Inside SNAP's source layer: why every output is grounded in your own material

Most AI marketing tools generate from a blank page and a prompt. SNAP generates from a source layer — a structured index of what your company already knows. Here's what that means underneath.

What the source layer actually is

A graph of your material: decks, PDFs, transcripts, screenshots, voice notes, product pages. Each fragment is indexed with provenance — where it came from, when, and who authored it. Generation cites these fragments, not the open internet.

Why grounding beats prompting

Prompt engineering asks the model to guess in your voice. Grounding forces it to quote you. The difference shows up in three places:

• Accuracy — nothing goes out that you didn't already say.
• Consistency — the deck, the video, and the post share a source of truth.
• Defensibility — every claim has a citation trail inside your own material.

How it flows through the chain

From ingestion to output

1. Ingest — pages, PDFs, screenshots, voice notes land in the source layer.
2. Structure — fragments are indexed with topic, provenance, and recency.
3. Retrieve — when you write a one-sentence ask, the layer pulls the relevant fragments first.
4. Generate — SNAP, Pitch, Plot, Post, Promote each read from the same retrieved set.
5. Trace — every output can be walked back to its source fragment.

What this unlocks for marketing

One ask becomes a deck, a narrated video, a post, and a promotion — all citing the same underlying material. No stage re-briefs the next. No line contradicts an earlier one. See the mechanics in inside the source layer — how SNAP grounds every training video in your own material, or the enterprise view in the enterprise knowledge graph that powers one-line sales briefings.

The short version

Your company already knows it. The source layer just makes sure every output says it the same way. Start with SNAP AI.