Adobe Adds AI Photo Critique and Editing Features to Project Indigo Camera App

Adobe has introduced a new collection of experimental artificial intelligence features for its iOS camera app, Project Indigo, expanding the app beyond professional camera controls and image capture. The latest update brings AI-powered photo critique, intelligent editing suggestions and several creative tools designed to help users improve both their photography skills and post-processing workflow.

Project Indigo, which launched last year as an experimental camera application, already offered advanced manual controls, multi-frame super-resolution and specialised capture modes. The newest release focuses on using large language models (LLMs) to analyse photographs, provide detailed feedback and recommend improvements instead of relying solely on traditional prompt-based AI editing.

AI offers detailed photography feedback.

The project is led by Marc Levoy, the imaging expert who previously helped develop Google’s Pixel camera technology. Levoy said many generative AI editing tools depend heavily on text prompts, making it difficult for users to achieve consistent results. Adobe has instead designed many of its new AI capabilities as one-click features that generate more predictable and reliable outputs.

One of the headline additions is an AI-powered photo critique system that evaluates framing, lighting, colour balance and the overall emotional impact of an image from what Adobe describes as a professional perspective. Rather than simply rating a photograph, the feature explains why an image works well or where improvements could be made, potentially helping users develop stronger photography techniques.

A second feature provides capture and editing suggestions. It recommends ways to improve a photograph before taking it again by adjusting framing, exposure or distracting elements within the scene. It also suggests how Adobe Lightroom editing controls could be used to improve an existing photograph, offering practical guidance instead of automatically applying edits.

Improved AI object removal and depth effects

Adobe has also enhanced its AI-powered object removal capabilities. While existing photo editing applications often require users to circle unwanted objects manually, Project Indigo instead presents selectable categories of items that can be removed automatically. These include background people, vehicles, fences, power lines, rubbish bins and other visual clutter. Users can also describe custom objects for removal using natural language.

According to Adobe’s demonstrations, the updated removal tool can eliminate background subjects while preserving realistic image quality without introducing obvious visual artefacts. The app also adds AI-generated depth-of-field effects that simulate the blurred background commonly produced by professional camera lenses.

Experimental creative tools remain in testing.

Another experimental feature introduces AI-powered style transfer, allowing photographs to be transformed into artistic looks such as watercolour, pen-and-ink, monochrome, ink line with colour wash and backlit subject effects. Although similar artistic filters have existed for years, Adobe says newer AI models produce more refined and natural-looking results.

Despite its preference for structured editing tools, Project Indigo also includes a prompt-based editing option that allows users to describe changes using natural language. Adobe acknowledges this offers greater flexibility for edits not covered by preset tools, although such systems can also generate inconsistent or unrealistic results.

The experimental AI Playground section currently usesGoogle’ss Gemini-based Nano Banana model to power many of these capabilities. However, Adobe says it could adopt other AI models in the future, including its own Firefly platform. The new features remain in testing and are only available to a limited group of users. While Adobe has not confirmed whether they will become permanent additions, the company believes the tools could encourage users to understand photography better rather than simply relying on AI-generated imagery.