Creative & Generative AI Production
AI-assisted creative production for video, voice, visuals, and 3D, generative tools inside a real pipeline with human craft on both ends. A recent engagement: six product training videos plus social assets in about three weeks, at roughly a quarter to a third of traditional production cost.
Companies we've collaborated with
AI Video and Voice Production
Scripts, scenes, synthetic voiceover, and edit, delivered as finished video for product training, explainers, promos, and social. Voice models handle consistent narration across a whole library of content in multiple styles and languages, which is where traditional production costs compound fastest.
This is the flagship of the practice, with its own service page: AI video production, including the real cost breakdown from a six-video client engagement.
Visual Assets, Styleframes, and 3D
Brand-aligned images, concept art, storyboards, and campaign visuals generated against a developed style system, plus handcrafted 3D modeling and rendering where fidelity can’t be faked, like our collectibles work for McFarlane Toys.
The practical value is iteration speed: exploring ten directions now costs what one used to, so creative decisions get made on evidence instead of scarcity.
Production Pipelines That Scale
When the need is dozens of assets instead of one (localized variants, data-driven video, multi-market campaigns) we build automated workflows around the generation step: templating, batch rendering, review gates, and QA.
We’re a development shop as much as a creative one, so the automation is engineered custom for your content operation rather than assembled from rented tools. That’s the difference between using AI tools and owning an AI pipeline.
Who this is for
The team behind it is the same Portland AI practice that builds our agents and LLM systems. The pipeline automation is ours, not a rented tool stack. If you have a script, a product, or just a volume problem, we will tell you honestly whether AI production fits and where traditional production would serve you better.
Marketing teams
Training or product video at a volume traditional production cannot reach.
Product companies
Visual assets, explainers, and campaign variations without a new shoot per iteration.
Agencies
Quietly subcontracting the AI parts they have not built in-house yet.
Why Choose SLIDEFACTORY for Generative AI Production
Because we’ll show you real numbers instead of a sizzle reel. The BatchGeo engagement above is on this site with its costs and hours attached; the McFarlane 3D work is in our portfolio; and the pipeline automation is built by the same engineers who ship our AI products. We stay current with the video, image, and voice models so you don’t have to, and we’re honest about what they still can’t do.
Based in Portland, Oregon, we work with startups, marketing teams, and established brands nationally. If your content calendar has outgrown your production budget, that gap is exactly what this practice exists for.
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Frequently Asked Questions
How much does AI video production cost?
Here’s a real engagement rather than a hypothetical: for BatchGeo, we produced six AI-assisted product training videos plus promotional and social cutdowns in about two to three weeks from concept to delivery, roughly $9,000–11,000 all-in. A traditional shoot for the same deliverables (talent, crew, filming days, reshoots) typically runs $30,000–60,000 or more. That’s roughly a quarter to a third of the cost, at a pace a traditional production calendar can’t match.
The full breakdown of that engagement, including where the hours actually went, is on our AI video production page, and the work itself is in the AI video production case study.
Will the output look AI-generated?
Not if the pipeline is built right. About a person-and-a-half day of skilled work goes into each finished video, style development, motion graphics, and editorial polish around the generated material. AI compresses production; it doesn’t remove the craft. Where generative fidelity isn’t good enough (like product-accurate 3D for collectibles) we build the assets by hand.
How fast can you deliver?
The six-video BatchGeo engagement went concept to delivery in about two to three weeks. Single videos and asset packages move faster; large localized campaigns take longer because review and QA scale with volume. AI removes most of the calendar cost of shoots (scheduling, crews, reshoots) which is where traditional timelines actually go.
Can you build an ongoing content pipeline rather than a one-off project?
Yes. That’s where the economics get interesting. We build automated production workflows (templating, batch generation, review gates) around your recurring content needs, engineered by the same team that ships our AI products. One-off projects prove the quality; the pipeline is what changes your cost per asset permanently.
What does an AI creative agency actually produce?
Finished creative (video, voiceover, visual assets, and 3D) made faster and cheaper by putting AI generation inside a real production pipeline, with human craft on both ends. AI compresses production; it doesn’t remove the concept work, the motion design, or the editorial judgment that makes something usable.
Our pipeline runs in five stages: concept and script, prompt and style development (building a visual language the models can hold consistently), generation across video, image, and voice models, then animation and motion graphics, then edit and polish. Roughly a person-and-a-half day of skilled work goes into each finished video, generation and voiceover, motion design, and final edit. The AI does the expensive middle; people do the parts audiences actually judge.
Where does 3D and product visualization fit?
Generative tools are only half of the visual practice. For McFarlane Toys, we’ve built digital 3D work around physical collectibles, modeling, rendering, and interactive presentation for products where accuracy matters, because collectors notice everything. That mix, generative speed where it’s safe, handcrafted 3D where fidelity is non-negotiable, is the honest state of AI creative production in 2026, and pretending the models can do all of it is how projects end up in the uncanny valley.
