Regulated industries require full transparency in AI platforms, including the ability to audit outcomes, track data lineage and ensure that AI model training and outcomes can be trusted.
- Responsible, Trusted and Explainable AI is critically important for establishing trust in an enterprise
- Charli AI's design principles around human-to-AI interaction deliver full transparency and explainability; not just on AI models but across the AI work process
- Every step of the AI workflow is exposed and fully observable. Humans can oversee each of the most nuanced parts of any action Charli AI takes or outcome produced by the AI models
- Charli AI embeds fine-grained controls over data, decision flows and user access including support for Enterprise IAM, ABAC, and Data Governance frameworks
- Advanced Separation of Concerns design to ensure that data, prompts and queries are protected and not shared or exposed through AI processing and outcomes; including container isolation