# Getting Started Atlas combines visual workflow design, diverse AI model orchestration, and asset creation specific AI agents into a single platform built for both artists and developers. ## Who Atlas is for Atlas is designed for **professional game studios and creative teams** producing 3D content at scale. The platform is built around real production workflows rather than one-off asset generation, which is why most of its users sit in roles like: * **Technical artists** building reusable asset pipelines for their studio * **Art directors** maintaining style consistency across asset libraries * **Engine programmers** integrating AI-generated content directly into Unreal Engine, Unity, or Blender * **Production leads** measuring and reducing asset turnaround time * **Studio CTOs and innovation teams** evaluating where AI fits in their pipeline If your work involves shipping 3D assets to a game, a virtual production, or an interactive experience, Atlas is built for you. **Visual Workflow Design** A common criticism by artists using AI today is that it does not produce the result they want, and this can be seen as two separate issues: 1. Lack of control / editability 2. Lack of quality - reliance on a single AI model Atlas uses a node based system which gives the artist a clear level of control to edit parts of assets in both 2D and 3D space in a non-destructive editor (point 1). And it encourages users to establish that control through the combination of AI models (e.g. isolating object parts with Gemini before generating them in 3D with CSM). Once an artist connects multiple AI models together the quality of the result improves significantly. Here is an example of an artist explaining his workflow: > “I used images from Grok Imagine, refined them with Nano Banana, Tripo for raw 3D generation, Hunyuan for lowpoly and UV unwrap, Trellis2 for texturing and AI upscaling.” Connect these generation and processing nodes on Atlas, and then add export nodes to create repeatable, version-controlled workflows that can be shared across teams or deployed as APIs - meaning the workflow runs at scale directly in Unreal Engine and Unity. Sample Capabilities (AI Models available on Atlas) * Text & Reasoning - Use AI extract key information from style guides and/or art bibles, and assist in prompting and workflow construction, and even automatically evaluate results based on user preferences. * Image Generation - Generate concept art from descriptions and/or image references with multiple style options * Multimodal Processing - Isolate objects, remove backgrounds, apply style transfer and edit everything from asset components to material properties * Image-to-3D - Reconstruct detailed 3D meshes from single reference images with a diversity of topology and texture options * Mesh Optimization - Auto-scale, set real-world dimensions, adjust pivots, reduce polycount, clean topology and all the other post-processing work required to make assets game ready for different engines Integration-First Architecture Design Simply being able to create high quality assets on the Atlas platform isn’t sufficient as it takes artists out of their established content creation and world building pipelines. Every workflow built on Atlas can be exported as a production API with a single click. Integrate Atlas directly into existing pipelines, DCC tools, or game engines. Full versioning ensures deterministic, reproducible results and quality control. * Direct integration with Unreal Engine, Unity, and Blender (and custom engines) * Webhook support for async job processing * Complete audit trail for enterprise compliance *In practice, this simply means once a workflow has been built with Atlas the entire team can use it directly in their software of choice.* ## How to navigate this documentation * [**Node Index**](/atlas-ai-studio-overview/node-index.md) — complete reference for every available node, with use cases, pitfalls, and FAQs per category. Start here when you're building or debugging a specific workflow. * [**3D & Gaming Focus**](/atlas-ai-studio-overview/3d-and-gaming-focus.md) — what makes Atlas different in the 3D-and-gaming context (retopology, PBR, engine-specific presets, integration patterns). * [**Atlas AI Agent**](/atlas-ai-studio-overview/atlas-ai-studio-overview.md) — how the multi-agent assistant helps build workflows, diagnose issues, and propose improvements. * [**Atlas x GCP**](/atlas-ai-studio-overview/atlas-x-gcp.md) — the Google Cloud deployment story, including procurement, billing, and integration with existing GCP commits. * [**Testimonials**](/atlas-ai-studio-overview/testimonials.md) — real customer feedback from studios shipping with Atlas in production. ## Common starter pitfalls A few mistakes that consistently slow down new users: * **Treating Atlas like a single-model generator.** The platform's biggest leverage comes from chaining multiple models (e.g., image generation → 3D conversion → mesh optimization → texturing) into one workflow. Single-step usage misses most of the value. * **Skipping the Atlas AI Agent.** The agent is trained to help with workflow construction; new users who try to manually wire every node spend hours where the agent would have taken minutes. Lean on it during early exploration. * **Generating before defining the production target.** Atlas can produce wildly different output styles depending on backend and parameter selection. Pin the target (engine, polycount budget, texture resolution, style direction) before you start, not after. * **Ignoring the API export.** Workflows that stay inside the Atlas web UI work for individuals, but the real production lift comes from exporting workflows as APIs and integrating them into existing tools (Unreal, Unity, Blender, custom pipelines). See [API Nodes](/atlas-ai-studio-overview/node-index/api-nodes.md) for the export flow. * **Comparing single-shot Atlas output to Meshy or Tripo.** Atlas is orchestration across many backends including those. A like-for-like single-model comparison misses Atlas's defining capability. Compare Atlas pipelines to your current studio pipeline, not to single-model competitors. ## Frequently asked questions **Do I need to know how to code to use Atlas?** No. The platform is built for artists and technical artists, not developers. The node-based visual editor and the Atlas AI Agent both handle workflow construction without requiring scripting. Code becomes relevant only when integrating exported APIs into game engines or custom backends, and you can use the official [Unity and Unreal plugins](/atlas-ai-studio-overview/node-index/api-nodes.md) to skip that step too. **Which game engines does Atlas integrate with?** Atlas has official plugins for Unity (2023.1+) and Unreal Engine (5.5+). It also integrates with Blender via an add-on. Workflows exported as APIs work with any HTTP-capable engine or custom backend. **How do I avoid spending too many credits during exploration?** Use the lightweight versions of generation nodes during ideation (Text → Image (Fast), Fast Image → 3D), and reserve the high-quality variants for final passes. The Atlas AI Agent can also help structure workflows efficiently to avoid redundant generation steps. **Can multiple team members collaborate on the same workflow?** Yes. Workflows are version-controlled and shareable. Once a workflow is built and tested, it can be exported as an API and used by the entire team through their software of choice, or imported into the Atlas web UI for collaborative editing. **What kind of input does Atlas need to produce high-quality output?** Generation quality tracks input quality. For 3D generation specifically, clean reference images (isolated subject, neutral background, three-quarter angle) produce dramatically better results than cluttered inputs. See [3D Generation Best Practices](/atlas-ai-studio-overview/node-index/mesh-nodes/3d-generation-best-practices.md) for the deeper guide. **Is Atlas suitable for solo developers or only for AAA studios?** The platform is designed for studios with production pipelines, but solo developers and small teams can use it too. The platform's strengths (multi-model orchestration, workflow reuse, API export) compound at studio scale, but the underlying capabilities work for any production size. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.atlas.design/atlas-ai-studio-overview/getting-started.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.