When enterprise teams need thousands, or even hundreds of thousands, 3D models to train AI systems, they often face a decision. Do you rely on ready-made models from marketplaces to move fast and stay on budget, or do you commission custom assets and risk delays and rising costs?

In practice, both options have their place. Marketplaces are a great solution when speed and volume are the priority. But for companies that need specific asset classes, consistent geometry, or models built under strict technical specs, there’s another option worth considering.

At Modelry, we built a solution for that scenario: custom 3D datasets produced at scale, within budget, and under full control.

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Define What You Need Before You Start

One of the best ways to save time and ensure consistency is to clearly define your requirements before sourcing 3D models. That includes:

• File formats and coordinate systems;
• Polygon count ranges or model resolution;
• Texture naming conventions;
• Semantic consistency across classes or variants.

For AI teams, clean data matters. Slight changes in naming, structure, or resolution can make datasets harder to train on or reproduce later. Getting this part right up front has a big impact on how usable your dataset is over time.

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How Modelry Fits Into the Picture

Modelry is a platform designed for structured 3D model production at scale. It’s used by teams that need full control over what is produced, but still want to move fast and avoid managing dozens of freelancers or internal workflows.

Here’s how it works:

• Models are made to spec. You define the technical requirements; we assign the right designers and validate every model against your specifications.
• Predictable delivery at scale. Hundreds of verified 3D artists work in parallel under one coordinated process, so large datasets can be created quickly and consistently.
• Automated + human QA. Every asset goes through over 200 automated checks (like format, topology, naming) and a layer of expert review to catch anything else.
• DAM for dataset control. Clients receive access to a Digital Asset Management system where they can store, search, track versions, and re-download assets.
• Clear ownership with flexible resale. Clients fully own the models they order. But if they allow it, designers can also resell those models on the marketplace. This lowers the original cost for the client and fairly rewards the creators. It’s a practical and ethical way to make high-quality 3D datasets more affordable.

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Why This Approach Works for AI Training

AI models need more than just high-quality visuals. They need large, clean, and consistent datasets. Modelry is tailored for exactly that.

• Consistency across categories. Whether it’s 1,000 chairs or 100,000 nature environments, assets follow shared specs across every instance.
• Parallel production. Instead of sourcing piecemeal over time, we can produce large batches in a short period by coordinating many designers at once.
• Reusable structure. When you want to add variations, refine texture maps, or expand a category, the original model data is already structured and accessible.

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Marketplace Also Play an Important Role

For many enterprise teams, CGTrader marketplace is still the fastest way to sort through large numbers of models. It’s a good fit when the priority is speed or when pre-existing models meet your needs. Many AI companies successfully build datasets from marketplace assets, especially when the project theme or tech specs are more standard.

Modelry provides another option - built for teams that need more control, more customization, or highly specific asset types that aren’t widely available off the shelf.

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Both stock marketplaces and custom model production offer valuable benefits. The key is to work with a partner experienced in both, who can help you choose the most efficient and scalable approach for your specific needs. With the right strategy, it’s entirely possible to get custom 3D models at scale - without compromising on quality, speed, or ethics.