Madgicx
Meta optimisation suite — bid automation + AI Marketer chat for performance Q&A.
Meta-heavy teams looking for bid-side automation and a Meta-focused AI assistant.
Madgicx is a Meta optimisation suite — bid management, creative diagnostics, and the AI Marketer chat for performance questions. It is deep on Meta and shallow elsewhere. Omniscia is cross-platform from the ground up: Meta, Google, and TikTok unified, with a single Cortex model reading performance across all three. Pair them only if you are Meta-heavy and want extra Meta-side optimisation; otherwise Omniscia covers the union.
Meta optimisation suite — bid automation + AI Marketer chat for performance Q&A.
Meta-heavy teams looking for bid-side automation and a Meta-focused AI assistant.
Closed-loop AI creative intelligence across Meta, Google Ads, and TikTok.
You want to score creatives before spend, read performance across all three platforms, score competitors on the same scale, and have a model that retrains on your account data over time.
Only the rows where capability differs are shown. Parity rows are hidden — see the full comparison for everything.
Reads on creative quality before any budget is spent.
| Capability | Omniscia | Madgicx |
|---|---|---|
| Pre-launch creative scoring (6-cat + clustering)Visual diversity, hook variety, angle coverage, format mix, audio diversity, text/CTA — scored before any spend. | ✓ | — |
| Andromeda fingerprinting (same creative across platforms)Auto-link the same creative running on Meta, Google, and TikTok via perceptual hash + audio fingerprint + CLIP embedding. | ✓ | — |
| Audio MFCC fingerprint clusteringSonic similarity across an ad set surfaces sound-driven clustering Meta delivery is sensitive to. | ✓ | — |
| CLIP visual similarity matrix512-dim embeddings on every frame; explicit similarity matrix flags overlap before delivery throttles it. | ✓ | — |
| Per-second hook fingerprinting (first 3s diversity)Frames pinned at hook / transition / body / CTA; hook-section fingerprints flag repetition the algorithm punishes. | ✓ | — |
| Network-effect percentile benchmarks (your score vs vertical)P50 / P75 / P90 across the network and your vertical, on every score — not just an isolated number. | ✓ | — |
| Sample-size + confidence inline on every readEvery forward-looking number names the N and confidence band that produced it. No hand-waved ROAS lifts. | ✓ | — |
| Landing page alignment (5-dimension scoring)Scores ad message vs landing page across hook, value prop, CTA continuity, visual continuity, and brand voice. | ✓ | — |
Reading what shipped — across Meta, Google, and TikTok.
| Capability | Omniscia | Madgicx |
|---|---|---|
| Cross-platform unified (Meta + Google Ads + TikTok native)One model reading all three platforms; not three siloed dashboards stitched together. | ✓ | ◐Meta-only |
| Survival-analysis fatigue prediction (Cox PH model)Multi-day lead time on fatigue risk, modelled per asset and per platform. | ✓ | ◐Meta-only fatigue flags |
| Cross-platform ROAS / CTR / CPA pattern analysis with confidenceRead patterns across Meta, Google, and TikTok with sample-size and confidence shown alongside. | ✓ | ◐Meta-only |
| Per-asset attribution (which variant carried ROAS)Asset Impact panel decomposes campaign ROAS down to the individual creative. | ✓ | ◐ |
| LTV-adjusted ROAS for multi-product brandsScore creatives on lifetime value, not first-purchase ROAS — the right read for subscription and repeat-buyer brands. | ✓ | — |
AI strategist + data-backed briefs + trend extraction.
| Capability | Omniscia | Madgicx |
|---|---|---|
| AI strategist with full data context (Scia)Chat assistant that sees every Lens score, every Nexus correlation, every Intel finding for your account. | ✓ | ◐AI Marketer (Meta-focused) |
| Data-backed brief generation (Forge directives)Briefs cite the campaigns, scores, and competitor reads that produced them — with confidence inline. | ✓ | — |
| Creative lineage / ancestry trackingGenealogy DAG linking iterations of the same idea; see which ancestor variant carried the win. | ✓ | — |
| Real-time trend feed + Helix 5-layer extraction32+ source feed (research, ad libraries, social, news) with a 5-layer extractor for hook / format / angle / sonic / cultural trends. | ✓ | — |
Watching the rivals, on the same scoring scale as your own work.
| Capability | Omniscia | Madgicx |
|---|---|---|
| Performance tier inference from ad longevityIndustry-standard proxy: longer-running ads in a competitor library are typically the winners. Surfaced as tiers, never invented ROAS. | ✓ | — |
| Brand library tracking with delta alertsNew competitor creatives, retired creatives, and tier-jumps surfaced as Signal entries you can review. | ✓ | — |
Models that retrain on your account, not just industry averages.
| Capability | Omniscia | Madgicx |
|---|---|---|
| Per-user Cortex retraining (private weights)After 30+ linked campaign-analysis pairs, your weights blend 70% your data with 30% global. Private to your account. | ✓ | — |
Publishing, governance, white-label, scheduled reports.
| Capability | Omniscia | Madgicx |
|---|---|---|
| Cross-platform publishing (Meta + Google + TikTok)Push approved ads to all three platforms with Cortex-informed priors. | ✓ | ◐ |
| Approval workflow + team governanceReviewer queue, audit trail, role-based permissions, agency-multi-client mode. | ✓ | — |
| White-label + public API + scheduled reportsBrand the dashboard, hit the v1 API, send weekly PDF reports to clients on a schedule. Agency-tier. | ✓ | — |
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