Internal / Hypothetical — Strategy Mock. This site is for internal positioning and fundraising preparation. Customers, metrics, and financing are illustrative unless marked verified.

Docs: Threat model

Short, practical risks and mitigations for onboarding ops workflows.

How we're different

  • Evidence-first workflows (not chat transcripts).
  • Policy-gated actions with human approvals.
  • Audit trail and exports by default.
Trust rule: AI drafts; humans decide for sensitive outcomes.

Primary data flows

High-level view. Exact deployment varies by environment.

Intake
Storage (docs + hashes)
Extraction (cited)
Policy engine
Approvals
Binder export
  • Documents are hashed on upload; binders include provenance.
  • LLM output is constrained to structured extraction and drafting under policy gates.
  • Every sensitive action requires explicit approval.

Top risks

Prompt injection / malicious documents

Documents can contain instructions that try to override policy or induce invented facts.

Unauthorized access

Onboarding packets include PII; role design and access controls must be explicit.

PII leaks (logs + exports)

Debug logs and ad-hoc exports are common leak paths in early products.

Workflow tampering

Changing state or approvals without trace undermines auditability and trust.

Mitigations

Strict policy gates

  • External comms require approval
  • Final outcomes require approval
  • Versioned policies + change control (roadmap)

Evidence-first schema

  • “No citation, no field” enforcement
  • Low-confidence extractions routed to review
  • Binders export citations + provenance

Least privilege + audit

  • Role-based access controls
  • Append-only audit timeline
  • Tamper-evident exports (roadmap)

Data minimization

  • Store only what is needed to run workflows and prove evidence
  • PII redaction in logs (roadmap)
  • Retention + deletion policies

Related

Not legal advice. Requirements vary by jurisdiction and institution.