Atlas Engine

Request source intake.
Build consented DNA evidence.

Atlas is the intake and evidence layer for OmenBroadcast. It organizes approved source material, consent records, manifests, and DNA analysis requests before campaign planning begins.
Core Functions

Four pillars of
channel intelligence

📥
Intake
Register a supported source or channel for operator-reviewed intake. Public, private, or authenticated sources require the right consent, connection method, and policy status before analysis.
💾
Archive
Approved campaign inputs are archived with context, manifests, hashes, and retention policy. Private or platform-restricted material stays governed by consent and access rules.
🔬
Analyze
Deep per-video analysis across all 10 DNA layers. Sentiment tracking, topic mapping, rhetorical pattern detection, and audience signal extraction.
🧬
DNA Extraction
Individual video analyses are synthesized into a unified channel DNA profile. Confidence bands distinguish strong signals from speculative inferences.
Platform Support

Where Atlas reaches

Atlas is designed for supported source intake across owned and third-party surfaces. Authenticated or platform-restricted access requires consent, operator review, and an approved connection mode.
YouTube
TikTok
📷
Instagram
X / Twitter
🎙
Podcasts
📝
Blogs / RSS
Mission

The preservation imperative

Campaign source material drifts. Listings change, platform posts move, and private assets require custody discipline.

Atlas records evidence. Approved source material enters with manifests, hashes, consent receipts, and retention rules so campaigns can be explained and audited.

This is not a one-click scraping tool. It is a controlled intake layer for source custody, campaign evidence, and reviewable Brand DNA profiles.

Your source material deserves custody, consent, and receipts before it becomes a campaign.
Channel DNA

The 10-layer identity model

Every channel has a unique identity fingerprint. Atlas extracts it across 10 distinct layers, each capturing a different dimension of the creator's voice.
Layer 01
Vocabulary & Diction
Word choice patterns, reading level, jargon density, and signature phrases.
Example: Uses slang frequently, 8th-grade reading level, heavy tech jargon, signature catchphrase detected
Layer 02
Sentence Architecture
Average length, complexity, use of fragments, rhetorical questions, and structural rhythm.
Example: Short punchy sentences, frequent fragments, 2x average rhetorical questions
Layer 03
Rhetorical Patterns
Argumentation style, analogies, repetition devices, and persuasion techniques.
Example: Heavy analogy use, Socratic questioning, builds to emotional climax
Layer 04
Emotional Signature
Baseline tone, humor type, intensity range, and audience emotional targeting.
Example: Dry humor, moderate intensity, vulnerability in openings, anger in conclusions
Layer 05
Topic & Domain Map
Subject expertise, topic clustering, cross-domain references, and content boundaries.
Example: Primary: tech reviews. Secondary: geopolitics. Never: lifestyle content
Layer 06
Ideological Markers
Political leanings, cultural values, philosophical frameworks with confidence scoring.
Example: Libertarian-leaning (0.7 confidence), pro-technology, skeptical of institutions
Layer 07
Audience Model
Assumed knowledge level, in-group references, community signals, and relationship dynamics.
Example: Assumes technical literacy, frequent in-jokes, parasocial warmth
Layer 08
Content Structure
Opening hooks, segment patterns, pacing, callback frequency, and closing moves.
Example: Cold open hook, 3-segment format, fast pacing, always ends with question
Layer 09
Visual & Format Language
Thumbnail patterns, text overlay style, color tendencies, and format choices.
Example: Bold text overlays, red+black palette, face-forward thumbnails
Layer 10
Platform Behavior
Posting cadence, engagement patterns, cross-promotion, and platform adaptations.
Example: 3x/week uploads, responds to top comments, cross-posts clips to TikTok
Process

How extraction works

DNA extraction is a three-stage process that moves from individual content analysis to a unified channel identity profile.
Stage 1
📹
Per-Video Analysis
Each piece of content is analyzed independently across all 10 DNA layers. Local LLM extracts structured data from transcripts and metadata.
Stage 2
📊
Batch Rollups
Individual analyses are grouped into batches and rolled up. Patterns emerge, outliers are flagged, and consistency scores are calculated.
Stage 3
🧬
Channel Synthesis
Batch rollups are synthesized into a unified DNA profile with confidence bands. The result is a complete, actionable identity fingerprint.