27 Feb 2026

Tech consultancy AND Digital, has partnered with conemis to help businesses to deliver security-focused data transformation and cloud projects for enterprises. 

Details about the transformation

The combined offering of AND Digital and conemis enables enterprises to address both the strategic and technical dimensions of transformation, from architecture and product design to scalable, secure data transition and consolidation.

As enterprises increasingly invest in AI, automation, and industry-specific cloud solutions, the need for clean, well-structured, and securely governed data is increasingly critical.

Partnership benefits

The partnership will provide enterprises with end-to-end modernisation support, from strategy and design to execution, enterprise-scale data migration capabilities to handle millions of records, de-risked transition, and AI-ready foundations to support intelligent automation and advanced analytics.

“Getting enterprise data truly AI-ready remains the hardest part of AI adoption across industries” said Kenn van Huen, Chief AI Officer of AND Digital. “Partnering with conemis strengthens our ability to deliver secure, scalable, and future-proof AI transformations for our clients.”

The two companies will also help organisations to modernise their application landscapes, reduce migration risk, and unlock greater value from their data methodology and platform. 

Expert insights

Omid Afaghi, co-founder and Managing Director of conemis, added, “This partnership allows us to combine deep digital delivery expertise with our proven migration platform, helping enterprises move faster, reduce complexity, and prepare their data foundations for the next generation of cloud and AI solutions.”

“I’m inspired by the vibe and deep expertise of AND Digital and look forward to bringing our combined strengths to joint customers across the U.K., Europe and North America. Organisations can rely on AND Digital’s close client relationships, and now benefit from the strong conemis technology underpinning data transformations.”