I built BindWeave, a subject-consistent video generation model that fuses multimodal reasoning with diffusion to keep your characters, objects, and creative intent perfectly aligned across shots. Instead of prompting frame by frame, BindWeave understands who’s who and what’s happening — maintaining story and visual continuity from single-person clips to multi-actor scenes.

What it does

Cross-Modal Integration for Fidelity – Binds text intent to visual references for faithful generation (MLLM-DiT core).

Single or Multi-Subject Consistency – Keeps identities and roles stable across frames and scenes.

Entity Grounding & Role Disentanglement – Reduces character swaps and attribute drift.

Prompt-Friendly Direction – Understands shot types, interactions, and cinematic notes.

Reference-Aware Identity Lock – Use one or more images to maintain the same subject identity.

Designed for Creative Stacks – Fits ads, trailers, explainers, and short-form storytelling.

Who it’s for

Creators, filmmakers, and marketers

Studios producing multi-scene or multi-actor videos

Educators, storytellers, and localization teams

https://www.bindweaveai.com/?i=d1d5k

Why it matters: BindWeave bridges the gap between text-to-video generation and consistent storytelling. It ensures that identities, roles, and scenes stay coherent — unlocking true narrative control in AI video generation.

I’d love feedback from the HN community — especially on cross-modal fidelity, multi-scene continuity, and real-world creative use cases.