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Andrew AdamsAndrew Adams · Co-Founder & Operations at Wireflow ·

AI Face Editor

Most face editors are a one-button guess you cannot steer.

Wireflow makes editing a face a small graph you own: a Nano Banana edit node reads the portrait and the change you write, and returns a retouched face that keeps the person's identity, bone structure, and framing. Free to build, pay per generation.

Free to build · no credit card · See how it works

AI Face EditorOpen workflow →
AI Face Editor
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01How it works

How to Use AI Face Editor

Steps to get you started in Wireflow.

Point the flow at a portrait
Step 1

Point the flow at a portrait

Open the flow. Keep the demo Text Input to generate a studio headshot, or follow the sticky note and swap the first node for an Import node to upload your own photo.

Write the face edit and run
Step 2

Write the face edit and run

Edit the Face Edit Instruction node with the change you want, for example a warm smile or softer studio light. Run the graph and the Nano Banana edit node returns the retouched portrait in seconds.

Steer, rerun, or chain the next hop
Step 3

Steer, rerun, or chain the next hop

Not happy with a look? Change the words and run again. Wire the edited portrait into an upscaler or a face swap node to enlarge or restage the same face in one pass.

02

Why one-button face editors hit a ceiling

Upload a portrait, pick a preset, download the result: most AI face editors work the same way, and the output is often decent. The ceiling arrives when the guess is wrong. The smile reads forced, the retouch smooths a face into plastic, the jawline shifts and the person stops looking like themselves, and there is no dial to turn. You re-upload and hope the model changes its mind. The edit is a black box you cannot open.

Wireflow answers with a different shape. Editing a face is a small workflow you own on a node canvas: a Nano Banana Lite node renders a studio headshot (or you upload your own), and a Nano Banana edit node reads that portrait plus a face edit instruction you write, then returns the retouched face while keeping identity, bone structure, and framing intact. Because the instruction is an editable node, you steer the change in words instead of re-rolling the dice, and the same canvas runs every other AI image editor job, from swapping a face to upscaling, in the same graph.

03

What the face editor graph gives you

01

Portrait intake

Keep the demo prompt for a studio headshot, or swap in an Import node and upload your own photo.

02

Editable edit step

The Nano Banana instruction is a Text Input; write the expression, lighting, hair, or wardrobe you want.

03

Identity kept intact

The instruction keeps identity, bone structure, and framing fixed, so only the named detail changes.

04

Swap and upscale nodes

Add a face swap or Topaz Upscale node to restage or enlarge the same portrait in the same run.

05

Rerun and swap models

Workflows are versioned and shareable by link; swap the image model as better ones ship.

06

REST and MCP

Every published flow is a REST endpoint and an MCP tool an agent can call over a batch of portraits.

04

How the face editor graph actually runs

The workflow behind this page's button is deliberately small: a Text Input, two image nodes, and one more Text Input for the edit.

  • Nano Banana Lite makes the source portrait. The demo generates a studio headshot so you can run the flow with nothing to upload. Swap this node for an Import node to edit your own photo.
  • Nano Banana edits the face. The edit node reads the portrait on one port and the edit instruction on another, then returns the retouched face with identity, bone structure, and framing preserved.
  • The instruction is yours to edit. Ask for a warm smile, softer light, a different hairstyle, or older or younger, and rerun until the look is right.

Because the edit lives in a node instead of a hidden model setting, the same portrait can roll straight into a longer chain, an AI face swap and an upscale, without leaving the browser. The whole graph is one of 70+ hosted model nodes you can rewire.

05

When a one-tap app or Photoshop is the better call

If you want to fix a single selfie on your phone in one tap and never think about it again, a dedicated consumer face editor app is the faster path, and this page will not pretend otherwise. If you need pixel-precise manual control, cloning a stray hair or painting a mask by hand, a layer editor like Photoshop still wins. Wireflow asks you to assemble a small graph on a canvas; that is the cost of getting a dial you can turn and a pipeline you can rerun.

Two honest limits worth stating plainly. Identity is preserved by the instruction, not a guaranteed biometric lock, so very large edits can drift and this is not a forensic identity tool. And it is built for consensual creative edits: use it on portraits you have the right to change, not to impersonate real people. What Wireflow adds is ownership of the pipeline, 70+ hosted models to swap between including a chained AI image restoration pass, and per generation pricing.

More Than Just AI Face Editor

Edit faces by describing the change

The edit step is a Text Input you own, not a hidden slider. Ask for a warm smile, softer light, or new hair and Nano Banana paints to your words.

Edit faces by describing the change

Chain the face edit, upscale, and swap

Face editing is one hop on a canvas. Wire the result into an AI image upscaler or a face swap node so one run edits, enlarges, and restages the same face.

Chain the face edit, upscale, and swap

Identity and framing stay locked

The instruction keeps identity, bone structure, and framing, so only the detail you named changes. Compare it beside an AI photo enhancer pass.

Identity and framing stay locked

Reruns are identical, upgrades are one node

Workflows are versioned and shareable by link, so your fiftieth headshot edits like your first. When a better model ships, swap that node and keep the graph.

Reruns are identical, upgrades are one node

Per generation pricing, not per seat

One tap apps charge per photo or per seat. Building this flow is free and generations are metered, so a shoot of portraits costs by output, not by headcount.

Per generation pricing, not per seat
Multi-Model

Face editor Workflows

Visual Builder

No Code Required

Production Ready

API & Batch Processing

FAQs

It depends on how much control you want. If you want a one tap phone app, a consumer face editor is simplest. If you want to steer the edit and chain it with swap and upscale, Wireflow makes editing a face a node graph: a portrait plus a face edit instruction you write, returned as a retouched result, priced per generation.

Andrew Adams

Written by

Andrew Adams · Co-Founder & Operations at Wireflow

Runs client operations and content strategy at Wireflow. Works directly with creative teams and agencies to build production AI workflows.

Content StrategyClient Operations

Edit faces on a canvas you control

Open the flow, write the change you want, and run it: a portrait becomes a retouched, identity-preserving result from one graph. Building is free; you pay per generation, not per seat.

Free to buildNo credit cardNo GPU or installCancel anytime