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AI Usage and Data Privacy Policy

Effective Date: September 2026

Entity: Inward Flow LLC

At Inward Flow, maintaining client trust, data confidentiality, and system security is foundational to how we build and operate. While we leverage artificial intelligence, advanced machine learning models, and automated pipelines to accelerate development and deliver high-performance solutions, we adhere strictly to the following principles:

Data Minimization and Model Isolation

  • We practice purposeful data minimization, sending only the operational data strictly necessary for a given automated workflow to complete its task.
  • Wherever feasible, we prioritize configurations and commercial API endpoints that do not train public foundation models on client inputs.
  • For organizations requiring complete data isolation, we offer architectural implementations powered by locally hosted, self-contained open-weight models that never transmit data outside the client's internal environment.

Operational Data Processing and In-Flight Context

Certain intelligent integrations, such as customer service automated responders, inbox triage agents, calendar coordinators, and database synchronization pipelines, require direct processing of live communication data (e.g., sender identity, scheduling details, inquiry context) to execute real-time actions.

When live data ingestion is necessary for core functionality, data is processed strictly in-flight for execution and recorded only to designated operational stores (such as approved databases, Google Workspace services, or CRM platforms) under client ownership.

High-risk credentials, authentication secrets, and payment data remain completely isolated and are never piped into AI completion prompts.

Human-in-the-Loop and Quality Controls

  • Automated pipelines are architected with guardrails, fallback states, and human-in-the-loop review capabilities where critical business actions are performed.
  • Code, configuration scripts, and logic trees generated or assisted by AI undergo rigorous manual review, verification, and testing prior to deployment in production environments.

Tooling Transparency and Architecture Reviews

  • We maintain complete transparency regarding third-party model providers, middleware, and automation tools utilized in any engagement.
  • Clients receive clear visibility into data pathways, storage locations, and automated triggers so their leadership retains total governance over their operational stack.