Andrew Adams · Co-Founder & Operations at Wireflow · White Label AI SaaS
Most white label AI tools resell a chatbot.
Wireflow is the generation backend for a branded media product: build an image or video workflow once on a node canvas, and it ships as a REST endpoint and an MCP tool your own app calls under your brand. You own the front end and the billing; Wireflow runs the generation and charges you per run.
Free to build · no credit card · See how it works ↓
How to Use White Label AI SaaS
Steps to get you started in Wireflow.
Build the generation workflow
Open the flow and wire a Client Brief text node into a Nano Banana Lite node. Add more model nodes for extra assets, then run it once to confirm the output.
Publish it as your backend
Publishing turns the graph into a REST endpoint and an MCP tool in one step. Copy the endpoint and the workflow id; both are ready to call immediately.
Wrap it under your brand and bill
Point your own app or agent at the endpoint, pass a brief, and return the asset URLs to your client. Generations are metered, so you mark up each run.
Why founders look for a white label AI SaaS
Search white label AI SaaS and the results are almost all chatbots: a rebranded knowledge assistant you resell to clients. That market is crowded. Branded media generation, the images and video your clients make under your name, has almost no off the shelf backend, so most teams assume they have to build one.
Building it means renting GPUs, wiring a dozen model APIs, versioning prompts, and keeping the whole thing online. Wireflow is that backend already built. You assemble a generation workflow on a node canvas, publish it, and it becomes a hosted API your product calls. The same canvas powers everything from product shots to agency client work, so one backend covers every media job you resell.
What your branded product gets
REST endpoint
Every published workflow is a POST endpoint. Your app sends a brief and gets asset URLs back.
MCP tool
The same workflow lists as an MCP tool, so an agent can run it with typed inputs.
Model swap
Change the model node and every client call uses it. No client update ships.
Batch and loop
Run one workflow over a CSV or a feed to fill a client's whole content calendar.
Hosted compute
No GPU, no CUDA, no install. Generation runs on hosted infrastructure per call.
Versioned runs
Workflows are versioned server side, so client output stays reproducible.
How the endpoint actually runs
The workflow behind this page's button is the shape you resell: a Client Brief text node wired to two Nano Banana Lite nodes, one for a studio pack shot and one for a lifestyle scene. Your product posts a brief to the endpoint and gets two image URLs back.
- One input, many outputs. The brief feeds every image node, so a single client request returns a set of on brand assets instead of one file.
- Published once, called forever. Publishing turns the graph into a REST endpoint and an MCP tool at the same time, with nothing else to deploy.
- Swap to add value. Drop in Nano Banana Pro for on pack text, or a video node like Veo 3.1, and the endpoint your clients call gains the feature.
Because it runs on a hosted canvas, the same graph scales from one client to a batch run over a whole feed without leaving the browser.
When Wireflow is not your white label
If what you want to resell is a branded chatbot or a knowledge assistant, the text focused white label platforms fit better, because Wireflow generates media, not conversations. And it is the generation layer, not the whole SaaS: it does not ship a client facing dashboard, user logins, or per client billing. You bring the front end and the billing, or wire the endpoint into the app you already run.
What it does replace is the hardest and most expensive part to build: the hosted, multi model generation backend behind a branded media product. If your clients need images, video, or audio under your name, build the workflow here and wrap it with your own agency tooling. Every generation costs credits you mark up.
More Than Just White Label AI SaaS
Own the endpoint, not the whole stack
You never build the GPU layer or the model plumbing. Build one workflow and get a REST endpoint your product calls under its own brand.
One graph, a REST endpoint and an MCP tool
The same graph is both a REST endpoint and an MCP tool, so your app or a client's agent calls it with typed inputs and gets asset URLs.
Ship new models without shipping an update
Swap the model node once and every client call uses it, no redeploy. Move from Nano Banana Lite to a newer image model in seconds.
Per generation cost you mark up
Building on the canvas is free and every run is metered, so you set a spend cap, mark up each generation, and keep the margin.
Reproducible output clients can trust
Workflows are versioned server side, so a hosted API returns the same result on every client run and your output stays consistent.
Build Any AI Workflow
AI Models Integrated
Full Commercial License
FAQs
It is prebuilt AI infrastructure you configure and present under your own brand instead of building it yourself. Wireflow is the generation backend version: you build a media workflow, publish it as an API, and resell what it produces under your name.
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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.
Build the backend, not the whole stack
Open the flow, wire a brief into a generation node, and publish it as a REST endpoint and an MCP tool your product calls under your brand. Building is free; you pay per generation and mark it up.