Key Takeaways
- A connected 2D and 3D workflow: CLO brings pattern drafting, grading, garment construction, and 3D fit review into one working environment. Its Pattern Drafter can generate parametric patterns from measurements, while grading tools help teams work across sizes.
- Fit review with fit maps: CLO’s fit maps provide a clear visual way to identify areas that are tight or may not be wearable. As with any simulation, the result depends on the quality of the avatar, pattern, and fabric settings.
- AI as a starting point: CLO’s AI-assisted tools can help translate sketches and ideas into draft patterns and visual content. Generated work still needs a designer’s technical review before it is ready for production.
- Useful export and collaboration options: CLO supports common formats used in downstream 3D workflows. CLO-SET complements the design process with browser-based garment review, annotations, version tracking, and shared assets.
- Set realistic expectations: Virtual sampling can help teams review more decisions digitally, but it does not eliminate the need for physical samples in every case. Results depend on the product and how the workflow is implemented.
2D Pattern Drafting and Parametric Size Grading
Apparel development works best when the 2D pattern and 3D garment stay connected. Designers can adjust pattern pieces, review the garment on an avatar, and refine the design without losing sight of how those changes affect the overall fit.
CLO brings pattern creation and 3D simulation together. Pattern Drafter lets users build parametric patterns from measurements, including measurements matched to a CLO avatar. Pattern pieces can then be adjusted, graded across sizes, and checked in 3D. CLO also supports production-oriented exchange formats such as DXF, Adobe Illustrator (AI), and vector PDF.
That link between drafting and visualization is useful for both independent users and product development teams. Rather than treating the 2D pattern and 3D garment as separate tasks, users can move between them as the design takes shape. Pattern and grading decisions still need the judgment of an experienced pattern maker, especially when translating a design into production-ready specifications.
Research on the transformative effect of 3D sampling technology in the ready-made garment industry discusses how digital sampling can support design precision, workflow efficiency, and reduced material use. The degree of benefit depends on the garment, the organization’s process, and the quality of the digital inputs.
Fabric Simulation Physics, Fit Maps, and Fit Validation
A virtual garment is only as useful as the pattern, avatar, and fabric information behind it. CLO’s 3D simulation helps designers see how garments drape on an avatar, while fit maps make areas of tightness and potential wearability issues easier to spot during review.
Fit maps are a visual aid, not a substitute for testing a garment on a person or validating fabric behavior in production. For a useful review, teams should use appropriate avatar measurements and fabric settings, then interpret the result alongside construction knowledge and any physical tests required for the product.
CLO’s workflow can also support digital material libraries and review processes that keep fabric and garment decisions visible as a design develops. Digital simulation can make it easier to catch issues before cutting a physical sample, though the realism of the result depends on the accuracy of the underlying material data and the intended use of the garment.
Some brands have described using 3D garment review to reduce physical sampling. Dainese, for example, has reported reaching a final product with one physical prototype in 90% of cases, compared with three or four iterations in its earlier process. Calida has described reviewing technical patterns on 3D avatars before cutting physical fabric samples. These are reported company outcomes, not a guarantee that every product team will see the same reduction.
Research on the use of 3D sampling in the ready-made garment industry also notes practical adoption challenges, including setup costs, material realism, and training. Digital sampling can improve review and communication, but teams should plan for the work needed to build dependable digital assets and processes.
AI-Assisted Ideation and Prototyping
AI can help move early concepts into a form that designers can evaluate and develop. In CLO, AI-assisted tools connect ideation with garment work: features such as Sketch on Avatar can help users translate a drawn silhouette into editable pattern shapes, while Pattern Drafter can generate a starting point from measurements or a sketch.
These tools are best treated as accelerators, not automatic replacements for technical design. Generated patterns need to be checked for shape, fit, construction, and production requirements. A useful workflow combines quick exploration with the pattern maker’s knowledge of how a garment is assembled and worn.
CLO also includes AI tools for visual content and avatar poses. These can support concept development and presentation alongside the core garment workflow. Availability and functionality may change over time, so users should consult CLO’s current product guidance when planning a workflow.
For teams, the practical value of AI is less about generating a finished product in one step and more about making it easier to explore variations, communicate an idea, and move into a reviewable digital sample. The designer remains responsible for making sure the garment works as intended.
Pipeline Interoperability and Engine Export
CLO supports a range of export workflows for teams that need to use garment assets beyond the design environment. Depending on the project, users can prepare garment geometry for visualization, animation, or further development in other 3D tools.
CLO Export Capabilities
CLO includes tools for preparing garment assets and pattern information for downstream workflows:
- Geometry and rigging: The EveryWear workflow supports garment skinning and FBX export, with tools to optimize geometry and remove unnecessary internal garment surfaces.
- 3D scene formats: CLO supports glTF exports with animation and USD/USDZ workflows, including Omniverse Connect. Export requirements vary by destination, so teams should check geometry, materials, and rigging after transfer.
- Production information: Users can export pattern layouts and production-related information, including BOM and nesting-based summaries, depending on the workflow and configuration.
As with any file exchange, a clean export depends on the needs of the receiving application. Teams should test a representative garment early to confirm that materials, topology, scale, and animation behave as expected.
CLO and CLO-SET in a Fashion Workflow
CLO is built around fashion design and garment development, from 2D patterns to 3D simulation. CLO-SET extends that work into a shared digital workspace where teams can review garments, add feedback, track versions, and manage design assets.
CLO-SET’s browser-based 3D viewer lets colleagues inspect a garment without working directly in the authoring software. Annotations can be pinned to specific areas of the garment, helping reviewers discuss fit, construction, or visual details in context. Version history helps teams keep feedback connected to the design iteration being reviewed.
For teams managing broader product information, CLO-SET can also support shared asset libraries and the organization of product development content. The value is practical: fewer disconnected files and clearer communication around the digital sample. Its role is complementary to CLO’s garment creation and simulation tools, rather than a replacement for pattern-making expertise or production review.
A Practical Starting Point
- For individual users and freelancers: CLO provides a connected environment for drafting, grading, simulation, and presentation. Active students enrolled at an accredited university may also qualify for a CLO individual subscription license. Eligible students may receive a student discount by submitting appropriate enrollment documentation through CLO’s user support team for verification.
- For teams reviewing designs together: Pairing CLO with CLO-SET gives teams a place to share digital garments, collect contextual feedback, and keep track of versions. Establishing clear review steps and naming conventions can make collaboration smoother.
- For learning and skills verification: CLO Academy is currently free for all individual subscribers, including active students. It does not currently offer quizzes or certificates of completion. CLO offers a separate, paid certification exam; successful candidates receive an official CLO certificate verifying their proficiency in the specific version of the software used during the test.
Frequently Asked Questions
Can CLO export garment models for use in Unreal Engine and Blender?
CLO supports common 3D exchange formats, including FBX and glTF. The right export settings depend on how the garment will be used. Before building a larger pipeline, test a sample garment in the destination application and check the mesh, materials, scale, and any rigging or animation requirements.
How does measurement-based pattern grading work in CLO?
Users can create parametric patterns from measurements and add size grading based on entered values or grading increments. The pattern can be reviewed on an avatar in 3D, helping designers assess how changes across sizes affect the garment. Pattern makers should still validate the measurements and grading rules against the intended fit and production specifications.
Can AI generate production-ready sewing patterns from a sketch?
AI-assisted tools can help generate draft geometry from sketches or design inputs, but the result should not be treated as production-ready without review. A pattern maker should check fit, construction, seam relationships, and manufacturing requirements before the pattern moves forward.
How much physical sampling can be reduced with 3D design?
There is no single reduction that applies to every team. Results depend on garment complexity, digital material and avatar quality, staff experience, and how a company uses virtual reviews. Dainese has reported reaching a final product with one physical prototype in 90% of cases, compared with three or four iterations in its earlier process. That company-reported result illustrates what may be possible in a specific workflow, not a typical outcome guaranteed for other organizations. Digital sampling can reduce some physical iterations, but teams may still need physical samples for fit, material, construction, and production validation.