
Message API for AI applications that connects conversations to user data sources while enforcing granular privacy controls and secure data access.
Pond is a message API designed for AI applications that need to interact with user data while maintaining strict privacy controls. It provides a unified interface for sending, receiving, and managing messages across different data sources, allowing developers to connect AI agents to user-specific context without exposing raw data unnecessarily. The primary purpose of Pond is to simplify secure data access for AI-driven workflows, enabling more personalized and reliable responses from AI systems.
Key features include fine-grained privacy and permission controls that determine what data an AI agent can access and how long it can retain context. Pond abstracts away the complexity of integrating with various data stores and communication channels, offering a single API to manage user messages, history, and metadata. It supports structured message threading, context windows, and configurable retention policies, helping developers avoid over-collection or accidental leakage of sensitive information. Additionally, Pond is built to be model-agnostic, so teams can use it with different LLM providers or switch models without redesigning their data access layer.
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