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.
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.
