personalisation engines that accelerate editorial workflows.
AI in your PIM
We automate product data enrichment, attribute generation, and taxonomy management within Akeneo, inRiver, and similar platforms. Product teams spend less time on manual data entry and more time on assortment strategy and product positioning that create business value.
AI in your DAM
We implement intelligent asset tagging, rights management, and usage suggestions within Bynder, Widen, and other digital asset management systems. Media libraries become self-organising, enabling editors to find required assets without time-consuming searches.
AI search and semantic discovery
We build search capabilities that understand user intent rather than just matching keywords. OpenAI embeddings and vector search integration with Elasticsearch or Azure AI Search creates intelligent semantic discovery within existing platform architectures.
AI in your DXP
We integrate AI assistance directly into content management platforms like Sitecore, Sanity, Optimizely, and Contentstack. Content editors receive AI support for match reports, product pages, and campaign copy, plus intelligent search, automated tagging, and personalisation engines that accelerate editorial workflows.
AI crawler governance
We help you control which AI bots access your platform content, and which don't. This protects your content investment whilst maintaining discoverability in AI-powered search environments, balancing content protection with AI visibility.
Let's discuss your AI needs
Our approach to embedding AI in your platform
Most platforms already contain more AI capabilities than teams currently use. Our approach begins not with technology selection but with workflow analysis: identifying where teams lose time to tasks AI can handle. From this analysis, we build integrations that fit existing architecture without requiring migrations or major system changes.
Use what you already have
We start by examining current stack capabilities and identifying unused potential. At Enexis, 80% of AI value was already available in Sitecore; it required configuration and integration — not new technology. Platform-native AI capabilities from Sitecore, Sanity, Optimizely, and other platforms often provide shorter time-to-value than custom builds.
Integrate into workflow, not alongside it
AI that operates outside existing workflows remains unused. We integrate AI capabilities directly into interfaces teams access daily, such as CMS editing screens, PIM product management, DAM search interfaces. Adoption becomes architectural rather than requiring training programmes.
Production-ready from day one
AI-in-stack implementations only succeed with reliable production operation including monitoring, retry logic, alerting, and clear SLAs for AI dependencies. We build production pipelines that handle real user data variability and maintain operation through dedicated CloudOps monitoring.
Why work with iO?
Platform depth combined with AI breadth
We maintain active AI-in-stack projects across Sitecore, Sanity, Optimizely, and Prepr. This combination of platform knowledge and AI engineering expertise enables integrations that work rather than stalling at architecture boundaries.
Platform-native to custom: choosing the right fit
Not every AI requirement fits within default platform offerings. We make conscious choices between platform-native AI and custom builds based on your context, stack, and team needs.
Production readiness as starting point, not finish line
Sandbox demonstrations reveal nothing about AI performance under real platform load with actual user data and variability. We establish AI workflows as production dependencies with monitoring, alerting, and operational safeguards appropriate for live platforms.
AI your teams actually use
Teams adopt AI naturally when it enhances existing workflows. We've never required change management programmes for platform-native AI adoption because we integrate capabilities at decision points within familiar tools.
