Research Orchestrator
Coordinates the campaign and delegates work across the platform.
Scientific Engines
Scientific AI engines from research intent to physical execution.
A coordinated system of focused AI modules, analytical models, deterministic engines, validators, and policy controls that manages the complete research and laboratory workflow.
Coordinated architecture
One orchestrator. Twelve specialist systems.
Each module has a defined research responsibility. AURA coordinates their work while TRACE preserves the complete reasoning and evidence chain.
Target Definition
Transforms requested biological output into measurable objectives.
Knowledge & Evidence
Retrieves, ranks, and connects external research and internal data.
Research Strategy
Develops candidate strategies with evidence, assumptions, and uncertainty.
Experiment Design
Creates parallel campaigns optimized for information gain.
Governance & Permissions
Checks policies, approvals, boundaries, and permitted actions.
Workflow Compilation
Compiles approved plans into structured machine-readable workflows.
Scheduling & Routing
Coordinates samples, equipment, resources, and timing.
Result Analysis
Processes measurements and compares results with target criteria.
Next-Best Experiment
Selects future experiments using results and remaining uncertainty.
Provenance
Records sources, versions, decisions, approvals, samples, and results.
Process Monitoring
Detects anomalies, device drift, failures, and maintenance needs.
Scientific Documentation
Creates reports, summaries, histories, and handover records.
Governed control chain
Scientific Engines manage the workflow and its machinery.
AURA owns the auditable research state machine. SENTINEL authorizes consequential action, FORGE resolves approved operations against real device capabilities, ORBIT schedules machinery and samples, and PULSE monitors execution telemetry.
01Scientific intent
02Experiment design
03Policy approval
04Device compile
05Machine schedule
06Live execution
07Measured result
EXECUTION BOUNDARY
Language models never issue unrestricted instrument commands. Every operation crosses schema validation, named-scientist review, SENTINEL policy approval, FORGE compilation, and ORBIT simulation before an authorized connector can act.
Explainability
Every recommendation carries its scientific context.
Important recommendations include the reason, evidence, contradictions, assumptions, confidence, alternatives, approvals, model version, and dataset version.
What supports the action?
Claims remain connected to publications, internal experiments, datasets, and measurements.
What remains unresolved?
Assumptions and contradictory evidence remain visible instead of being averaged away.
What must be approved?
Policy gates and human review remain explicit before consequential execution.