Addepto, a leading AI and data engineering company, has been acquired by KMS Technology, a U.S.-based software and product engineering firm. The acquisition marks a strategic step toward building a new kind of technology organization—one where artificial intelligence and software engineering are fully integrated from the ground up.
This partnership combines our deep expertise in AI, machine learning, and data platforms with KMS Technology’s global delivery capabilities and mature software engineering practices. Together, the companies aim to deliver end-to-end, production-ready solutions designed for an AI-driven future.


At the core of the partnership is a shared belief: modern software should be AI-first by design—not retrofitted with AI as an afterthought.
With this acquisition, the combined organization introduces an AI-Ready approach to software development. This means that every system is designed from the outset to seamlessly integrate with large language models (LLMs), predictive models, and other AI systems—without requiring costly re-architecture.
In practice, this approach operates on two complementary levels:
This dual strategy enables faster delivery while maintaining high engineering standards.

One of the fundamental challenges in modern AI systems is the imbalance between speed and reliability: content and solutions can be generated quickly, but validating their quality remains significantly more complex and time-consuming.
To address this, Addepto and KMS are investing in comprehensive evaluation and quality control frameworks that become an integral part of the development lifecycle.
This approach combines:
By embedding evaluation directly into delivery processes, the organization ensures that AI-powered systems are not only fast to build but also reliable, measurable, and production-ready.
Founded in 2018 by Artur Haponik and Edwin Lisowski, Addepto has established itself as a trusted partner in AI and big data engineering, working with global enterprises such as Rolls-Royce, BMW, ABB, SITA, Continental, and Nissan. The company has grown to a team of approximately 70 specialists and has been recognized by Forbes, Deloitte, and the Financial Times as one of the fastest-growing and most impactful AI consultancies in Europe.
KMS Technology, headquartered in Atlanta, brings over 1,100 employees across the United States, Vietnam, and Mexico. Since 2009, the company has supported organizations in building, modernizing, and scaling digital products through a global delivery model and strong enterprise relationships.
The acquisition creates new opportunities across several dimensions:
For clients, the partnership enhances delivery capacity while maintaining continuity in expertise and service quality. Organizations will benefit from broader capabilities, deeper technical integration, and more scalable solutions supporting their digital transformation initiatives.
For employees, the acquisition opens access to international projects, cross-functional collaboration, and a global network of over 1,100 professionals, creating new opportunities for professional development and knowledge exchange.
“This is a transformative moment for Addepto,” said Artur Haponik, Co-founder of Addepto. “Joining KMS Technology gives us the reach, resources, and global platform to scale faster than ever before—while staying true to our roots as an innovation-driven AI company.”
The combined organization is positioned to shape the next generation of software development—where intelligence is embedded throughout the entire product lifecycle.
With an AI-Ready foundation, strong engineering culture, and a deep focus on evaluation and quality, Addepto and KMS Technology are building systems that are not only intelligent but also trustworthy, scalable, and ready for real-world impact.
This marks the beginning of a new chapter focused on delivering AI-driven solutions at a global scale.
This article was originally published on Dec 18, 2025, and was updated on Mar 13, 2026, to incorporate new information about the Addepto and the KMS approach.
It will likely blur the boundaries between data scientists, ML engineers, and software developers, leading to more cross-functional teams where AI expertise is embedded directly into product engineering workflows rather than operating as a separate function.
They can track metrics such as model accuracy over time, failure rates in production, validation speed, and the consistency of outputs against predefined quality benchmarks or business KPIs.
It creates both faster product innovation and operational efficiency, allowing companies to shorten development cycles while simultaneously improving the quality and scalability of their solutions.
It could accelerate a shift toward fully integrated service offerings, pushing competitors to combine AI expertise with end-to-end engineering capabilities to remain relevant in delivering production-ready AI solutions.
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