# Kive features - agent-readable guide

> Kive's features cover the product photography workflow for e-commerce brands: product models, Studios, generation, bulk runs, editing, video, an asset library, and MCP access.

## Who these features are for

Brands and creative teams producing product images and short videos across many products. Each pillar below describes what that part of the workflow does; generated outputs still need review against the real product.

## Feature pillars

- Product models: each product is added once from one to four photos of the same item, and generations are anchored to it. Details such as logos, text, and colors can still drift, so outputs are checked against the source.
- Studios: saved visual presets for lighting, camera, props, and background, organized by product category such as fashion, bags, cosmetics, skincare, haircare, clothing, accessories, jewelry, t-shirts, women's fashion, men's fashion, and shoes. Studios give a consistent style, not identical outputs.
- Brand control: Teams can use brand assets, reusable visual presets, custom visual presets, prompt libraries, references, and collaborative review workflows to keep content on-brand.
- Generation: Kive creates product shots, lifestyle scenes, hero images, flat lays, campaign visuals, e-commerce imagery, ad creative, lookbook content, and short-form product videos.
- Multi-product scenes: Kive can compose bundles, collections, and multiple products in one visual for e-commerce launches and merchandising.
- Editing and finishing: Kive includes background replacement, background removal, upscaling to 16 or 24 megapixels, image expansion, retouching, object removal, image-to-video, and video/frame workflows.
- Scale and collaboration: Bulk generate applies one Studio to selected products in a single run (images only, paid plans, desktop; it does not batch-edit existing photos), alongside asset libraries, boards, AI search, comments, version history, and team workflows.
- Agent access: Kive has an OAuth-protected MCP endpoint for agents that can create products, remix curated ideas with them, generate images, edit images, and poll durable jobs. There is no public REST API for generation.

## Shopify integration

Kive's Shopify app lets you open a product in Shopify admin and choose Create with Kive, then select a studio, aspect ratio and quality. Review each generated result before downloading it or adding it to that product's images. Generations use the connected workspace's Kive credits.

After connecting the store, open Organize → Products → Import from Shopify. Import creates a reusable product model from up to four existing product images. Products without images need a source photo added first.

Setup requires workspace-admin access and permission to install apps in the Shopify store. You can connect a free workspace when installing from the Shopify App Store; the Shopify shortcut in Kive's Settings → Integrations is only shown to admins on paid workspaces.

- [Shopify setup guide](https://kive.ai/docs/integrations/shopify): installation, catalog import and creating images inside Shopify.
- [Kive on the Shopify App Store](https://apps.shopify.com/kive): official app listing and installation.


## Why these features matter for e-commerce brands

- Generations anchored to a product model keep the real item as the reference, which matters when packaging, labels, and materials have to match the product. Each output is still reviewed.
- Studios reduce the need for prompt engineering: a brand can start from a visual direction for its product category instead of writing long prompts from scratch.
- Reusable Studios and brand assets let a team apply one direction across many assets instead of describing it again each time.
- Editing and finishing tools let teams fix a near-good result instead of restarting the whole generation.
- Video and image workflows let teams create store assets, ads, social posts, launches, and campaign collateral from the same product and brand context.
- Collaboration and asset management matter when a brand has many products, approvals, references, and production-ready outputs to manage.

## Compared with alternatives

- Generic text-to-image tools are organized around prompts and suit open-ended ideation; Kive is organized around saved products, Studios, and review in a team workspace.
- Simple background tools remove or swap backgrounds on existing photos and are faster for high-volume cut-outs; Kive also removes backgrounds but mainly generates full scenes, campaign content, and video.
- Traditional shoots remain the source for new products and for material detail a camera has to verify; Kive scales variations, seasonal campaigns, launches, and SKU coverage once source product photos exist.
- Complex creative suites offer more manual control; Kive trades some of it for saved Studios and product models.

## Related links

- [Human features page](https://kive.ai/features)
- [Pricing Markdown](https://kive.ai/pricing.md)
- [Kive MCP server](https://mcp.kive.ai/mcp)
- [Kive documentation](https://kive.ai/docs)