To provide clarity on what we actually do, we separate our AI capabilities into four distinct areas of technical depth and strategic focus. We do this to highlight the complex engineering approach that we apply, in the shadow of the highly overused AI buzzword.
Applied AI & Integration
Like many modern development teams, we know how to leverage the robust tools already available on the market. When a client’s business goal can be efficiently solved using existing technology, we integrate and configure these systems to deliver immediate value. This baseline of AI development includes orchestrating cloud-based cognitive services, building LLM-driven applications, deploying intelligent agents, chatbots, and integrating standard APIs for tasks like image generation or general text processing. But we can go way beyond this superficial understanding of the technology.
Deep AI & Custom Model Engineering
This is where we separate from the broader agency crowd. When off-the-shelf tools fail to handle domain-specific nuances, we go deeper. We actively fine-tune foundation models and architect entirely custom machine learning models tailored to complex, highly specific tasks. This custom engineering goes beyond the model architecture itself; it requires building robust data pipelines for data collection, cleaning, and processing raw data to ensure our systems learn from the highest quality inputs. To guarantee our solutions solve the exact business problem, we rely on structured experimentation and rigorous evaluation metrics to iterate on performance.
Crucially, we are highly experienced in deploying these as on-premise, completely offline solutions running on custom GPU-enabled hardware. When doing so, we focus heavily on setting up the underlying infrastructure for scalability, reproducibility, and continuous monitoring, ensuring that our models remain reliable over time. This localized architecture is vital for organizations requiring strict information security and regulatory compliance, while also offering predictable cost control and protecting our clients from cloud vendor lock-in.
Our real-world footprint in this space currently includes highly specialized audio and text processing solutions. For example, recently we have worked on a speech-to-text engine specific to the Hungarian language, processing broadcasts with high accuracy, identifying speakers in dialogues, and classifying audio segments, detecting topics, and identifying songs. We also have experience in AI assisted data retrieval systems, through engineering sophisticated retrieval-augmented generation (RAG) pipelines powered by custom embedding models and tailor-built LLM agents.
Internal AI Maturity
We don’t just sell artificial intelligence; we rely on it to run our own business. We understand that while AI tools will inevitably commoditize basic code generation, they will only amplify the value of true domain experts—engineers who know exactly how to architect these systems and possess the deep technical knowledge to rigorously validate their outputs. Our internal software engineering workflows are heavily augmented by AI. By integrating advanced coding agents and automated, AI-assisted code review systems into our daily operations (built by ourselves according to our very own needs!), we continuously optimize our development velocity, enforce high-quality standards, and maintain exceptional operational efficiency. By continuously experimenting with the latest technologies and following the state of the art, we ensure that our team keeps on learning, and is ready for future challenges in this extremely quickly evolving AI landscape.
Strategic AI Consulting
Beyond writing code, we guide clients through their broader digital transformations. Through our product discovery and business consulting services, we audit our clients' existing workflows to identify genuine opportunities for AI-enabled automations. We help organizations pinpoint exactly where machine learning can replace manual bottlenecks, reduce costs, and drive measurable business value.
