> ## Documentation Index
> Fetch the complete documentation index at: https://docs.highailabs.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Notebook Media Governance

> How High IQ evaluates optional notebook media without selecting a provider or exposing customer data.

## Current state

High IQ's paid notebook is the readable, educational notebook. Optional share
cards, mindmaps, audio, images, infographics, and video must never be required
for that core experience to finish.

Notebook companion execution is currently off. The production registry has
zero selected executors, and the provider-evaluation tools are local,
synthetic, and unable to make network, storage, analytics, subscription, or
persistence calls. NotebookLM is not a product executor and is retained only
as historical internal prototype evidence.

<Warning>
  A research candidate is not an approved vendor. No provider, model, endpoint,
  region, tier, or marketplace listing is selected for notebook media.
</Warning>

## First-party architecture

TIWIH owns the source projection, evidence rules, recipes, structured briefs,
deterministic factual overlays, evaluation corpus, artifact status, storage
policy, and mobile experience. A future provider could execute one bounded
step, but it cannot own the notebook contract or receive an entire notebook,
order, stash, source snapshot, or user profile.

The evaluation order intentionally moves from greatest control to greatest
uncertainty:

1. Deterministic TIWIH share cards and structured mindmaps
2. Deterministic video composition after evidence and private storage land
3. One exact direct image endpoint and one exact direct speech endpoint
4. One exact video endpoint, evaluated last

## Candidate identity

| Candidate class  | What it identifies                                              | What it can do now                                 |
| ---------------- | --------------------------------------------------------------- | -------------------------------------------------- |
| Local proposal   | Exact TIWIH proposal and recipe                                 | Produce a local no-call evaluation packet          |
| Exact endpoint   | Provider, endpoint, model/version, region, tier, and media kind | Nothing until all independent gates pass           |
| Research subject | Provider or marketplace topic without an exact endpoint         | Research only; never callable or offline-qualified |

There is no blanket marketplace approval. A fal.ai or Replicate listing would
need its own exact underlying model/version, license, region, tier, retention,
deletion, and commercial review. There is also no silent fallback: an
unavailable or disallowed endpoint makes the optional artifact unavailable.

## Independent hard gates

Every exact endpoint must independently pass commercial rights,
regulated-content approval, input training, output rights, retention, deletion,
processing region, subprocessors, attribution, moderation, SLA, support,
indemnity, and private-storage handling. Each result is `pass`, `fail`, or
`unknown`; unknown blocks evaluation.

Quality, latency, cost, or a successful demo can never compensate for a failed
privacy, safety, rights, storage, or regulated-content gate.

## Synthetic-only evaluation

The current harness accepts only bounded synthetic briefs for a share card,
mindmap, audio script, image brief, infographic brief, storyboard, or video
brief. It rejects private identity fields or values, email addresses,
credentials, URLs, clinical or prescriptive copy, Report V1 content, source
snapshots, and oversized inputs.

A future Report V2 integration may expose only the exact public/shareable
projection required by one artifact. It may not send a whole report or source
snapshot to a provider.

Evaluation packets use versioned, domain-separated SHA-256 identities for
content, request, idempotency, and packet data. A future offline receipt can
record hashes, usage, cost, retention/delete state, exact provenance, and
manual safety review, but no provider artifact URL.

## Storage and publication

Before any future customer delivery, generated artifacts need private
TIWIH-controlled storage, authenticated retrieval, short-lived delivery,
deletion, regeneration, retention limits, and auditability. Public provider
copies must be copied privately and confirmed deleted. Pending safety review
always requires manual publication review.

## Provider research posture

* OpenAI Images and text-to-speech are provider-generic research subjects; no
  endpoint or model is approved.
* Luma, Kling, and Runway video research is blocked pending exact identity,
  written regulated-content confirmation, commercial review, and private
  storage.
* ElevenLabs remains blocked because its published policy requires prior
  written authorization for regulated or recreational drug use.
* OpenAI's current Videos API path is retired from new-integration research
  because its official documentation says the API is deprecated and scheduled
  to shut down September 24, 2026.

Provider terms change. These statements are architectural diligence, not legal
advice, and must be re-verified from primary sources immediately before any
future evaluation or activation change.

## What activation would require

Activation is a separate reviewed change. It requires evidence-first Report V2
projections, private media storage, one exact all-pass endpoint record, a golden
corpus review, budgets, observability, cancellation, reconciliation, cleanup,
deletion, rollback drills, and an explicit production executor selection.

A mobile or environment flag may change presentation only. It cannot select or
run an executor.

## Related pages

* [AI Features](/guides/platform/ai-features)
* [Notebook Generation](/help/features/notebooks/how-generation-works)
* [Notebook Overview](/help/features/notebooks/overview)