- Iris.ai builds a semantic-enriched AI knowledge foundation that gives models and agents accurate business context – addressing a gap that model choice alone cannot fix.
- Iris.ai’s data unification engine, Axion, has processed and contextualised more than 330 million documents across 68 languages, connecting to more than 50 data source types so synthesis across different business units becomes reusable at scale rather than rebuilt for each use case.
- AWS provides the enterprise-grade cloud and model stack; Iris.ai provides the trusted knowledge foundation, running natively on Amazon OpenSearch, Amazon Bedrock, EC2 GPU, and SageMaker – now available through AWS Marketplace.
- Iris.ai offers AI control for regulated industries – financial services, manufacturing, healthcare, and public sector – the platform delivers deterministic, auditable AI output with 96%+ accuracy aligned to regulatory compliance and data governance.
OSLO, Norway, May 11, 2026 – Iris.ai, a deep-tech turned AI software company providing a semantic-enriched knowledge foundation for agentic enterprises, is building a strategic collaboration model with Amazon Web Services (AWS) to advance its platform across regulated industries globally. One of the biggest challenges in driving AI adoption is building a trusted data pipeline that delivers accurate business context across an organisation’s business units – one that can handle complex industry and domain specific data and produce bespoke use cases reusable at scale.
For regulated industries, the bar is high: AI output must be deterministic and fully auditable to meet compliance, governance, and data sovereignty requirements. Companies can’t fully trust AI systems without governance, verification, and reliability. AWS provides the enterprise-grade cloud and model stack, while Iris.ai provides the trusted knowledge foundation that lets those models and agents operate with expert-level business context and logic, control, and governance.
A Decade Building What Enterprise AI Actually Needs
When Iris.ai’s research team started in 2015, the dominant conversation in AI was about algorithms. The company’s founding thesis was focused on democratizing deep knowledge -making expert-level research and discovery accessible to the teams who needed it the most. By 2017, the team had published WISDM, a framework for evaluating how well language models handle domain-specific knowledge, and the methodological foundation that still powers Iris.ai’s understanding of enterprise context today. In 2023, the European Innovation Council awarded the company an EIC Accelerator grant, the same cohort that funded Mistral AI.
Iris.ai starts from the contextualization of data first, before working with LLMs. Standard enterprise AI implementations fail because 60 to 80 percent of enterprise knowledge sits in formats that most data lakes and business intelligence tools cannot easily ingest and synthesize. Axion has processed and contextualised more than 330 million documents across manufacturing, telecommunications, financial services, healthcare, and public sector.
It has 50+ data source connectors, it extracts and contextualises content at expert-level precision, and produces reusable knowledge that AI agents can reason on reliably, delivering 96%+ precision and 4x speed across 68 languages. The result is a semantic knowledge layer infused by expert knowledge & ontology that teams build once and deploy across departments, use cases, and workflows that scale with trust. Development teams don’t have to rebuild their data pipeline every time, which increases the pace of AI innovation and adoption. Top use cases:
- 20x lower costs to extract and contextualize technical, domain-specific documentation across 68 languages.
- Accelerate AI innovation and adoption by 80% with a unified knowledge foundation.
- Reduce cloud migration and data modernization time by 40-50%.
Technical Integration with AWS
Iris.ai’s platform runs natively on Amazon OpenSearch, Amazon Bedrock, EC2 GPU, and SageMaker instances. On the AI development side, Iris.ai is also fully integrated with Amazon Bedrock AgentCore, giving enterprises enriched context and deterministic control over LLM outputs.
As a centralised knowledge layer, Iris.ai gives development teams structured, contextualised enterprise knowledge that your knowledge-infused agents can query, reason over, and act on. Full integration with Amazon Bedrock and Amazon QuickSight means teams can move from raw enterprise data to production-ready agents without rebuilding the knowledge layer for every new use case. Compliance and data governance are built into the pipelines by design – auditable outputs, full traceability, and alignment with GDPR, the EU AI Act, and ISO 27001. When purchased through AWS Marketplace, Iris.ai further simplifies procurement and helps customers draw down eligible AWS spend commitments.
Matthew Thomson, Director EMEA Startups of AWS, stated: “At AWS, we see customers shift from AI curiosity to AI commitment. And that demands partners who can unlock expert-level knowledge buried inside decades of documents, contracts, and data sources. Our collaboration with Iris.ai brings together their powerful knowledge extraction and contextualization capabilities with the security and agility of AWS. This means that enterprises can put their most valuable data to work with high-quality LLM outputs, faster migrations, sharper decisions, and AI that runs in production and drives real outcomes.”
Victor Botev, Co-Founder and CTO of Iris.ai, commented: “AWS powers the compute and the models. Iris.ai powers the knowledge those models reason on. Most enterprise AI conversations revolve around model choice. That focus isn’t wrong. But the model is only as good as the knowledge it has access to. If the knowledge layer is incomplete, outdated, or poorly structured, the output looks convincing right up until it becomes a production issue. Or a trust issue. For ten years we’ve focused on that layer.”
Expansion and Forward Outlook
Iris.ai is expanding deployments in the Kingdom of Saudi Arabia, deepening its presence in North America, and growing its European customer base. The focus markets for 2026 are financial services institutions preparing for DORA and EU AI Act compliance, manufacturers running complex cloud migration programs, and organisations in healthcare and life sciences managing large volumes of multilingual regulatory documentation.
The product roadmap extends Axion’s data unification capabilities and Neuralith’s knowledge agent orchestration layer, with tighter integration planned and joint production solutions with Amazon Bedrock AgentCore, QuickSight, and OpenSearch.
Press contact:
Iris.ai: contact@iris.ai
About Iris.ai
Iris.ai is an enterprise AI knowledge foundation company founded in Norway in 2015. Its platform – comprising the Axion data unification engine and the Neuralith agent orchestration layer – turns fragmented enterprise data into reusable, AI-ready knowledge that large language models can reason on reliably. The company is ISO 27001 certified, GDPR compliant, and EU AI Act compliant, and operates across AWS regions in Dublin, US East and West, and the Kingdom of Saudi Arabia. Iris.ai has been recognised as a Top 10 IBM Watson AI XPRIZE finalist (2020) and an EIC Accelerator recipient (2023).
