ThoughtFrame is designed for environments where privacy is a system property, not a policy checkbox.
Client data, documents, and personally identifiable information (PII) are handled according to strict architectural boundaries. ThoughtFrame never silently forwards data, never trains on client content, and never blurs responsibility for where information lives or who controls it.
ThoughtFrame is designed to operate across a wide range of environments, from highly regulated, privacy-constrained systems to fully connected cloud deployments. Data handling is not implicit or hidden — it is explicitly determined by how ThoughtFrame is deployed and configured.
Clients control where ThoughtFrame runs, which services it can access, and what information is permitted to cross system boundaries. ThoughtFrame does not silently impose or bypass data restrictions.
ThoughtFrame can be deployed entirely within client-controlled infrastructure. All documents, prompts, memory, models, and workflows remain inside the client environment.
This model is typically used in regulated or high-sensitivity contexts where full data sovereignty is required.
ThoughtFrame may also be deployed in a fully connected configuration, where it is permitted to interact directly with cloud-based services and model providers.
In this model, raw documents, prompts, and context may be transmitted externally as part of normal operation. This configuration is selected when privacy constraints allow and when access to external models or services is operationally advantageous.
ThoughtFrame also supports hybrid deployments where cloud services are used, but only behind a mandatory local sterilization boundary.
In this configuration, raw data and personally identifiable information (PII) are processed locally first. Identifying details are removed or transformed before any content is transmitted to cloud services — including ThoughtFrame-operated infrastructure.
This model is commonly used when external models are desired but strict data minimization requirements apply.
Privacy posture in ThoughtFrame is a deployment decision, not an implementation accident.
Because ThoughtFrame operates through deterministic workflows (Frame FSM) and structured, persistent memory (FrameSession Deep Memory), clients can inspect which workflows ran, which data sources were used, and which boundaries were crossed.
ThoughtFrame provides the flexibility to match operational needs without obscuring where data flows or how decisions are made.
Flexibility without ambiguity.