PureVector by STELR AI - The Trust Layer for Generative Content

As generative AI floods enterprise systems, organizations face a critical question:

Do you know if the data flowing through your pipelines is real, or AI-generated?

PureVector is an AWS-native content authenticity engine that automatically detects and classifies AI-generated versus human-authored data in real time. Whether content is ingested via API, uploaded to an S3 bucket, or streamed through your pipelines, PureVector continuously inspects and routes it to ensure AI governance, auditability, and compliance.

Key Capabilities

AI-vs-Human Classification: High-accuracy model distinguishes AI-generated content from human-written content using advanced linguistic and statistical signals.

S3-Aware Architecture: Automatically scans content as it enters your S3 buckets, classifying and routing it to /human/ or /ai/ prefixes.

Real-Time Inference: Lightweight Lambda-compatible API enables sub-second detection without interrupting workflows.

Audit Logs and Metadata: Enriched output includes classification confidence, timestamp, and source metadata for traceability.

Webhook and SIEM Integration: Stream results into existing governance or security workflows.

Compliance Support

PureVector supports enterprise AI governance aligned with:

EU AI Act

NYDFS AI accountability guidelines

Internal model review and dataset traceability programs

Deployment

Fully serverless and API-first

Deployable via AWS Lambda, S3 event triggers, or direct API

Quickstart templates available for common ingestion flows

Who It Is For

Data Science and MLOps teams needing AI hygiene

Legal and Risk teams focused on regulatory compliance

Education, publishing, finance, and government institutions handling sensitive or regulated content

Stop training your models on AI-generated content.

With PureVector, you always know what is real and what is not.