Viz 360

The description states that Viz 360 is an AI-first pre-production workspace for filmmakers. It transforms a screenplay into a complete production plan, including breaking stories into scenes and shots, generating keyframes and storyboard prompts, organizing everything on a timeline, and playing back the story as a lightweight animatic or story preview.

It supports:

• Project creation and multi-project dashboard
• Screenplay generation and editing
• Scene and shot breakdowns
• Progressive keyframe and storyboard prompt generation
• Timeline-style editors for scenes and shots
• Text-first playback at project, scene, and shot levels
• SQLite-backed local persistence
• Support for OpenAI, Gemini, and Ollama-based AI providers

It is described as a "local demo flow" with no full media generation yet, instead showing prompts, script coverage, context, and keyframe intent directly in the preview.

Inference The product functions primarily as an interactive planning tool that uses AI to structure creative workflows rather than generate final visuals.

The author claims Viz 360 addresses a broken AI video workflow where creators jump between tools, losing context and wasting time. It positions itself as solving this by offering a single workspace for pre-production that preserves project-wide creative context.

Key claims:

• "Viz 360 optimizes decisions" rather than optimizing generation.
• The goal is to avoid generating the wrong videos in the first place.
• It acts as a "production layer between concept and render."
• It helps reduce unnecessary AI generation by validating decisions early.

The positioning has evolved from an idea about AI filmmaking into a structured product with defined workflows: Idea → Script → Scenes → Shots → Keyframes → Story Preview → Final Video.

Inference The author sees Viz 360 as a shift toward planning-first AI filmmaking, not just generation-first tools.

The description states that Viz 360 targets filmmakers who want to plan their projects before investing in expensive video generation. It is built for creators who need a director’s workspace, not just a generation box.

It implies:

• Independent filmmakers or small production teams
• Users looking to reduce waste in AI-generated content workflows
• People who value continuity and context across creative stages

There is no mention of specific customer segments beyond general "creators" or "filmmakers."

Inference The ICP appears to be indie filmmakers, directors, or creative teams working with limited resources and seeking structured planning tools.

The description does not provide any information about pricing models, monetization strategies, or business models. It only describes the current local demo version of the product.

Not evidenced

The project is built using:

• Framework: Next.js
• UI Library: React
• Language: TypeScript
• Database: SQLite
• AI Providers: OpenAI API, Gemini, Ollama
• Libraries: better-sqlite3, provider-abstraction

It includes:

• Server-side APIs
• Local demo authentication
• Timeline-oriented editing components
• Browser-tested core flows
• Structured project hierarchy with CRUD operations for projects, scenes, shots, keyframes, and layers

The architecture supports switching between local models (lower cost) and cloud models (higher quality), suggesting a potential path to commercial scalability.

Inference The tech stack suggests a lightweight, developer-focused approach that could scale toward hosted services or enterprise integrations.

The description states:

• Viz 360 is a local demo flow
• It includes working features such as project creation, screenplay editing, scene/shot breakdowns, keyframe generation, timeline editors, and text-first playback
• It avoids faking outputs and instead shows prompts and intent in previews
• It was built for the OpenAI 2026 hackathon

There is no evidence of revenue, customers, or adoption beyond the author’s own use case.

Not evidenced

The description does not mention competitors or how Viz 360 compares to existing tools in the AI filmmaking or creative workflow space. It focuses on its unique value proposition — optimizing decisions over generation — but does not name similar products or platforms.

Not evidenced

• No commercial traction: The product is described as a local demo with no evidence of users, customers, or revenue.
• Limited scope: It currently avoids full media generation and relies on placeholders; this may limit its appeal to early adopters.
• Single founder: The team size is listed as one person (Sumit Chavan), which raises questions about scalability and execution capacity.
• Unclear monetization path: No pricing or business model details are provided, making it hard to assess commercial viability.
• Hackathon origin: While this can indicate innovation, it also suggests a prototype rather than a mature product.

Inference The risk of failure is high if the author cannot demonstrate real-world utility beyond personal use or hackathon experimentation.

1. What specific pain points in current AI filmmaking workflows are you solving, and how do you know?
2. Have you tested Viz 360 with actual filmmakers or production teams?
3. How do you plan to transition from a local demo to a scalable SaaS or hosted offering?
4. Are there any early adopters or pilot users who have provided feedback on the workflow?
5. What are your plans for integrating full media generation (video/image) into the platform?
6. How do you intend to monetize this tool, and what pricing model are you considering?