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AI Video Production - From Concept to Commercial in Hours hero image
Artificial IntelligenceOverview

AI Video Production

From Concept to Commercial in Hours

TL;DR

01

Unified a fragmented multi-tool workflow into a single AI-powered platform, reducing video ad production time from ~4.5 hours to under 3 hours for small business clients

02

Built an automated brand research engine using Perplexity and Tavily APIs alongside Instagram and Yelp data feeds to surface key audience and brand insights without manual research

03

Integrated Eleven Labs voice synthesis, generative image APIs, and an optimized prompt generation system into one cohesive end-to-end production pipeline

The Challenge

Television advertising has historically been out of reach for small businesses. The cost of producing a professional commercial, traditionally ranging from $10,000 and up, puts broadcast advertising firmly in the territory of large brands with dedicated marketing budgets. Local businesses, from flower shops to auto mechanics to clothing boutiques, are left competing for attention without access to the same creative tools.

The local advertising market in the United States is valued at $162 billion, but only 4.2% of that spend goes to video. The barriers are not a lack of interest from small businesses; they are a lack of affordable production options and the complexity of placing media effectively. Generative AI is beginning to change what is possible, but the tools exist in isolation.

The client, an early-stage stealth startup, had already built a working process that used AI to generate video ads for local businesses at a fraction of traditional costs. The problem was the workflow itself. It relied on a combination of disparate tools: manual scripts, Google Drive folders, spreadsheets, and consumer AI products accessed through their UIs rather than APIs. Designers and prompt engineers stitched the process together by hand.

Producing a single video ad took approximately 4.5 hours of combined effort. The process worked but it did not scale. Every new client added proportional manual work. Quality control was inconsistent. There was no central system of record, no standardized outputs, and no path to a self-service model that could operate without constant internal involvement.

The client needed to unify their workflow into a platform that could grow with their business, reduce production time, maintain creative quality, and eventually support a self-service model where local businesses could initiate the process themselves.

Key Results

01

~230 minutes removed from the end-to-end ad production workflow

02

Production time reduced from ~4.5 hours to under 3 hours per video ad

03

5 previously manual workflow stages unified into a single platform

04

Automated brand research via Perplexity, Tavily, Instagram, and Yelp APIs

05

Foundation established for self-service model targeting $162B local ad market

The Solution

01

Auditing the Existing Workflow

Before building anything, AE Studio mapped the client's existing video ad creation process end to end. This meant interviewing designers and prompt engineers, identifying every tool in the stack, and tracing where handoffs happened and where time was lost.

The audit revealed that the bottlenecks were not in any single tool but in the gaps between them. Research outputs had to be manually formatted before they could feed into the storytelling step. Scripts had to be copy-pasted into voice synthesis tools. Image prompts required expert knowledge to construct from scratch for each new client.

With a clear picture of where manual effort was concentrated, the team could prioritize which integrations would unlock the most time savings and quality improvements.

02

Automated Brand Research and Data Gathering

The first step in creating a video ad for a local business is understanding that business: its brand, its customers, its competitive landscape, and what makes it worth advertising. This research had been done manually, requiring staff to visit websites, read reviews, and synthesize findings into a usable format.

AE Studio replaced this with an automated brand research engine. Using Perplexity and Tavily for AI-powered web research alongside direct API integrations with Instagram and Yelp, the system gathers structured data about any SMB client automatically. The output is standardized for downstream processing and stored in a centralized database, so every subsequent step in the workflow has consistent, reliable inputs.

What previously required manual research time is now initiated by entering a business name and URL.

03

AI-Powered Storytelling and Script Generation

With structured brand data in hand, the platform generates advertising narratives automatically. The storytelling module uses improved prompt engineering practices, including prompt templating, versioning, and easy modification, to produce scripts that are tonally appropriate, aligned with the brand, and compatible with voice synthesis requirements.

Rather than replacing human creative judgment, the system generates multiple narrative directions that the internal team can review, select from, and edit. The output is structured for direct handoff to the voiceover step without reformatting or manual intervention.

04

Streamlined Voiceover Creation with Eleven Labs

Voice synthesis had previously required manual interaction with third-party tools outside the core workflow. AE Studio integrated the Eleven Labs API directly into the platform, allowing approved scripts to move automatically into voiceover production.

The integration supports multiple voice options and includes automated quality control to ensure outputs are consistent with video length and pacing requirements. If a generated voiceover does not meet length or timing standards, the system flags it for review before it proceeds to the next stage rather than passing a flawed asset downstream.

05

Optimized Prompt Generation for Visual Assets

Generating effective image and video prompts requires domain expertise that not every team member has. The client's designers were producing high-quality results, but the process was manual and not reproducible at scale.

AE Studio built a prompt generation system that automatically selects camera angles, shot types, visual styles, and pacing parameters based on the brand profile and narrative generated in earlier steps. The system was designed in collaboration with the client's design team through SME interviews, encoding their visual expertise into repeatable logic.

The output prompts are structured for compatibility with image and video generation APIs, with pathways built for migration from Midjourney to automated alternatives including Ideogram, ImageGen, and SDXL, as well as direct-to-video generation pipelines that can bypass intermediate image steps entirely.

06

Unified Platform with End-to-End Workflow Automation

The five components, brand research, storytelling, voiceover, prompt generation, and customer onboarding, are connected through a centralized database and managed through a single interface. Because all intermediate outputs are standardized and stored in one place, the modules pass data to each other without manual intervention.

Role-based access controls separate what clients see from what internal team members can access. Clients interact with onboarding inputs and final outputs. The internal team can review, modify, and re-run intermediate steps at any quality control checkpoint. This structure makes the system auditable and controllable without sacrificing the automation that makes it fast.

The platform replaces the previous combination of Google Drive folders, spreadsheets, manual scripts, and disconnected third-party tools with a single enterprise-grade system designed for scale.

Results

Key Metrics

~230 minutes removed from the end-to-end ad production workflow

Production time reduced from ~4.5 hours to under 3 hours per video ad

5 previously manual workflow stages unified into a single platform

Automated brand research via Perplexity, Tavily, Instagram, and Yelp APIs

Foundation established for self-service model targeting $162B local ad market

The Full Story

AE Studio unified the client's fragmented video ad production workflow into a single AI-powered platform, reducing production time from approximately 4.5 hours to under 3 hours per ad, a reduction of roughly 230 minutes across the end-to-end process.

The platform now handles automated brand research, AI-driven storytelling, voice synthesis, prompt generation, and customer onboarding through one cohesive system. What previously required manual coordination across disparate tools, Google Drive folders, spreadsheets, and consumer AI products, is now managed through a centralized interface with standardized outputs at every stage.

By automating the research and content preparation pipeline, the client can take on more small business clients without proportionally increasing internal workload. The foundation built in this engagement directly enables the long-term goal of transitioning from a managed service model to a self-service platform where local businesses initiate and review ad creation independently.

The client is now positioned to pursue a market where local advertising is a $162 billion industry and only 4.2% currently goes to video, with AI-powered production making professional TV commercials accessible at a fraction of traditional costs.

Conclusion

Professional video advertising has been inaccessible to small businesses for decades, not because local businesses lack the need for it, but because production costs and workflow complexity made it impractical. Generative AI changes the economics, but only if the tools work together as a system rather than as a collection of disconnected experiments.

By consolidating the client's workflow into a unified, automated platform, AE Studio reduced production time by approximately 230 minutes per ad and created the operational foundation for a self-service model that can scale without proportional increases in cost or manual effort. The $162 billion local advertising market, where video currently captures just 4.2% of spend, represents a significant opportunity for a platform that makes broadcast-quality ads accessible to any small business in hours.

Key Insights

1

Workflow unification unlocks scale. Connecting five separate tools into one platform with standardized outputs eliminated the manual handoffs that made each new client a proportional increase in internal work.

2

Auditing before building is essential. Mapping the existing workflow revealed that bottlenecks were in the gaps between tools, not within any single tool, which focused development effort where it would have the most impact.

3

Encoding expert judgment into automated systems preserves quality. Collaborating with designers to translate their visual expertise into the prompt generation logic allowed the system to produce results that matched human-crafted prompts without requiring expert involvement every time.

4

API integrations replace fragile manual processes. Moving from consumer UI interactions with ChatGPT and Midjourney to enterprise API connections made the workflow reliable, repeatable, and independent of manual tool-switching.

5

Building for the self-service future while delivering managed service value now. The platform architecture was designed from the start to support both models, allowing the client to generate immediate value while building toward a more scalable business.

Frequently Asked Questions

The platform automates the most time-intensive parts of video ad creation: researching the business, generating a compelling narrative, creating a voiceover, and building the visual prompts needed to produce ad-ready imagery. What traditionally required a production team, significant budget, and days of work can now be completed in hours through an end-to-end automated workflow. By reducing production costs from the $10,000+ range to hundreds of dollars, the platform makes broadcast-quality advertising viable for local businesses like flower shops, auto mechanics, and clothing boutiques that have historically been priced out of the television advertising market.
The platform integrates several AI tools and APIs across different stages of the production process. Brand research is powered by Perplexity and Tavily for AI-driven web research, along with direct API connections to Instagram and Yelp for structured business data. Voiceover creation uses the Eleven Labs API for voice synthesis with multiple voice options. Visual prompt generation is designed for compatibility with image and video generation APIs including Ideogram, ImageGen, SDXL, and direct video generation pipelines. All of these components are connected through a centralized database and managed through a single interface, replacing the previous combination of consumer AI tools accessed manually through their UIs.
The platform was built in close collaboration with the client's existing creative team. Prompt engineering best practices, including templating, versioning, and easy modification, were incorporated into the storytelling module. The visual prompt generation system was designed through direct interviews with the client's designers, encoding their expertise into automated logic so the system produces results that match what an expert prompt engineer would create. Quality control checkpoints are built into the workflow at each stage. The voiceover module, for example, automatically checks timing consistency before passing audio downstream. Items that fall outside acceptable parameters are flagged for human review rather than proceeding automatically.
The platform separates client and internal team access through role-based controls. Clients interact with the onboarding inputs, where they provide information about their business, and with final outputs, where they review and approve the finished ad. They do not have visibility into intermediate production steps. The internal team can access all intermediate outputs and has the ability to review, modify, and re-run any stage in the workflow at defined quality control checkpoints. This structure gives the client's team full control over production quality while keeping the interface simple and clean for the small business clients they serve.
The initial engagement focused on unifying the existing workflow and establishing a solid automated foundation. Future phases include more advanced video generation capabilities, automated image processing and sorting, prescriptive image generation systems, After Effects template optimization, and music selection automation. The longer-term strategic goal is to transition from a managed service model, where the client's internal team guides each production, to a fully self-service platform where local businesses can initiate, review, and approve their own video ads without internal involvement. The centralized architecture built in this engagement was designed with that future state in mind.
OverviewArtificial Intelligenceintermediate8 min readAI Video ProductionGenerative AISMB AdvertisingWorkflow AutomationPrompt EngineeringVoice SynthesisLocal AdvertisingBroadcast AdvertisingCreative Automation

Published: Dec 2025 ยท Last updated: Feb 2026

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AI Video Ad Production: From Concept to Commercial in Hours