Bezi AI
Bezi AI is a tool designed to simplify and accelerate the design process, particularly for 3D apps and games. It streamlines the workflow by allowing users to g...
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What is Bezi AI?
Bezi is an AI-powered development assistant and platform focused on game and 3D project workflows, tightly integrated with Unity to provide project-aware suggestions, code generation, debugging help, and asset generation. The product surfaces real-time project context (code, scenes, prefabs, assets, packages and more) so the assistant can propose changes, generate scripts that fit the existing codebase, and debug runtime and compilation issues without requiring lengthy manual context. It also includes a generative 3D asset workflow where users can create preview models from text prompts, drag them into scenes, upscale geometry and textures, and iterate on variations directly inside the Bezi interface. Targeted at solo developers, indie teams, and studios working in Unity (and 3D designers/prototypers), Bezi aims to speed prototyping, reduce repetitive work, and keep outputs consistent with team standards while preserving project privacy and not using user code/assets to train models.
Bezi AI pricing
Pricing model: Freemium
Bezi offers a free tier / trial to start and then paid plans for individuals and teams; exact plan names and tiered features are presented on their pricing page with team-level pricing and contact options for enterprise or sales inquiries. The website describes a free trial and subscription options that include unlimited debugging help and code generation for paid users, with higher-tier plans focused on team collaboration and additional capabilities; for custom or enterprise needs the site directs prospective customers to contact sales or email [email protected].
Bezi AI pros
- deep Unity project awareness (reads code, scenes, prefabs, assets)
- generates ready-to-use scripts that match existing codebase patterns
- built-in debugging assistance for compilation and runtime errors
- Ask vs Agent modes for ideation vs code modification workflows
- in-editor integration so suggestions apply directly to the Unity Editor
- generative 3D asset creation from text prompts inside the platform
- produces 4 variations per prompt for fast iteration
- ability to drag-and-drop generated preview models into scenes
- upscale operation to produce higher-resolution geometry and textures
- creates quick variations from a selected generated model
- command center and Bezi AI panel for streamlined prompting
- threaded conversations with project-specific context
- controls and guidance for prompt structure to improve results
- security promise: project source and assets not used to train models
- designed to compound output across teams and maintain consistency
Bezi AI cons
- currently only supports Unity (no other engines yet)
- upscaling models may take significant time (can take up to 10 minutes)
- generated preview models are low-resolution by default
- Agent Mode requires extra setup (version history/tool integration) for safe changes
- thread length and multi-topic threads degrade response quality
- prompt quality strongly affects outputs—requires careful prompting
- some advanced operations require paid plan or trial gating
- real-time project access requires granting the platform deep project permissions
Frequently asked questions about Bezi AI
What engines does Bezi support?
Bezi currently supports Unity only; the product is built as a Unity-first, project-aware assistant and the team indicates plans to expand to additional engines in the future.
How does Bezi access my project data?
Bezi connects to your Unity project and reads project context such as scripts, scenes, prefabs, assets, and packages to provide tailored suggestions; this deep integration enables script generation and debugging that fits your existing codebase.
Will my code or assets be used to train the AI?
Bezi states that your source code, assets, and game data are not used to train AI models; they provide a security program and a contact email for security questions to support that claim.
What is the difference between Ask Mode and Agent Mode?
Ask Mode is intended for ideation, planning, and searching for information while Agent Mode is specifically for writing or modifying scripts; Agent Mode should be used only after setting up version history or a safe testing workflow to avoid unwanted changes.
How do generated 3D assets work in Bezi?
You type a descriptive text prompt which produces four preview variations; you can drag a preview into the scene, create new variations from a selected preview, or run an upscale operation to generate higher-resolution geometry and textures (upscales can take longer, sometimes up to 10 minutes).
What quality of models does Bezi produce by default?
Generated preview models are typically low-resolution for quick iteration, and the platform provides an upscale feature to refine texture and geometry into higher-resolution assets when needed.
How should I write prompts for best results?
Bezi recommends a prompt structure that states the current state, the expected/ideal state, and the desired response format; use descriptive language, tag relevant project assets inline, attach images if helpful, and keep prompts focused to improve output quality.
Are there best practices for using threads?
Yes—keep threads short (aim for fewer than 10 prompts), cover only one topic per thread, and start a new thread when the task changes because long or multi-topic threads reduce response quality.
What happens if I don’t like Bezi’s response?
The documentation advises against prompting ‘fix’ or asking to iteratively fix a bad response; instead, edit the original prompt to add missing details and regenerate, or start a new thread that summarizes what you liked and re-asks the question.
How do teams collaborate and maintain consistency with Bezi?
Bezi acts as a source of truth across connected Unity projects and data sources, offering project-aware suggestions, teams/plan features for collaboration, and guidance to align changes with team standards so outputs remain consistent across contributors.