Summary: Splyc AI draws on two complementary systems—a corpus (broad patterns from clips in production) and a live knowledge layer (what’s happening recently, plus published guidance). Together they keep answers useful and current without exposing private clip data in bulk.

Why two systems?

• Corpus answers: “What do successful clips tend to look like?”—titles, tags, phrasing by category, short example lines—built from large volumes of real production clips, refreshed on a schedule.
• Live knowledge answers: “What’s the product seeing lately?”—rolled-up, anonymized activity (for example, how much automated analysis and thumbs feedback is landing per category) plus responsible clipping policy text, updated as the product is used.

Chat does not rewrite those stores directly. They are maintained through logged analysis, scheduled jobs, and team-controlled policy, so behavior stays predictable and auditable.

The corpus (slow, wide loop)

In plain terms: Splyc compresses production clip data into reference packs: tag and title patterns (including by clip category), and short anonymized snippets that can be matched to a question or to your clip’s metadata.

How it stays fresh

1. When media analysis runs on clips, the product records structured summary metadata (for example, quality tiers, ratings, cache flags, category)—enough to improve retrieval and quality over time, not raw video.
2. On a regular schedule, those records are consolidated per clip and merged with things like category and extension feedback where available.
3. Reference packs are rebuilt from eligible clips (global and, where applicable, per organization), respecting content and visibility rules (for example, public-only vs broader modes, safety filters).

What you should expect: Splyc AI can sound more grounded in real stream culture because it is reading curated summaries of production behavior, not guessing from a generic model alone. The packs are versioned snapshots—the product reads the latest pack, not the entire clip database on every message.

Culture add-on: Separately, Splyc can include curated culture and ecosystem context (for example, community terms and dossiers) in the same artifact style, so suggestions can respect how given corners of the internet actually talk.

Live knowledge (fast, recent loop)