Compliance in Under 10 Minutes
Valesta automates the 8-to-12-week manual documentation cycle into a streamlined, high-speed automated approval process.
The Request & Multi-Agent Trigger
A compliance analyst selects a model in the dashboard. Upon clicking 'Generate', a single API call fires, orchestrating four specialized data-gathering agents to run in parallel.
Parallel Data Collection
Model Agent
Extracts training data schema, hyperparams, and test metrics.
Infrastructure Agent
Queries MLOps platforms for deployment details and CI/CD logs.
Governance Agent
Pulls from Collibra/Alation for data lineage and ownership.
Regulatory Agent
Applies rules engine, mapping Annex III classifications.
Parallel Data Collection
Four specialized agents run concurrently, pulling evidence from model registries, MLOps platforms (MLflow, SageMaker), data catalogs, and compliance rules engines to assemble a full evidence bundle.
30-Second Generation
The document generator assembles all collected data into a complete package. Six documents are produced simultaneously—Technical Docs, Risk Reports, Data Governance, Transparency, Human Oversight, and Conformity Declarations—all cross-referenced and internally consistent.
The Valesta pip Package
Everything begins with passive collection. Added directly to the model training and serving code, it hooks into the model lifecycle without developer overhead.
pip install valesta
# Add to model code at deployment
from valesta import ComplianceAgent
agent = ComplianceAgent(model_id='credit-score-v3.1')
agent.attach(model)
Analyst Review & Export
The analyst is no longer a documentation producer, but an approver. They review the pre-generated documents where flags only surface for incomplete data or regulatory ambiguities. Once approved, cryptographically signed documents are exported to PDF, Word, and JSON.