The post‑Sora landscape of AI video generation centers on tools and models designed for production workflows, rapid repurposing, and consistent on‑screen characters. Rather than a single breakthrough model, the market has diversified into complementary categories: multimodal foundation models that prioritize speed and integration (e.g., LTXV‑13b/LTX family), creative platforms that combine generation with node‑based editing and APIs (Runway), browser‑first editors that convert text, URLs or slides into short branded assets (Pictory.ai), and specialist systems that lock in avatar, voice and personality across scenes (ShowHive). Supporting capabilities include precision animation and clip extraction for social formats (VidSimplify) and deep video understanding for indexing, search, summarization and programmatic workflows (TwelveLabs). As of 2026, relevance is driven by demand for scalable, editable video content across marketing, training, and streaming pipelines. Key trends are production readiness (models built for integration and throughput), workflow integration (APIs and node‑based chaining), content repurposing (automated clipping and branding), and fidelity controls for character continuity and voice. Equally important are tooling ecosystems that combine generation with analysis—enabling faster iteration, searchable archives, and moderated outputs. For teams evaluating solutions, the choice is increasingly about fit: foundation models and APIs for backend generation and customization; creative platforms for iterative editing and visual effects; browser editors for non‑technical content teams; and character systems for narrative consistency. Operational considerations—latency, cost, rights management, provenance, and moderation—now shape adoption as much as raw image or motion quality.