Andrew Adams · Co-Founder & Operations at Wireflow · AI Solutions for Marketing Agencies
Agencies wire one content and ad pipeline on a node canvas, then run it per client.
Brief in, on-brand images, video cutdowns, and channel variants out, with no GPU and nothing to install.
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How to Use AI Solutions for Marketing Agencies
Steps to get you started in Wireflow.

Wire the client pipeline once
Start from the brief: a text input, then Nano Banana Lite for the hero visual and Veo 3.1 for the cutdown clip. Build it one time on the canvas.

Fan out the channel variants
Add a Text Iterator over the client's hooks, formats, or channels and the graph renders a variant per row, so one brief fills a launch calendar.

Hand the pipeline to your agents
Publish the graph and it becomes an MCP tool with typed inputs. An agent fills the client brief, runs the pipeline, and returns asset URLs your team reviews.
The production layer, not another chatbot
Most AI pitched at agencies is a smarter assistant: a chat window that drafts copy or a dashboard that scores campaigns. The bottleneck in an agency is rarely ideas, it is production, turning a client brief into on-brand images, cutdowns, and channel variants, this week, for every account on the roster.
Wireflow is where that production lives. You wire the pipeline once on a node canvas: brief intake, an image model for the hero visual, a video model for cutdowns, an iterator for channel variants. It runs on hosted compute in the browser, no GPU and no install, and the same graph later becomes the tool your agents call. That is AI pipeline automation pointed straight at the weekly client grind.
What the client pipeline can do
Brief intake
Pull briefs from Notion pages or Google Drive with fetch nodes, or paste the client's text.
Hero visuals
Generate with Nano Banana Lite, Flux 2, Seedream V4.5, or GPT Image 2 from the client brief.
Video cutdowns
Veo 3.1, Kling O3, Sora 2, and Seedance 2.0 turn the hero frame into channel-ready clips.
Voice and avatars
ElevenLabs voice-over, HeyGen Avatar4, and Sync Lipsync v3 build spokesperson variants in-graph.
Variant fan-out
Text and Image Iterators loop one brief over hooks, channels, or a product CSV.
Finish and ship
Topaz upscaling, background removal, and a Social Publish node close out the run.
How an agency divides the work
Running AI well at an agency is a division of labor, not a hand-over of judgment.
- The team designs. You choose the models, lock the brand inputs, and decide what a variant is allowed to change. That happens once, on the canvas.
- The pipeline produces. Brief in, the graph renders the hero image, cutdowns, and channel variants on hosted compute, the same way for every client run.
- Agents operate. Over the hosted MCP server an agent lists your published workflows, fills the typed inputs from this client's brief, and returns asset URLs for review.
Delegation only works because runs are reproducible: workflows are versioned server-side, so the difference between two runs is the inputs, never the pipeline. That property is what separates AI creative workflows an agency can hand to an agent from prompt sessions it cannot.
What Wireflow is not for an agency
Wireflow is the production and publishing layer, not the strategy brain. Positioning, budget, audience, and channel choices come from your team or the agent you bring; an LLM node can rewrite prompts and caption variants inside the graph, but it will not plan a client's quarter.
It is not an ad platform or a reporting suite either: there is no audience targeting, no attribution dashboard, and no media buying. It does not run client sign-off or host per-account review libraries, so pair it with your agency workflow for approvals. And every generation costs credits, so an agent looping over hundreds of rows is a spend decision to cap deliberately. If a client is one-off work with no repeatable shape, a pipeline has little to automate; if the same campaign structure ships every week with new inputs, this is exactly the solution for it.
More Than Just AI Solutions for Marketing Agencies
One pipeline, every client
Build the client pipeline once on the canvas, then swap the brief and brand inputs to run the same creative workflow automation for the next account.

Brief to on-brand asset in one graph
Chain a brief, an image model like Nano Banana Lite, and a video model in one canvas, the pattern behind every AI brand content generator run.

Variants scale by loop, not headcount
A Text Iterator turns one client brief into a variant per channel or hook, the same fan-out that powers batch AI generation on the canvas.

Every pipeline your stack can call
Publish a workflow and it becomes a REST endpoint and an MCP tool, so an AI marketing agent can trigger client runs and get asset URLs back.

Reproducible keeps each client on brand
Workflows are versioned server-side, so the fiftieth asset follows the same pipeline as the first, the discipline behind reliable AI social media video.

AI Models Available
Automate Any Workflow
Included in Every Plan
FAQs
A production pipeline the team builds once and runs across clients, not another chat assistant. On Wireflow you wire brief to image to video to variants on a node canvas, then re-run the same graph per client by swapping the brief.
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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 pipeline your agency reruns for every client
Wire the client workflow once on the canvas: brief in, on-brand images, video cutdowns, and channel variants out. Run it by hand today; hand it to an agent when you are ready. Building is free, generations are pay per run.