The AI Factory for building your own frontier capabilities.
LegionEdge is an AI/ML lab dedicated to building the frontier models of the future, and to making it easier and more accessible to build your own. Every layer is offered as a service, so the stack you scale on is yours. Most of the work is open.
- 01Protocols
- 02Data
- 03Inference
- 04Training
- 05Compute
The stack
- 01Protocols
- 02Data
- 03Inference
- 04Training
- 05Compute
Our partners
- ZivaZiva
- Google Cloud
- Together AI
- AMD
- RocketRide
- GitHits
- Daytona
- Rho
- NVIDIA
The scaling story
From your data to a model you can operate.
Building useful AI takes more than access to a model. It takes the right data, a training method that fits the task, and infrastructure that fits your product.
LegionEdge brings those disciplines together. We help you develop the capability inside your business, with a clear path from the first experiment to deployment.
How we can helpThe workload comes first.
Start with the task, the data, and the constraints. We establish an evaluation baseline before choosing a model or committing to a training run.
The layers work together.
Data quality, training, and serving are connected decisions. Work with one team across the stack, or bring us in for the part you need.
The work stays useful.
The engagement includes the agreed datasets, weights, evaluations, and implementation details. Your team can inspect the result and keep building on it.
Services
Specialist work at every stage.
Engage the lab for one part of your stack or the full project. Each engagement starts with a defined scope, evaluation criteria, and a practical handoff.
Managed datasets
Start with our open corpora or commission data for your domain. Generation, curation, and validation are designed around the task you want to teach.
You receive
- Validated corpus
- Provenance
- Reproducible pipeline
Model training
Fine-tune an existing model or scope a custom training run. Compare the result against a baseline and the evaluations that matter to your product.
You receive
- Weights or adapters
- Evaluation results
- Run configurations
Inference optimization
Reduce the cost of serving a model through quantization, distillation, and runtime optimization, with quality and performance measured together.
You receive
- Optimized model
- Benchmarks
- Deployment guidance
Protocol design
Define how your agents, tools, and systems exchange information. Make context, interfaces, and compatibility explicit as your architecture grows.
You receive
- Specification
- Reference implementation
- Conformance tests
Research partnerships
Work directly with the lab on a technical question. Structure the experiments, review the evidence, and decide what is worth taking into production.
You receive
- Research program
- Experiment results
- Recommendations
- On demand or reserved
Dedicated compute
GPU capacity for training and serving. Choose the infrastructure your workload needs, with clear hourly pricing.
Capacity & pricingStarting at
$4.79per GPU-hour
- NVIDIA H200141 GB HBM3e$4.79/hr
Now available to reserve for Q1 2027New
- NVIDIA GB300288 GB HBM3eQ1 2027
- NVIDIA B300288 GB HBM3eQ1 2027
Products
Research in practice.
Our work in context protocols and agent systems becomes tools for designing, developing, and shipping software.
All productsDeveloper documentation
Documentation for the work ahead.
Working examples and technical references for connecting an application, training a model, and putting it into production.
Browse all documentationKeys are issued per workspace from a service account, so apps never act as a person.
- Getting startedQuickstartCreate a workspace API key, choose a model, and send a request with an OpenAI-compatible SDK.Authentication · Model selection · First request
- API referenceChat completionsThe request and response contract for inference, with examples for messages, parameters, and streamed output.Request fields · Response formats · Streaming
- Model developmentFine-tuningPrepare a training dataset, configure a run, evaluate the result, and serve your model on dedicated capacity.Training data · Evaluation · Deployment
Newsroom
Latest from the lab.
Product releases, research, and engineering notes from the team.
- Partnership1 min readLegionEdge partners with Google CloudA dedicated NVIDIA H200 cluster on Google Cloud now powers our training and research — and Google Cloud becomes a first-class target for everything we ship.Read the story
- Product1 min readLegionEdge launches LegionEdge CloudOne panel for the compute side of AI work: train models, manage capacity, and spin up inference — on our fleet or yours.
- Company1 min readLegionEdge acquires HazeThe Haze team joins Nokuva as part of our initiative to build the next layer of infrastructure for design.
- Company1 min readBuilding the Agent Command SystemThe Agent Initiative puts fleets of agents in command of workflows, automations, and entire projects — this is the system that coordinates them.
