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Tag: ai video production

  • Full Video Production Cycle: Lumen5 Integrates with Claude, ChatGPT, Zapier, and Make

    Full Video Production Cycle: Lumen5 Integrates with Claude, ChatGPT, Zapier, and Make

    In modern marketing, efficiency is key to success. How many browser tabs do you have open right now? Probably quite a few. Transferring texts from one tool to another, searching for a brand book, coordinating with the team – all this takes up precious time and nerves. Imagine being able to shorten this path, getting a ready-made, brand-compliant video without leaving your familiar AI assistant or by fully automating the process. With Lumen5, this has become a reality thanks to new integrations with Claude, ChatGPT, Zapier, and Make, offering full-cycle video production.

    Now you can order everything in one place: from video editing to posting, replacing an entire SMM team. This is not only budget savings but also a significant relief for your nerves. All created videos automatically appear in your Lumen5 workspace, where you can always make final edits before publishing. Artificial intelligence does the rough work, and you maintain control.

    Comprehensive Short Video Production: Forget the Routine

    Lumen5 + Claude: from Draft to Finished Video

    Claude excels at a task that usually consumes hours: transforming lengthy reports, articles, or scattered notes into coherent, engaging text. Previously, after creating the perfect script, you had to transfer it to a video editor and start over. Now, thanks to the Lumen5 connector, this step is skipped.

    • Script Preservation: Lumen5 uses your script word-for-word for voiceover, ensuring full compliance with the approved text.
    • Context: Claude can summarize voluminous documents (reports, articles, notes) into a short script and create a video within a single dialogue.
    • Flexibility: The ability to work in Claude Code allows developers to create videos (e.g., for product updates) without leaving the terminal.
    • Customization: You can specify a particular template, AI voice, brand book, or leave the choice to Lumen5.

    “If Claude is your tool for perfecting a long draft, then the integration with ChatGPT is the express lane.”

    Lumen5 + ChatGPT: Video on Demand

    Add the Lumen5 app to ChatGPT, describe your needs, and Lumen5 will write the script and create the video. One sentence is enough to start, without the need to pre-write a script or open a new tab.

    • Quick Start: A single-line prompt is enough to create a promo, a social media clip, or a review.
    • Using Existing Scripts: If you already have a script, simply paste it, and Lumen5 will use it for voiceover.
    • Voice Selection: Listen to various AI voice options by accent, gender, and tone to find the perfect one for your video.
    • Status Tracking: Ask ChatGPT about the video status or a list of recently requested videos, getting links when they are ready.
    • Branding: Integration supports brand books, ensuring that even the quickest requests comply with your corporate identity.

    Lumen5 + Zapier: no-code automation

    The Lumen5 app for Zapier allows you to automatically create videos when new content (posts, products, updates) appears, without the need for coding. This is an ideal solution for those looking for social media content outsourcing.

    • Triggers: Start video creation from your CMS, online store, CRM, forms, or spreadsheets.
    • Unified Style: Set up your workspace and style once, and all created videos will match your brand.
    • Easy Setup: Log in to Lumen5 via Zapier, grant access, and Zapier will take care of the rest.
    • Flexibility: Lumen5 can write a script for you if you provide post text or a brief description.

    AI vs. Real Clipping Comparison: In this case, AI offers automation that can be significantly cheaper than manual clipping, especially for mass content production.

    Lumen5 + Make: for advanced automations

    The upcoming Lumen5 app for Make is designed for routing, filtering, and batch processing content into ready-made videos within existing scenarios. These are the quality criteria for mass posting, taken to the absolute.

    • Batch Processing: Create videos for each table row or feed item, with individual scripts, templates, or voices.
    • Content Type Branching: Send each item to a separate template, voice, or brand book. For example, a product launch will get a promo, and a “how-to” article will get a tutorial video.
    • Reliability: Using idempotency keys prevents the creation of duplicate videos when the scenario is run again.
    • Availability: Currently, you can use Lumen5 in Make via the HTTP module and the Lumen5 Video Creation API using an API key.

    Is it worth unique content or new? With Make, you can automate the creation of unique videos for each product or article, which is significantly more effective than creating one general video.

    Whichever integration you choose, the principle remains the same: your videos go into the Lumen5 workspace, use your brand books and templates, and open in the Lumen5 editor for final refinement.

    Full video production cycle: Lumen5 integrates with Claude, ChatGPT, Zapier and Make — illustration 2

    Frequently Asked Questions

    Can I create Lumen5 videos from Claude or ChatGPT?

    Yes. Using the Lumen5 connector in Claude (including Claude Code) or the Lumen5 app in ChatGPT, you can request a video in a conversation and get a link to the finished video in minutes.

    Do I need to write a script first?

    No. Provide a brief description, and Lumen5 will write the script. If you already have a script, Lumen5 will use it word for word for the voiceover.

    Will my videos be on brand?

    Yes. You can request a specific brand book, template, AI voice, or blueprint from your workspace. In Zapier, you set up your workspace and style once when creating a Zap.

    Can I edit videos created through integration?

    Yes. Each video opens in the Lumen5 editor, allowing you to review and adjust it before publishing.

    Who can create videos through integration with Claude?

    Anyone who has permission to create videos in your Lumen5 workspace. Users with view or review permissions can view content but not create videos, just like in the Lumen5 app.

    Can I automate video creation without code?

    Yes. The Lumen5 app for Zapier allows you to trigger video creation from your CMS, store, CRM, forms, or spreadsheets without writing code or managing API keys.

    Conclusion: How to choose a video content contractor

    These integrations were created because we constantly heard the same thing: the difficulty is not in the ideas, but in their implementation, in transferring content from one tool to another. Lumen5 has come to where your ideas already live. If you are looking for a full cycle of short video production that will save you time and resources, and replace a team with a service, these solutions are for you.

    Quality criteria when choosing a contractor include not only the final product, but also the efficiency of the process. Lumen5 offers exactly that: reduction of routine, automation, and preservation of creative control. Learn more or book a demo to see how teams turn articles, scripts, and ideas into polished, branded videos.

    • For those working with long documents: start with Claude.
    • For quick ideas: start with ChatGPT.
    • For automation when new content appears: start with Zapier.
    • For high-volume or multi-step processes: keep an eye on Make (or start today with the API).
  • Vibecoding: Real Project Incomes and Myths About Millions

    Vibecoding: Real Project Incomes and Myths About Millions

    Talks of millions from vibecoding are everywhere: a million in 17 days, a million by October, a million from one prompt. I decided to investigate: how many projects have truly crossed the threshold of $100,000 in monthly revenue or $1,000,000 in total income (including exit value). The picture turned out to be much more modest than expected. If we exclude projects whose product itself is an AI solution, very few startups based specifically on vibecoding remain.

    In this analysis, I do not conflate ARR (Annual Recurring Revenue) and actual revenue. ARR is a projection of the current month multiplied by twelve, not money earned. Where a source indicates ARR, I note it and recalculate the monthly revenue separately. The order of projects in the table below is determined not by revenue size, but by the reliability of financial data confirmation.

    Projects that have crossed the $100,000/month or $1 million total income threshold

    The list includes projects with public reports of revenue from $100,000 per month or cumulative income from $1,000,000.

    1. Medvi: $401 million in the first year

      Telemedicine specializing in GLP-1 weight loss drugs. Founder Matthew Gallagher launched the project in September 2024 with an investment of about $20,000. According to publications, the first year brought $401 million in revenue, about 250,000 clients, and $65 million in profit with a 16% margin. Staff: two people (Gallagher himself and his brother Elliot), the rest are contractors.

      • Vibecoding: Code, website, and agents were written using Claude, Grok, and ChatGPT. Visuals for advertising — Midjourney and Runway. Client calls — ElevenLabs.
      • Business essence: The main part of the business — doctors, pharmacy, prescription writing, and legal framework — is outsourced through CareValidate, OpenLoop Health, and LegalZoom. Gallagher focused on assembly and traffic.

    2. Base44: sold for $80 million

      An application builder from text description, created by Maor Shlomo. Launched in early 2025. In May, the company showed $189,000 in monthly profit. In June, Wix announced its acquisition for $80 million in cash. At the time of the deal, the project had 250,000 users. Shlomo was the sole owner, but at the time of sale, eight people worked for the company, who received $25 million from the deal amount as retention.

      • Vibecoding: Shlomo deliberately built the codebase so that most of it was generated by models, and used prompt routing between different models. This is one of the purest examples where the product itself is vibecoding and built using the same method.
      • Confirmation: Financial performance is confirmed by the deal document, not a tweet.

    3. Peec AI: $4M ARR (up to $833,000/month)

      A Berlin-based company that tracks how a brand is represented in AI search (ChatGPT, Perplexity, Gemini). Founder Marius Meiners. The first prototype was built on v0 from Vercel in about a day and a half. The product was then developed in a traditional way by a team. In November 2025, the company announced a Series A of $21 million, with a total of $29 million raised. At that time, Peec AI had 1300+ connected companies and ARR of about $4 million (approximately $333,000 per month). Later, ARR grew to $10 million (about $833,000 per month).

      • Vibecoding: Used to quickly create a prototype and test demand, but the main product was built traditionally.

    4. Wave AI: $7M ARR

      An application for recording, transcribing, and retelling audio, focused on casual conversations, not meetings. Author Josh Moorer, former Uber GM for New York, not a programmer. He built the first working prototype in Swift in a day using ChatGPT. The project reached $7 million ARR with $3 million in annual profit and about 4000 paid subscribers.

      • Vibecoding: Prototype created with AI.
      • Feature: High costs for accessing the best models to ensure transcription quality, which is the key product.

    Projects that did not reach the threshold, but are often mentioned

    These projects often appear in selections, but their financial performance does not meet the specified threshold.

    1. Cal AI: $2M monthly revenue, but the label is questionable

      An application for counting calories from a photo of food. Authors Zach Yadegari and Henry Langmack. Launched in May 2024. By July 2025 – 8.3 million downloads and, according to CNBC Make It, about $1.4 million in gross monthly profit, and $2 million in monthly revenue is also mentioned. It passes in terms of money, but not in terms of the vibecoding label. TechCrunch revealed that Yadegari wrote the code himself, starting programming at the age of ten. Anthropic and OpenAI models are only used for image recognition within the product.

    2. fly.pieter.com: $1M ARR, but peak $87,000/month

      A browser-based flight simulator by Pieter Levels. Basic prototype in 30 minutes. $1M ARR was announced in February 2025, 17 days after release. Peak monthly revenue was around $87,000. Monetization: paid aircraft models and items for $29.99. Levels’ method: “one prompt – one layer.” $1M ARR is an annual projection, not a million earned. The project did not reach the $100,000 monthly revenue threshold.

    3. Stanley: $1M ARR, but not revenue

      An AI content tool created by Vitaly Dodonov and Jon Hu in 14 days. The LinkedIn version was released in June 2025 and showed $200,000 ARR after six weeks. The team passed the $1M ARR mark by October 2025. “14-day app” refers to the first working cut, not the full product. The main value was added after launch. Again, this is ARR, not actual revenue.

    4. Lumoo: €700,000 ARR, about €58,000/month

      A platform for fashion and retail brands by Henrik Skagerlind Fast and Peter Törngren. Offers photorealistic visualizations and virtual try-on. According to the Lovable case, in nine months the product reached €700,000 ARR, connecting more than fifteen brands. The goal is €1M ARR by November 2025. Monthly revenue is about €58,000, which is below the threshold. The project’s success is due to the founders’ industry connections, not a generated interface.

    5. Plinq: $456,000 ARR, about $38,000/month

      A background and safety check app by Sabine Matos. Built entirely on Lovable. 6,000 ARR was reported, R3 million raised, and over 10,000 users. 6,000 ARR is about $500 a month, and that’s in the best interpretation. The case is interesting because the app gathered an audience before it made money. Investments came after users appeared, not because the first version was generated by a tool.

      Вайбкодинг: реальные доходы проектов и мифы о миллионах — illustration 2

    General Conclusions and Key Success Factors

    Analysis shows that project success is not limited to cheap, AI-generated code. There are several common traits among successful startups.

    Team Size at Launch

    Four out of five successful cases started with one or two people. This is not so much a credit to vibecoding as it is an indicator that a product can be built faster than a team can be formed.

    Infrastructure on Others’ Shoulders

    Successful projects actively used third-party services and APIs:

    • Medvi outsourced doctors, pharmacies, and lawyers.
    • Wave AI used third-party APIs for transcription.
    • Cal AI — for recognition and product database.
    • Lumoo integrated into existing brand workflows.

    Only what was not on the market had to be built from scratch.

    Money doesn’t come from cheap code

    No product won solely due to cheap or generated code. Money came from other factors:

    • Cal AI — through influencers.
    • Stanley — through distribution via LinkedIn.
    • Medvi — through contractors with licenses.
    • Wave AI — through expensive inference (model computations).
    • Plinq — through an audience that appeared before revenue.

    Code generation shortens the path to launch but is not the main source of income.

    Multimodel Verification Method

    Almost all teams in the selection use the trick: run one task through several models and compare the results. This is how Peec AI checked demand, Base44 routed prompts, and Levels assembled game layers, changing the model for each task. This allows for quick hypothesis testing and finding optimal solutions. You can test this approach in an evening: take your current prompt and run it through three different models to see the discrepancies and choose the best option.

    Frequently Asked Questions

    What CPM should be considered profitable for hypothesis testing?

    For hypothesis testing, not only CPM is important, but also the speed of data acquisition. If AI tools allow for quick creative generation and campaign launches, then even with a relatively high CPM, hypothesis testing is cheap due to reduced time and labor costs. A profitable CPM is one that provides sufficient data volume for decision-making with minimal launch costs. For example, if the price per one finished clip, generated by AI, allows launching 100 variants for the same budget as 10 variants from a human, it is profitable.

    What’s cheaper: banner advertising or bloggers?

    A direct price comparison is difficult, as the result is different. Banner advertising (how much does 1 million impressions via banner cost) can be cheaper in terms of CPM, for example, CPM cheaper than 50 rubles per 1000 impressions. But bloggers provide native integration and audience trust. For a budget alternative to blogger seeding, you can consider a mass-posting package price which will be lower, but the reach may be less targeted. Cheaper than influencers can only be your own traffic or very targeted advertising.

    Is it worth investing in AI for content creation?

    If the goal is to reduce content production costs and increase speed, then is AI worth it — definitely yes. For example, the cost of generating 100 AI videos will be many times lower than creating them manually. The cost of uniqueizing one video with AI also significantly reduces costs. However, it is important to remember that price vs result is a key factor. AI speeds up the process, but a quality result still requires human control and refinement.

    How to estimate the cost of AI video production?

    The price per minute of AI video with an avatar can vary. It is important to consider not only generation, but also how much it costs to cut 1 hour of stream into short clips using AI. This allows for a lot of content from one source. The cost of publishing 500 videos, if they are generated or cut by AI, will be significantly lower than manual work. What is cheaper: banner or target — this is a question of effectiveness, not just price, and AI can increase the effectiveness of any channel through personalization and scale.

    Conclusion

    Analysis shows that “millions on vibecoding” is more of a myth than a reality, if we consider the net income from generated code. The success of projects lies in the ability to quickly assemble an MVP, use third-party infrastructure, and scale the business through effective distribution and customer work, and not just through cheap code. The unit economics of these projects are based on a comprehensive approach. Before believing in another success story, always demand statistics screenshots and ask the main question: how much money will each ruble spent bring. For those who are ready to experiment, we recommend trying different models on the same task. Use promo code CTRLAI for a 20% discount on any plan at SYNTX.AI.

  • How much does AI advertising cost: a 25-second video for ₽2,126

    How much does AI advertising cost: a 25-second video for ₽2,126

    Generative AI promises a revolution, but the real cost of content production often remains hidden. We calculated how much it costs to create a 25-second commercial using neural networks, including script, images, video, voiceover, and music. Spoiler: the 25-second video cost 2,126 ₽, or 85 ₽ per second. The lion’s share of the budget, almost 90%, was “eaten up” by video generation.

    How much does AI advertising cost: a 25-second video for 2,126 ₽

    In a world where technology is developing at an incredible pace, artificial intelligence is becoming an integral part of many industries, including content creation. But what is the real price of this innovation? We conducted an experiment to find out how much it costs to create a 25-second commercial entirely with neural networks. The results may surprise you, because the cost of unique content for one video and profitable CPM for advertising materials are becoming key factors.

    The experiment was conducted through BotHub using the following models:

    • GPT-6 Astra for script and prompt refinement.
    • Nano Banana 2 for generating source images.
    • Kling v3 for converting images to video.
    • ElevenLabs Flash v3 for voiceover.
    • Suno v5.5 for musical accompaniment.

    We advertised a herbarium, without commercial implications. Important: only the marginal cost was taken into account — the cost of successful generations included in the final video. Actual costs may vary depending on prompting skills and perfectionism level, increasing the number of regenerations and, accordingly, the budget.

    Methodology for calculating the cost of AI production

    For an objective assessment, it is important to distinguish between two types of costs:

    1. Cost of result generation: direct computational costs for content creation.
    2. Cost of infrastructure access: costs for subscriptions or minimum credit packages for using services.

    In the case of a single video, the second amount can significantly exceed the first. Of course, open-source models can be deployed locally, but this requires a powerful PC, which is not always available.

    «Don’t replace professionals with browser tabs. AI content has nuances: rights, licenses, character stability, result control, and brand requirements. AI slop is easy to get, and you’ll get flamed for it».

    Step 1: AI-powered ad script

    We started by creating a concept. GPT-6 Astra acted as a creative producer and scriptwriter. The prompt was formulated so that the model immediately took into account the limitations of AI generation and formed prompts for each element.

    Prompt to GPT-6 Astra:

    «Role: You are an experienced creative producer and scriptwriter specializing in creating advertisements using neural networks. Task: Develop a detailed script for a 25-second commercial for a Herbarium (an album with a collection of dried plants/herbs). Important condition: All content (video, photo, audio) will be AI-generated. Therefore, your task is not just to provide a script with a description of the picture, but a script supplemented with prompts for each element. Atmosphere: warm, autumn, cozy».

    The script development and adjustments took ₽102.09.

    Step 2: Generating images for the ad

    Nano Banana 2 was used to create eight base images that set the composition, atmosphere, and style. The total cost of this stage was ₽128.29, which is an average of ₽16 per image.

    The images served as an intermediate state: they fixed the spatial structure of the frame, which simplifies the task for the video model. This allows for consistency between scenes, which is critical for a commercial.

    Image-to-video: precise control over the result

    Unlike text-to-video, where the model simultaneously interprets the description, chooses the composition, and adds movement, image-to-video fixes most variables. This gives greater control over the result and ensures stylistic unity across all frames, which reduces the cost of uniqueizing one video and provides a favorable CPM for advertising materials.

    Step 3: Video generation: the most expensive part of AI advertising

    Converting static images into video scenes is the most resource-intensive stage. Seven video scenes were generated using Kling v3 Video, preserving the original composition and adding natural dynamics.

    The cost of one video scene was about ₽268, and the total cost of video generation was ₽1,878.17. This is 88% of the total budget. The high cost is due to the need to ensure temporal consistency: objects, camera, lighting, and scene geometry must be stable throughout the video.

    How much does AI advertising cost: a 25-second video for ₽2,126 — illustration 2

    Step 4: Ad voiceover with ElevenLabs: cheap and tasteful

    ElevenLabs Flash v3 was used for the voiceover. This stage turned out to be one of the cheapest — only 6.04 ₽. TTS technologies significantly simplify the process compared to traditional voice actor recording, providing fast generation and low costs. This is an excellent option for cheap hypothesis testing and prototypes.

    Step 5: Music for advertising in Suno: budget and limitations

    The musical accompaniment was created using Suno v5.5. The model allows describing the mood and genre, rather than specific notes, which is convenient for advertising tasks. The cost of music generation was 11.82 ₽.

    Although AI music saves budget, full control over the result is not guaranteed. However, for small projects, it is an effective alternative to stock tracks or ordering original music.

    Total cost and comparison with direct subscriptions

    The total cost of a 25-second advertising video created with AI was 2,126.41 ₽.

    Tool Cost
    Script and prompts (GPT-6 Astra) 102.09 ₽
    Base images (Nano Banana 2) 128.29 ₽
    Video generation (Kling v3 Video) 1,878.17 ₽
    Voiceover (ElevenLabs Flash v3) 6.04 ₽
    Music (Suno v5.5) 11.82 ₽
    TOTAL 2,126.41 ₽

    If access to each service were paid for separately, minimum monthly subscriptions would be around 3,591 ₽ (at an exchange rate of $1 = 86.4 ₽):

    • ChatGPT (Plus): $20 (~1,729 ₽)
    • Nano Banana 2: ~$0.54 (~47 ₽)
    • Kling v3 Video: $6.99 (~604 ₽)
    • ElevenLabs Flash: $6 (~519 ₽)
    • Suno v5.5: $8 (~692 ₽)

    These 3,591 ₽ are more of a starting capital than the cost of a single video, as tariffs usually include many more credits than required for one project. This highlights the benefit of using aggregators like BotHub for one-off tasks or cheap hypothesis testing.

    Conclusions and prospects for AI production

    AI production is not yet a seamless process. Each model has its own features and data formats. Cohesion between stages is ensured by an external workflow: prompts, references, manual editing. This distinguishes the demonstration of individual model capabilities from a full-fledged production system, where all elements must work in unison. The price per finished clip with AI can be significantly lower than traditional production, but requires competent pipeline management.

    Overall, AI tools significantly lower the barrier to entry for video content creation, offering a budget-friendly alternative to seeding and traditional production studios. However, obtaining a high-quality result requires skills and an understanding of each model’s limitations. This makes CPM profitable for testing various advertising creatives.

    Frequently asked questions

    What CPM should be considered profitable for AI advertising?

    A profitable CPM depends on the niche and campaign goals. If the cost of producing a video is low, as in our case, then even with an average CPM, the overall return on investment (ROI) can be high. The main advantage is the ability to quickly and cheaply test hypotheses.

    What is cheaper: a banner, a blogger, or an AI video?

    A direct comparison is incorrect, as these are different formats with different goals. However, AI video offers cheap hypothesis testing and can be significantly cheaper than producing a video with a blogger or even some types of banners, especially if complex animations are required. The cost of creating one AI video at 2,126 ₽ makes it competitive for mass content production.

    Is it worth investing in AI for content production?

    Yes, it is. AI significantly reduces the time and cost of production, allowing for quick creation and testing of advertising materials. This is especially relevant for small and medium-sized businesses, as well as for arbitragers who value the cash and unit economics of each creative. However, it is necessary to consider that the price vs. result strongly depends on the skills of working with prompts and post-processing.

    How much does it cost to cut 1 hour of stream using AI?

    The cost of cutting an hour of stream using AI will depend on the services used and their rates for video processing. If it’s about creating short clips, it can be significantly cheaper than manual work and comparable to the price of generating one video, as the main costs will be for transcription and content analysis, not for generating video from scratch.

    What is the price per minute of AI video with an avatar?

    The price per minute of AI video with an avatar varies depending on the platform and the complexity of the avatar (2D, 3D, customization). In our experiment, 25 seconds of video cost 1,878 ₽, which is equivalent to approximately 4,500 ₽ per minute if only the video generation cost is extrapolated. However, avatar platforms have their own rates, which can be both higher and lower, depending on the features and quality provided.

    AI advertising opens up new horizons for content creation, making it more accessible and faster. If you want to delve deeper into the world of AI and learn how it can transform your business, visit our blog. Discover new opportunities and start creating unique content today!