Data governance
Where data lives, what’s stored, sub-processors, org isolation. No training on your data.
Observability
Every Lab turn fully traced — system prompts, tools, model I/O, render output. Visible to engineers and analysts.
Guardrails
Deterministic code computes the numbers. Sandboxes isolate execution. Schemas validate every output. Missing inputs refuse to be fabricated.
Citations and audit trail
Every figure traces to its source. Threads export as compliance-ready audit trails.
The posture at a glance
| Concern | cf0’s answer |
|---|---|
| ”Where does my data live?” | Immutable storage as the canonical record, US region. AI inference inside cf0’s cloud perimeter. |
| ”Who else touches it?” | A curated set of sub-processors covering identity, infrastructure, AI inference, and observability — see the categories. The full vendor list is disclosed under the DPA. |
| ”Will it train on my data?” | No. Customer threads, documents, and reports never enter a training set. |
| ”Can I trust the numbers?” | Math runs in deterministic code templates, not AI inference. Outputs pass through schema validation before they reach storage or the UI. |
| ”Can I audit a report?” | Every figure has a numbered footnote linking to the Sources Table; threads export as compliance-ready audit trails. |
| ”What if a number is missing?“ | cf0 surfaces the gap rather than inventing it. See the refuse-to-fabricate doctrine. |
| ”What about hallucinations?” | Numbers are sandbox-computed. Prose can still drift — citations make every claim traceable and challengeable. |