Build adaptive intelligence.
NNGrowth is a platform that helps researchers design, simulate and validate adaptive AI architectures in one modular research workbench.
NNGrowth is a platform that helps researchers design, simulate and validate adaptive AI architectures in one modular research workbench.
Many AI systems are trained in distinct phases and require retraining or carefully controlled updates when tasks, data or environments change.
Memory, internal state and behavioral shifts can be hard to trace across runs, especially in long-lived, adaptive or multi-agent systems.
Final scores and aggregate benchmarks can hide instability, failure modes and the causes of unexpected or emergent behavior.
Tremergent AI is building the scientific and software infrastructure required to make adaptive intelligence designable and verifiable. We are working with researchers, robotics teams and computing partners to define the benchmarks, safeguards and interfaces these systems need before they scale into the physical world.
Concept visualization - NNGrowth is currently in private pre-alpha development. Technical previews may be shared selectively upon request.
Define modular neural components, temporal structures, memory and environment interfaces without locking the experiment to a single architecture.
Run adaptive and embodied experiments in controlled digital environments, including novelty, structural change and behavior over time.
Trace memory, structural change, behavior and failures; compare baselines and produce reproducible evidence before committing to scale.
We are connecting with researchers, technical teams and scientific partners working on the open challenges of adaptive intelligence.
NeuroAI researchers, robotics engineers and AI R&D teams developing experimental architectures, adaptive agents and embodied intelligence.
Organizations building scalable infrastructure for adaptive AI, from cloud and HPC to wafer-scale, neuromorphic, photonic and edge computing.
Researchers and domain experts willing to challenge assumptions, review experimental methods and help define rigorous benchmarks.
Founder & CEO, Software and AI Systems Architect
With more than 10 years of professional experience, his background spans software architecture, full-stack development, real-time 3D, procedural geometry, networking, Unreal Engine C++, R&D and technical leadership. He has contributed to Twinmotion and next-generation BIM software and previously co-founded a startup as CTO.
Alongside his engineering career, he has independently studied AI, deep learning, neuroscience and cognitive systems for more than 15 years, developing the research direction behind Tremergent AI from prototypes first explored between 2014 and 2016.
© 2026 Tremergent AI. Adaptive intelligence research.