What exactly is “Nano Banana”?

“Nano Banana” is the friendly name for Gemini 2.5 Flash Image, Google’s state‑of‑the‑art model for:

• High‑quality text‑to‑image (concepts, scenes, products, mockups).

• Targeted transformations of existing photos using natural language (no manual masks required for most tasks).

• Multi‑image blending (combine 2–3 inputs to borrow styles, layouts, or objects).

• Character & style consistency across a sequence of images.

• Sharper, more reliable text rendering (posters, UI, labels, signage), a long‑standing pain point in other models.

• Enterprise access via Gemini API and Vertex AI, including safety features and watermarking.

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See It in Action

Whether you're building a multilingual website, crafting product pages, or creating visual stories — the AI Assistant helps you get there faster, with better quality and less effort.

How Nano Banana works (in practice)

You describe the change; the model figures out where and how much to edit.

1. Understand: It analyzes the input(s)—your prompt + one or more images—building a scene graph: subjects, materials, lighting, perspective, and any written text.

2. Locate: From that understanding, it infers the regions that should change (e.g., “replace the sky with sunset clouds,” “put our logo on the mug,” “turn this into a toy‑box figurine”). You don’t usually paint masks.

3. Transform: It synthesizes just the needed pixels and harmonizes them with the untouched areas: matching lighting, shadows, and grain so the edit feels native.

4. Constrain & finalize: Safety filters run, and an invisible watermark is embedded. You get a ready‑to‑ship PNG.

In short: describe → locate → replace → blend. Compared to “regenerate the whole frame,” this approach preserves details you like and saves time.

What makes it best‑in‑class today

• Speed + price/performance: “Flash” tier models deliver quick turnarounds suitable for editorial workflows.

• Reliable localized edits: Natural‑language, region‑aware changes without fussy masks.

• Multi‑image fusion: Borrow a product silhouette from shot A, a surface texture from B, and a background from C.

• Consistent characters/props: Keep the same model, outfit, or mascot across a campaign.

• Text that actually looks like text: Posters, UI comps, and mock labels land with fewer garbled glyphs.

• Built‑in responsibility: Invisible SynthID watermarking + app‑level visible markers; enterprise guardrails via Vertex AI.

• Ecosystem reach: Works in Gemini apps, Google AI Studio, and enterprise stacks (and already popping up in creative tools).

Hands‑on: Nano Banana inside Optimizely CMS

I wire this through Epicweb AI‑Assistant for Optimizely so editors don’t leave the CMS.

Typical editor flow

1. Open any media from the Assets pane → choose AI Image Editor.
   
   
   

2. Pick a task: Generate new, Transform existing, Blend images, Clean background, Replace text.

3. Describe the change in plain language: e.g., “Swap the backdrop to a foggy Paris dawn. Keep the product color unchanged.”

4. Review variations → Save as new asset with auto‑alt text + version notes.

5. Insert into blocks/pages. The assistant can also generate captions, summaries and schema markup.

Installation Guide

To enable the AI Assistant in your solution, follow these quick steps. Installation should be done by a developer with access to the source code.

1. Install via NuGet

Add the package using Optimizely's NuGet feed:

🔗 Epicweb.Optimizely.AIAssistant NuGet Package

dotnet add package Epicweb.Optimizely.AIAssistant