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.

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