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How does Sparkflows handle inferencing to ensure data privacy and system performance?
Sparkflows takes an innovative approach to inferencing by conducting it offline, eliminating the need for external API calls. This approach enhances data security, and mitigates risks of prompt injection, jailbreaking, and prompt leaking, among others. By keeping the inferencing process within the system, Sparkflows ensures that sensitive information remains confidential and is not exposed to external servers. Moreover, this offline inferencing capability contributes to improved performance and reduced latency, enabling near-real-time processing of Natural Language tasks. This advantage is particularly valuable for applications that require swift and seamless interactions.