diff --git a/entities/entertainment/seedance.md b/entities/entertainment/seedance.md
new file mode 100644
index 000000000..a45eec795
--- /dev/null
+++ b/entities/entertainment/seedance.md
@@ -0,0 +1,21 @@
+---
+type: entity
+entity_type: company
+name: Seedance (ByteDance)
+domain: entertainment
+status: active
+tracked_by: clay
+created: 2026-03-11
+---
+
+# Seedance (ByteDance)
+
+ByteDance's AI video generation platform, competing with Google Veo, Runway, and Pika Labs. Seedance achieved #1 global ranking on Artificial Analysis benchmark in February 2026 with Seedance 2.0.
+
+## Timeline
+- **2026-02-01** — Seedance 2.0 launched: ranked #1 globally on Artificial Analysis benchmark, native 2K resolution (2048x1080), 4-15s dynamic duration, near-perfect hand anatomy scores in complex movements (magician card shuffling, pianist playing), phoneme-level lip-sync across 8+ languages, 30% faster throughput than Seedance 1.5 Pro
+
+## Relationship to KB
+- [[ai-video-hand-anatomy-fidelity-crossed-production-threshold-in-2026-making-visual-tells-unreliable]] — technical capability evidence
+- [[non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain]] — production cost convergence
+- [[domains/entertainment/_map]]
\ No newline at end of file
diff --git a/entities/entertainment/sora-openai.md b/entities/entertainment/sora-openai.md
new file mode 100644
index 000000000..b9d606f17
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+++ b/entities/entertainment/sora-openai.md
@@ -0,0 +1,21 @@
+---
+type: entity
+entity_type: company
+name: Sora (OpenAI)
+domain: entertainment
+status: active
+tracked_by: clay
+created: 2026-03-11
+---
+
+# Sora (OpenAI)
+
+OpenAI's AI video generation platform, launched as standalone app in late 2025/early 2026. Despite flagship positioning and massive distribution advantages, Sora faced significant retention challenges revealing demand-side constraints in AI video adoption.
+
+## Timeline
+- **2026-02-01** — Sora standalone app reached 12 million downloads but retention fell below 8% at day 30 (vs. 30%+ benchmark for top consumer apps), signaling demand-side constraint despite technical capability improvements across AI video sector
+
+## Relationship to KB
+- [[sora-8-percent-retention-signals-ai-video-tools-face-demand-constraint-despite-capability-breakthrough]] — retention data evidence
+- [[GenAI adoption in entertainment will be gated by consumer acceptance not technology capability]] — consumer acceptance barrier
+- [[domains/entertainment/_map]]
\ No newline at end of file
diff --git a/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md b/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md
index b0c317b22..a4f6f7d36 100644
--- a/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md
+++ b/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md
@@ -7,9 +7,14 @@ date: 2026-02-01
 domain: entertainment
 secondary_domains: []
 format: report
-status: unprocessed
+status: processed
 priority: medium
 tags: [ai-video-generation, seedance, production-costs, quality-threshold, capability]
+processed_by: clay
+processed_date: 2026-03-11
+enrichments_applied: ["non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain.md", "GenAI adoption in entertainment will be gated by consumer acceptance not technology capability.md", "consumer definition of quality is fluid and revealed through preference not fixed by production value.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "Two new claims extracted: (1) AI video hand anatomy crossing quality threshold, (2) Sora retention data revealing demand constraint. Three enrichments applied to existing claims about production costs, consumer acceptance, and quality definition. Two new entities created for Seedance and Sora. The Sora retention data is the most significant insight—it reveals demand-side constraint operating even among early adopters despite supply-side capability breakthroughs. Benchmark-to-production gap noted as limitation in hand anatomy claim."
 ---
 
 ## Content
@@ -59,3 +64,10 @@ Aggregated benchmark data on the leading AI video generation models in 2026 (See
 PRIMARY CONNECTION: `non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain`
 WHY ARCHIVED: The hand anatomy benchmark crossing signals that the quality threshold for realistic video has been substantially cleared — which shifts the remaining barrier to consumer acceptance (demand-side) and creative direction (human judgment), not raw capability.
 EXTRACTION HINT: The Sora retention data (supply without demand) is the most extractable insight. A claim about AI video tool adoption being demand-constrained despite supply capability would be new to the KB.
+
+
+## Key Facts
+- Seedance 2.0 ranked #1 globally on Artificial Analysis benchmark (February 2026)
+- Kling 3.0 edges ahead for straightforward video generation ease of use
+- Google Veo 3 breakthrough combined visual and audio generation
+- Benchmark methodology: 50+ generations per model, identical prompt set of 15 categories, 4 seconds at 720p/24fps, rated on 6 dimensions by 2 independent reviewers