Data is not a static artifact. It is an interface.
Models learn more and better through structured experiences instead of sheer volume. Our products are mechanisms that shape how intelligence forms.
Products
01
Learning Interfaces
We design the experiences through which models learn.
The core primitive of Vetto's platform:
Learning interfaces aligned with research goals
Living data environments that evolve with model behavior
Expert-driven evaluations and QA design
Research-aware post-training loops
02
Living Data Environments
AI needs environments, not datasets.
We build adaptive environments that evolve as models change:
Dynamic task pools responding to weaknesses
Curriculum policies based on learning trajectories
Continuous distribution-shift monitoring
Environment state and transition logs
03
Post-Training for Frontier Models
SFT, preference data, and safety refinement — built with researchers, not crowds.
We bring domain expertise + research-aware scaffolding:
High-precision preference data
Safety and alignment loops
Domain-specific corrective training
Built by vetted scientists, engineered for real capability gains
04
Evaluations & Model Behavior Analysis
Expert evaluations aligned with real scientific reasoning.
Domain-expert benchmark extensions
Failure-mode taxonomies linked to data provenance
Red-teaming through structured environments
Longitudinal capability tracking
05
Research Ops Infrastructure
Where research intent becomes executable learning.
Hypothesis → data design translation
Custom instruction environments
Fast iteration cycles with researchers
Data provenance + model learning telemetry