# Data handling Source: https://convergingthought.com/docs/concepts/data-handling > Understand the source, result, checkpoint, and telemetry boundaries. The learning source, inference messages, generated answers, and adapter checkpoints are different forms of data with different purposes. Keeping the source out of later prompts does not mean the source was never processed or that no execution records exist. ## During a request [#during-a-request] The control plane stores the payload needed to dispatch an admitted job. The private worker receives that payload to run training or inference. It also records operation receipts so an interrupted paid operation can be investigated without blindly repeating it. Internalization uses the source to build grounded examples and to guide the teacher. Later inference uses the submitted messages and the selected adapter. The service does not append the learning source to those messages. The worker's provider processes data necessary to perform the requested computation. These docs do not claim zero retention, a particular data-residency region, or a contractual exclusion from all provider processing. Confirm any required production data terms before submitting regulated or contractually restricted material. ## After a known terminal outcome [#after-a-known-terminal-outcome] The control-plane job payload is cleared on settlement. Worker payloads are cleared on known terminal completion. Final results and operational metadata remain in authenticated job records so the application can retrieve the answer and inspect usage. An ambiguous job can require retained execution data for reconciliation. Clearing a browser form does not delete that durable state. The source's learned effects can also remain in a retained adapter even after the original execution payload is removed. Checkpoint storage is private. Public responses expose version IDs and retention deadlines, not provider checkpoint paths. Versions are scoped to a project, optional tenant, and subject; routing does not borrow another subject's weights. ## Analytics and logs [#analytics-and-logs] Product analytics record navigation, interactions, errors, and operational metadata. They exclude full API keys, passwords, learning passages, inference prompts, and completions. Session replay masks inputs and blocks designated model-content surfaces. Raw reasoning is not exposed as a returned transcript. Apply the same separation in your own observability. Log job IDs, error codes, timings, adapter versions, and integer charges. Do not log authorization headers or request bodies merely to diagnose an authentication problem. Use access-controlled storage if your application must retain evaluation outputs. ## Corrections and deletion [#corrections-and-deletion] Learning a correction is not a verified deletion operation. Activating an older adapter changes routing but does not erase newer retained versions, execution records, or historical charges. Creating a fresh subject starts with clean base weights but does not delete the old subject. There is no public self-service subject or adapter deletion endpoint in the current API. Contact [team@convergingthought.com](mailto:team@convergingthought.com) for data-access or deletion requests, and identify the authorized project without sending secrets or raw content in the first message. Keep a canonical source in your own governed storage. An adapter is not a document archive, and its retention deadline is not a promise to retain the original passage forever. See [Privacy](/docs/privacy) and [safe diagnostics](/docs/troubleshooting/diagnostics) for related handling rules.