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The Boring Problem That Makes Millions ft. Elias Stråvik
In today's episode, I chat with Elias Stråvik, founder at Cleanroom (AI-powered CRM data cleaning), about solving the unsexy problem he faced as GTM engineer—clients asking to enrich CRM but Clay lookups returning six results in a cell, realizing good data makes him 10x effective but hard to set deduplication rules across rows, so he built next-gen tool using AI just for this problem.
We explore his Swiss law tech campaign targeting AI-averse old partners vs AI-native new grads, scraping law firm directories, using AI vision to approximate age ("how old does this person look?") via LinkedIn graduation dates and profile photos, translating outbound to German/French based on location—getting 40% reply rate because lawyers check inbox in minutes with polite rejections vs SF founders saying "get off my list" with expletives. Elias shares his journey launching VC-backed employee wellbeing startup (vitamin not painkiller—buyers getting fired during 2021-2022 economic crash with no budget), discovering Clay after final_final_no_for_real_this_time.csv workflow realizing he could handle dozens of customers, meeting Justin (Kiln) on Twitter, joining Kiln as first GTM engineer then head (best year ever), and launching Cleanroom while working with Kiln on educational side. He predicts Clay dominating (anyone can use it but experts 10X-100X results), bifurcation with cloud code/cursor making it easier to tell AI than click buttons (shift back from low-code), hackers building code-first GTM agencies with better speed/cost vs enterprises wanting stable maintainable tools, and computing history rhyming. Elias's advice: GTM engineering has super low paid ($1K-$2K/month) or senior Anthropic/OpenAI roles with no real middle class yet, go freelancer/agency route to gain experience, step across river of cringe posting on Twitter/LinkedIn building stuff publicly—everything you want is on other side of cringe.
Enjoy 🙂
(00:00) Introduction to Outbound Wizards
(00:34) What Cleanroom Does: AI-Powered CRM Data Cleaning
(02:38) Swiss Law Tech Campaign (AI Vision for Age Approximation)
(06:47) Native Language Translation (40% Reply Rate)
(09:17) Journey: Employee Wellbeing Startup (Vitamin Not Painkiller)
(11:27) Discovering Clay After final_final_no_for_real_this_time.csv
(14:15) Future Prediction: Clay Dominating, Cloud Code Bifurcation
(21:25) Advice: No Real Middle Class, Go Freelancer/Agency Route
(27:06) Step Across River of Cringe, Build Publicly
(29:44) Closing and Contact Information
🔗 CONNECT WITH ELIAS
👥 LinkedIn
💻 Website
🔗 CONNECT WITH SAURAV
🎥 YouTube Channel
🐦 X (Twitter)
💻 Website
👥 LinkedIn
📧 Email - [email protected]
🙏 LEAVE A REVIEW If you enjoyed listening to the podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)
👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.
View all episodes
By Saurav GuptaIn today's episode, I chat with Elias Stråvik, founder at Cleanroom (AI-powered CRM data cleaning), about solving the unsexy problem he faced as GTM engineer—clients asking to enrich CRM but Clay lookups returning six results in a cell, realizing good data makes him 10x effective but hard to set deduplication rules across rows, so he built next-gen tool using AI just for this problem.
We explore his Swiss law tech campaign targeting AI-averse old partners vs AI-native new grads, scraping law firm directories, using AI vision to approximate age ("how old does this person look?") via LinkedIn graduation dates and profile photos, translating outbound to German/French based on location—getting 40% reply rate because lawyers check inbox in minutes with polite rejections vs SF founders saying "get off my list" with expletives. Elias shares his journey launching VC-backed employee wellbeing startup (vitamin not painkiller—buyers getting fired during 2021-2022 economic crash with no budget), discovering Clay after final_final_no_for_real_this_time.csv workflow realizing he could handle dozens of customers, meeting Justin (Kiln) on Twitter, joining Kiln as first GTM engineer then head (best year ever), and launching Cleanroom while working with Kiln on educational side. He predicts Clay dominating (anyone can use it but experts 10X-100X results), bifurcation with cloud code/cursor making it easier to tell AI than click buttons (shift back from low-code), hackers building code-first GTM agencies with better speed/cost vs enterprises wanting stable maintainable tools, and computing history rhyming. Elias's advice: GTM engineering has super low paid ($1K-$2K/month) or senior Anthropic/OpenAI roles with no real middle class yet, go freelancer/agency route to gain experience, step across river of cringe posting on Twitter/LinkedIn building stuff publicly—everything you want is on other side of cringe.
Enjoy 🙂
(00:00) Introduction to Outbound Wizards
(00:34) What Cleanroom Does: AI-Powered CRM Data Cleaning
(02:38) Swiss Law Tech Campaign (AI Vision for Age Approximation)
(06:47) Native Language Translation (40% Reply Rate)
(09:17) Journey: Employee Wellbeing Startup (Vitamin Not Painkiller)
(11:27) Discovering Clay After final_final_no_for_real_this_time.csv
(14:15) Future Prediction: Clay Dominating, Cloud Code Bifurcation
(21:25) Advice: No Real Middle Class, Go Freelancer/Agency Route
(27:06) Step Across River of Cringe, Build Publicly
(29:44) Closing and Contact Information
🔗 CONNECT WITH ELIAS
👥 LinkedIn
💻 Website
🔗 CONNECT WITH SAURAV
🎥 YouTube Channel
🐦 X (Twitter)
💻 Website
👥 LinkedIn
📧 Email - [email protected]
🙏 LEAVE A REVIEW If you enjoyed listening to the podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)
👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.