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Enterprise AI Still Depends On Data Quality
While much of today’s AI market focuses on selecting the right large language model, organisations are increasingly recognising that data quality plays an equally important role.
According to Iris.ai, a large share of enterprise knowledge remains stored in documents, reports and internal systems that are difficult for conventional data platforms to process. Its technology is designed to organise and contextualise this information before it is used by AI applications, allowing organisations to reuse business knowledge across multiple departments instead of preparing data separately for every project.
The company says its platform has been applied across industries including manufacturing, healthcare, financial services, telecommunications and the public sector.
AWS Collaboration Focuses On Enterprise Deployment
As part of the collaboration, the platform integrates with several AWS services, including Amazon Bedrock, Amazon OpenSearch, Amazon SageMaker and Amazon EC2 GPU instances.
The goal is to help organisations develop AI applications that can work with structured business knowledge while supporting governance and compliance requirements.
According to the company, the platform is designed to provide traceable AI outputs and aligns with standards including GDPR, the EU AI Act and ISO 27001.
The software is also available through AWS Marketplace, simplifying procurement for organisations already using AWS infrastructure.
Matthew Thomson, Director of EMEA Startups at AWS, said enterprise customers are increasingly looking for ways to unlock knowledge stored across years of documents and internal systems rather than focusing solely on AI models.
Victor Botev, Co-Founder and CTO of Iris.ai, believes the quality of enterprise knowledge remains one of the biggest factors affecting AI performance.
“The model is only as good as the knowledge it has access to.”
He argues that even advanced language models can produce unreliable results when enterprise information is incomplete, outdated or poorly structured.
A Growing Focus On AI Governance
The announcement reflects a broader trend across enterprise AI, particularly in regulated industries where organisations face stricter governance, compliance and data sovereignty requirements.
Financial institutions preparing for the Digital Operational Resilience Act (DORA), manufacturers modernising legacy systems, and healthcare organisations managing multilingual documentation are among the sectors expected to increase AI investments over the coming years.
Looking ahead, Iris.ai plans to expand its presence in North America, Saudi Arabia and Europe while further integrating its platform with AWS services such as Amazon Bedrock AgentCore, Amazon QuickSight and Amazon OpenSearch.
