Nexome is a founder-led AI engineering practice run by Michał Budnik, built around deep expertise in computer vision and applied deep learning.
The work spans the full stack: research, model design, training, optimisation, and production deployment.
Computer vision, deep learning, and multimodal AI systems — engineered for production.
LLMs, vision-language systems, diffusion pipelines, and custom generative workflows designed around real product and business needs.
// When off-the-shelf generative models can’t meet brand, domain, or compliance constraints.
Custom architectures, training pipelines, optimisation, quantisation, and deployment at scale.
// When off-the-shelf models hit accuracy, latency, or cost ceilings.
Object detection, segmentation, tracking, 3D reconstruction, biometric verification. From dataset to deployed model.
// When you have visual data — images, video, scans — and need reliable automated understanding.
End-to-end AI engineering: problem framing, research, implementation, and production deployment with rigorous evaluation.
// When the problem is hard enough that ready-made tools won’t solve it.
Mainstream platforms leave deaf users with flat captions — text that strips the grammar, timing, and non-manual markers that make sign language readable. Nexome is building a real-time 3D avatar driven by an LLM for semantic translation, paired with a motion-synthesis pipeline that produces natural, expressive signing from text or audio. Ongoing engagement on the client’s platform.
KYC-regulated industries need identity verification that holds up against motivated attackers, not just casual fraud. Co-built by Nexome’s founder: a multi-layer pipeline (face verification, document OCR and authentication) engineered to catch presentation attacks (screen and print) and document modifications across text, photos and security features. In production, sub-200ms inference on standard hardware, GDPR-compliant by design.
Eye disease detection models stall on rare cases — the very ones where AI matters most — because clinical datasets are small and skewed. Nexome combined realistic medical image synthesis (SDXL with LoRA fine-tuned on limited clinical data) with classification training, producing balanced datasets that cover rare presentations without violating data-scarcity or compliance constraints.
Nexome is a founder-led AI engineering practice run by Michał Budnik, built around deep expertise in computer vision and applied deep learning.
The work spans the full stack: research, model design, training, optimisation, and production deployment.
Describe the challenge. Response within one business day.