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Altan: How This AI Startup Built Software That Builds Itself

One of the most interesting success stories in tech right now is Altan, a Barcelona-based startup founded in 2023. Their idea is audacious: let software build software. They have developed a platform that lets non-technical founders or businesses build applications via text or voice prompts, using AI agents that simulate roles like UX designer, full-stack developer, etc. (Business Insider)

Here are the key parts of their journey:

The Problem They Saw

  • Many business owners want custom apps (for inventory management, reservations, internal tools etc.), but hiring developers is expensive and slow.
  • Non-technical founders often feel stuck with off-the-shelf tools that don’t match their exact needs.
  • Existing low-code / no-code tools still require some technical skill or customization.

Altan’s value proposition: reduce those technical and cost barriers by letting their AI system fill in roles and generate code or systems via natural language. (Business Insider)

How They Built Traction

  • They offer a subscription model starting at about US$25/month, which makes it accessible. (Business Insider)
  • Already they serve ~25,000 users (both businesses and non-technical founders). So usage is growing. (Business Insider)
  • Their offerings are practical: examples include reservation and inventory systems for restaurants. So the products solve real, immediate business problems.
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Funding & Growth

  • In a pre-seed funding round, Altan raised US$2.5 million. (Business Insider)
  • Investors include VentureFriends, JME Ventures, 4Founders Ventures, etc. (Business Insider)
  • A small team (7 people) at this stage. They plan to use the funding to grow that team. (Business Insider)

What Makes Their Success Special

  1. Great product-market fit early on: Non-technical founders are always looking for simpler ways to build stuff.
  2. Low barrier to entry: Both in cost and in skill requirements. The pricing and UX are built to allow a wide audience.
  3. AI agents with defined roles: Not a generic “AI does everything” but modular agents (for different parts like UX, backend) leading to better specialization.
  4. Scalability: Once the platform is built, user-scale can grow without linear growth in human resources.

Challenges They’ll Likely Face

  • Quality and reliability of generated software. Bugs, edge cases, security issues are harder than simply assembling code.
  • Trust and reputation become critical: if their system generates something unstable, users may lose confidence.
  • Competition from other AI-assisted tools, generative AI platforms, low-code / no-code tools.
  • Maintenance and updates: as technologies or frameworks evolve, keeping generated software up to date is non-trivial.
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Lessons for Other Startups

  1. Find a clear problem that many have and solve it simply and accessibly.
  2. Pricing matters: making it affordable helps adoption, especially among non-traditional users.
  3. Use AI agents in a way that mimics existing roles; this gives users mental models they recognize and trust.
  4. Start small, iterate quickly, learn from early users.

Other Noteworthy Stories

  1. Here are a couple more success or rising stories that are trending:

    • Clyx: A social-events/friendship app started by a 25-year-old founder, raised US$14 million in Series A. It uses AI to match people and curate real-life events. (Business Insider)
    • Toss: A South Korean fintech “super app” with over 30 million users. They plan global expansion, including Australia, and aim to issue a won stablecoin. They may go public in U.S. in Q2 2026. Their valuation likely to exceed US$10-15 billion. (Reuters)
    • Carro: Southeast Asia’s leading used-car online marketplace. It is eyeing dual listing (U.S., Hong Kong or Singapore) with valuation exceeding US$3 billion. (Reuters)