Duality Secure AI Collaboration Platform vs Sarus SarusLLM: Side-by-Side Comparison (2026)

Duality Secure AI Collaboration Platform

Enterprise security and ML teams that need to train models on sensitive external data without exposing it will find real value in Duality Secure AI Collaboration Platform; the platform's multi-party computation approach lets you collaborate on datasets you'd normally keep behind walls. The hybrid deployment model and support for traditional ML through generative AI workloads means you're not locked into one model type or cloud provider, and NIST coverage across data security, platform security, and asset management confirms the security controls are intentional rather than bolted-on. Skip this if your primary constraint is cost or if you need out-of-the-box integrations with legacy on-premises data warehouses; Duality's value proposition assumes you've already committed to moving compute toward your data rather than moving data toward your models.

Sarus SarusLLM

Mid-market and enterprise teams fine-tuning LLMs on sensitive data will find real value in SarusLLM's differential privacy approach, which lets data scientists build custom models without exposing raw datasets to the training process. The platform's DP-SGD implementation and zero-trust data access model directly address NIST PR.DS (Data Security) requirements that most LLM workflows ignore entirely. Skip this if your org needs to fine-tune at scale without GPU infrastructure constraints; SarusLLM's on-premises deployment and orchestration overhead make it a poor fit for teams wanting minimal operational lift.