Cascadeur as an "assistive AI" 3D animation tool: local inference, documented training-data provenance, no training on user animations, video-to-pose mocap alpha, and a new MCP server hook
Nekki's Cascadeur publishes an unusually specific AI-use disclosure (R1): ML tools are AutoPosing, Inbetweening, AutoInterpolation and Video Mocap; AutoPhysics, Ragdoll, Animation Unbaking and Fulcrum cleaning are explicitly non-ML. Pose/inbetween models were trained on Nekki's own game animation (hand-key + mocap for Shadow Fight and SPINE), supplementary mocap and purchased third-party packs "certified for AI use"; the video mocap uses open-source libraries plus post-processing. User animations are not collected for training, and all tools run locally (mocap downloads a ~700 MB mocap.pt package once). Video Mocap (Alpha, R2): import an .mp4 reference, select N timeline frames, get N keyframed poses - single actor only, poses can miss nuance because a 2D view hides depth; intended for animation drafts, then refine with AutoPosing/physics. 2026.2 (R3): Additive Layers (alpha), Easing on intervals, Inbetweening/Motion Generation retrained on larger datasets and now passing style betw...
Structured fields
{
"citations": [
{
"url": "https://cascadeur.com/help/category/285",
"note": "Q3 training data; Q4/Q5; Limitations; 2026.2 Other Updates; Indie plan"
},
{
"url": "https://cascadeur.com/help/category/203",
"note": "Q3 training data; Q4/Q5; Limitations; 2026.2 Other Updates; Indie plan"
},
{
"url": "https://cascadeur.com/help/category/319",
"note": "Q3 training data; Q4/Q5; Limitations; 2026.2 Other Updates; Indie plan"
},
{
"url": "https://cascadeur.com/plans",
"note": "Q3 training data; Q4/Q5; Limitations; 2026.2 Other Updates; Indie plan"
}
]
}Evidence claims
- [sourced_fact] Nekki's Cascadeur publishes an unusually specific AI-use disclosure (R1): ML tools are AutoPosing, Inbetweening, AutoInterpolation and Video Mocap; AutoPhysics, Ragdoll, Animation Unbaking and Fulcrum cleaning are explicitly non-ML. Pose/inbetween models were trained on Nekki's own game animation (hand-key + mocap for Shadow Fight and SPINE), supplementary mocap and purchased third-party packs "certified for AI use"; the video mocap uses open-source libraries plus post-processing. User animations are not collected for training, and all tools run locally (mocap downloads a ~700 MB mocap.pt package once). Video Mocap (Alpha, R2): import an .mp4 reference, select N timeline frames, get N keyframed poses - single actor only, poses can miss nuance because a 2D view hides depth; intended for animation drafts, then refine with AutoPosing/physics. 2026.2 (R3): Additive Layers (alpha), Easing on intervals, Inbetweening/Motion Generation retrained on larger datasets and now passing style between keys, BVH animation import, "support for a simple MCP server" in the Scripts menu, PySide custom UI, camera exposure (ISO/shutter/aperture), UE 5.8 LiveLink, Meshy rig template fix (2026.2.3). Pricing (R4): Free (full toolset, non-commercial, .casc export only), Indie $19/month (FBX/DAE export, revenue < $100k/yr), Pro $49/month or $33/month billed annually (unlimited commercial, retargeting, quadruped autoposing), Teams 2-6 seats same per-user price; annual Indie/Pro include perpetual-licence builds. Fit: a keyframe-centred alternative to prompt-to-motion generators where the animator keeps control and provenance is documented - useful for clients asking how the AI was trained. · locator: Q3 training data; Q4/Q5; Limitations; 2026.2 Other Updates; Indie plan source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |