An R&D laboratory where AI, simulation, security, finance, energy, and engineering intersect. We build systems that learn across domains, discover hidden patterns, and create value at the intersection of disciplines.
Research Tracks
AI Specialists
Data Records
Autonomous
Patterns discovered in one domain transfer to others. A model trained on risk analysis strengthens its security audit capabilities — and vice versa.
Self-improving systems that run 24/7, finding new connections between disciplines. 48K+ autonomous learning sessions completed without human intervention.
Fully self-hosted on-premises infrastructure. Research data never leaves the lab. Enterprise-grade guardrails across every domain we operate in.
56 AI agents, each mastering a specific domain, orchestrated by a central intelligence that routes tasks to the right specialist.
Every dataset, every training run, every result is Merkle-verified. Full provenance and auditability for reproducible science.
We believe in open research. Our tools, methods, and trained models will be available to the community. Science advances when it's shared.
Autonomous training pipelines, multi-teacher distillation, large language models, and frontier-class evaluation systems.
Humanoid locomotion, manipulation, and sim-to-real transfer. Physics-based environments for training autonomous systems.
Vulnerability analysis, code auditing, cryptographic systems, and automated security evaluation across software ecosystems.
Quantitative modeling, risk analysis, market simulation, and economic forecasting with AI-driven pattern recognition.
Optimization of compute resources, energy-efficient AI training, smart grid patterns, and sustainable infrastructure research.
Text-to-3D generation, procedural modeling, interactive environments, and digital asset creation for industry applications.
32 tracks across computer science, mathematics, physics, engineering, and interdisciplinary studies from top universities.
Real-time AI interaction, procedural content generation, agent-driven experiences, and human-AI collaboration frameworks.
Large-scale data curation, statistical analysis, signal processing, and multi-modal learning across structured and unstructured data.
Directs research priorities, partnerships, and go-to-market strategy for CoreLabs AI platform.
Owns the full NVIDIA stack integration, training pipeline reliability, and infrastructure operations.
Self-training AI platform. 56 specialist agents, 966K training records, ranked #4 globally in domain evaluations.
CoreLabs established in Panama. Initial research infrastructure deployed. Multi-node compute cluster assembled.
Autonomous training platform launched on NVIDIA Grace-Hopper. 32 academic research tracks activated. 966K cross-domain training records curated.
Full NVIDIA stack integration: NeMo, NIM, Guardrails, NemoClaw, Isaac Sim, Agent Toolkit. Active member of the NVIDIA Developer Program.
Commercial launch of the autonomous AI platform at iamolly.ai. Domain-specialist agents for enterprise and research.
Opening new research verticals: energy optimization, interactive systems, and industrial simulation. Multi-GPU cluster scaling.
CoreLabs builds at the intersection of AI, simulation, security, finance, and engineering. Our flagship product Molly AI is preparing for public launch.