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AI Research Lab
Making AI Smarter, Safer,
and More Efficient.
We're an AI research lab building the protocols, datasets, and efficient methods that power the next generation of intelligent applications. Most of our work is open.
Newsroom
Latest News & Announcements
Stay up-to-date with company news, press releases, and key milestones from the LegionEdge team.
No press releases found.
Applied Research
Technical Articles & Research Protocols
Explore our technical deep-dives, official research papers, and open protocol publications.
Our Customers
Powering industry leaders
with autonomous security
See how forward-thinking engineering teams leverage LegionEdge secure sandbox environments and AI orchestrations to safely build next-generation tech.
Our Mission
Building the protocols that power AI products.
We're an AI research lab focused on the foundational work that makes intelligent applications possible. Most of our research is published openly — because the future of AI should be built together.
Design Protocols
Creating standard interfaces for structured AI representations
Synthetic Training Data
Generating highly diverse, high-quality tokens for specialized tasks
Model Development
Studying architecture efficiency and fine-tuning optimized methods
Open Research
Publishing papers, code, benchmarks, and model weights openly
Protocol Research
Designing foundational protocols that enable AI-native applications — from structured UI representations to model context optimization.
OpenAll specs published
Synthetic Data Generation
Creating high-quality synthetic datasets that improve model performance. Better training data means smarter, more reliable AI systems.
10B+Tokens generated
Model Development
Researching efficient architectures, fine-tuning methods, and inference optimization. Making models smaller, faster, and more capable.
50xContext efficiency
Open Research
Most of our research is published openly. Papers, datasets, model weights, and protocols — available for the community to build upon.
100%Research public
Research Areas
Protocols, data, and models — the foundations of AI
Our research spans the full stack of AI development — from how models understand context to how agents interact with the world.
Context Protocols
How do we give AI models the right context without overwhelming them? We develop protocols that structure information for optimal model comprehension and reduced token usage.
- Model Context Protocol
- Structured UI Protocol
- Context compression
Synthetic Data
Training data is the bottleneck. We generate diverse, high-quality synthetic datasets for code, UI, reasoning tasks, and domain-specific applications.
- Code generation datasets
- UI/UX training data
- Reasoning benchmarks
Model Efficiency
Smaller models that perform like larger ones. We research quantization, distillation, and architectural innovations that reduce compute without sacrificing capability.
- Efficient architectures
- Quantization methods
- Inference optimization
Agent Systems
How should AI agents communicate, plan, and execute? We study multi-agent coordination, tool use, and the protocols that make autonomous systems reliable.
- Multi-agent coordination
- Tool use patterns
- Autonomous planning
Human-AI Interaction
The interface between humans and AI matters. We research how to make AI systems more interpretable, controllable, and aligned with user intent.
- Interpretability
- User intent modeling
- Feedback loops
Applied Research
Theory meets practice. Our research directly informs the products we build — Nokuva, Tavoc, and Foltrac are testbeds for our protocols and methods.
- Design intelligence
- Code understanding
- Infrastructure automation