AdMaCom Qualifier: Winner Announced
From scientific literature to smarter manufacturing: POMA AI wins the AdMaCom 2026 Qualifier with MKS’ Atotech
How can AI turn the growing body of scientific and technical knowledge into practical improvements in materials and manufacturing processes? This was the challenge at the AdMaCom 2026 Qualifier organised by INAM in collaboration with MKS’ Atotech. POMA AI emerged as the winner, joining four other finalists working at the intersection of AI, materials science and industrial innovation.
Turning knowledge into industrial advantage
Materials and manufacturing industries generate enormous amounts of scientific and technical knowledge. Research papers, patents, technical publications and other documents contain insights that could help companies develop better materials, improve production processes and accelerate innovation. Yet turning this information into actionable knowledge remains a challenge. Relevant data is often scattered across documents, presented in different formats and difficult to translate into structured inputs for machine learning and process optimisation.
This is where artificial intelligence offers an opportunity: not simply to retrieve information, but to extract relevant knowledge, structure it and make it useful for improving materials and manufacturing processes. To explore this opportunity, INAM partnered with MKS’ Atotech for one of the AdMaCom 2026 Qualifiers, a targeted startup competition designed around a specific industrial challenge.
The call invited startups developing AI solutions capable of extracting knowledge from publicly available scientific and technical documents and preparing it for machine learning-driven optimisation of materials and manufacturing processes. Integrated, end-to-end solutions were particularly encouraged.
The objective was twofold: identify promising technologies and connect their developers with an industrial partner that understands the demands of advanced manufacturing.
POMA AI takes the winning position
Following the selection process, POMA AI was named the winner of the MKS' Atotech AdMaCom Qualifier with PrimeCut, its document ingestion and chunking tool that turns scientific and technical documents into structured, machine-readable data.
The final pitch round also featured four other highly innovative companies:
The finalists brought their approaches to a challenge that sits at the intersection of AI, data and industrial innovation. Their participation highlighted the growing importance of making scientific and technical knowledge more accessible, structured and actionable for industrial R&D.
Congratulations to POMA AI on winning the qualifier, and to all five teams for bringing their work to the selection process.
What is next?
AI is increasingly discussed as a driver of industrial transformation. But its value in materials science and manufacturing will depend on more than the availability of algorithms.
Industrial applications require relevant data, domain knowledge and a clear understanding of the processes being improved. They also require solutions that can fit into existing R&D and manufacturing workflows.
The opportunity lies in connecting these elements: turning unstructured knowledge into usable data, applying it to specific technical challenges and enabling better-informed decisions in materials development and process engineering.
For companies operating in advanced manufacturing, this can open new possibilities for improving process performance, accelerating development and making better use of accumulated scientific knowledge.
For startups, working directly with industrial partners offers an opportunity to test their value propositions against real-world requirements and identify pathways towards adoption.
Connecting startup innovation with industrial demand
The AdMaCom Qualifiers are a new element of INAM’s approach to startup scouting and commercialisation. Rather than relying exclusively on broad accelerator applications, they focus on clearly defined technological challenges in collaboration with industry and ecosystem partners.
This creates a more targeted connection between the needs of established companies and the solutions being developed by startups.
The format also provides a pathway into INAM’s wider programmes and network, connecting selected teams with potential industrial partners, investors and experts who can help advance their technologies towards market adoption.
The collaboration with MKS’ Atotech demonstrates the potential of this approach: start with a concrete industrial challenge, identify the teams working on relevant solutions, and create opportunities for meaningful exchange between them and industry.
We thank MKS’ Atotech for the collaboration and all participating startups for their contributions.
Congratulations once again to POMA AI and the other finalists.
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