Remediate AI risks with state-of-the-art risk mitigation techniques

DynamoEnhance provides enterprises with a path to addressing AI privacy, security, and hallucination risks. The product module provides enterprises with easy-to-use techniques to improve privacy (leveraging privacy-enhancing technologies like differential privacy and federated learning), mitigate hallucinations, and bolster AI safety using LLM alignment techniques.

Request a Demo

Differential Privacy

Mitigate data memorization and leakage vulnerabilities by leveraging differential privacy to inject noise during model training and fine-tuning.

Training Data Sanitization

Redact or pseudonymize unstructured training and fine-tuning datasets leveraging DynamoEnhance’s data sanitization capabilities.

Optimize your RAG Pipeline to mitigate hallucinations

Address hallucinations issues in your RAG pipeline through few shot prompting optimizations, end-to-end RAG fine-tuning, and retrieval strategy optimizations (i.e. chunking, indexing, etc.)

Federated Learning

Train AI models across distributed user datasets, while simplifying cross-jurisdictional compliance and hardening your models against adversarial attacks.