Expose the missing capability.
Test preference discovery, memory, correction, collaboration, and outcomes across repeated interactions.
HELM / FRONTIER + NEO LABSHELM PRODUCTS
Behavioral environments
for training and evaluation.
Behavioral environments for software and embodied AI. Study clarification, memory, corrections, and recovery in tasks where people and conditions change.
One environment connects simulated people, task state, expert standards, and outcome checks. Compare models and harnesses, then scope training access while keeping independent evaluation evidence separate.
Explore the judgment layerA CLEAR ENTRY POINT
Define what your evaluation should reveal.
Build a useful curriculum.
Scope versioned worlds, tasks, and learning signals. Agree training rights separately from evaluation access.
Inspect the underlying models.
Explore System 1 decision components and Helm’s Implicit Brain Model research alongside task-specific evidence.
QUESTIONS WORTH EXPLORING
Environments for agent development.
AGENT TRAINING + EVALUATION
Train and evaluate personal agents
Does a model discover preferences, remember context, and adapt?
Explore the use case ↗SYSTEM 1 DECISIONSTrain a workflow decision model
Which route, tool, or next step fits this situation?
Explore the use case ↗ROBOTICS + EMBODIED AIEvaluate robots in your site
What changes when this robot meets this environment?
Explore the use case ↗HELM PRODUCTS
Connect Helm to your requirements.
Select the Helm products and integration scope for your operation or research program. Agree the evaluation, deployment, data, and commercial requirements together.
Discuss a lab environment pack- YOU BRING
- Your agent interface, target capability, experiment design, and environment requirements.
- WE SCOPE TOGETHER
- A versioned environment pack, simulator, outcome checks, traces, and validity report.
- THE SUCCESS TEST
- Useful evaluation signal or learning gains on independent tasks and human evidence.
Engagement details. Scope, timing, price, interfaces, data rights, and acceptance criteria are agreed before work begins.
PRIVATE BY AGREEMENT
Agree on data access and ownership.
We agree permitted use, deployment boundaries, access, retention, and ownership before an engagement. Private customer records do not become another buyer’s training data by default. Signed lineage connects records to their origin; controls and integrations follow the data and operating requirements.
Embodied AI research
Extend the evaluation
into the physical world.
For robotics and multimodal teams, scope human interaction and recovery tasks around an agreed embodiment, policy interface, and environment.
Explore Physical AI environmentsFor frontier, neo, and robotics labs
Models. Environments.
Evaluation. Data.
Connect vertical models and decision components with behavioral populations, embodied tasks, harness evaluation, and traceable training and evaluation data.