Softr, the Berlin-based no-code platform used by more than one million builders and 7,000 organizations including Netflix, Google, and Stripe, today launched what it calls an AI-native platform — a bet that the explosive growth of AI-powered app creation tools has produced a market full of impressive demos but very little production-ready business software.
The company’s new AI Co-Builder lets non-technical users describe in plain language the software they need, and the platform generates a fully integrated system — database, user interface, permissions, and business logic included — connected and ready for real-world deployment immediately. The move marks a fundamental evolution for a company that spent five years building a no-code business before layering AI on top of what it describes as a proven infrastructure of constrained, pre-built building blocks.
“Most AI app-builders stop at the shiny demo stage,” Softr Co-Founder and CEO Mariam Hakobyan told VentureBeat in an exclusive interview ahead of the launch. “A lot of the time, people generate calculators, landing pages, and websites — and there are a huge number of use cases for those. But there is no actual business application builder, which has completely different needs.”
The announcement arrives at a moment when the AI app-building market finds itself at an inflection point. A wave of so-called “vibe coding” platforms — tools like Lovable, Bolt, and Replit that generate application code from natural language prompts — have captured developer mindshare and venture capital over the past 18 months. But Hakobyan argues those tools fundamentally misserve the audience Softr is chasing: the estimated billions of non-technical business users inside companies who need custom operational software but lack the skills to maintain AI-generated code when it inevitably breaks.
Why AI-generated app prototypes keep failing when real business data is involved
The core tension Softr is trying to resolve is one that has plagued the AI app-building category since its inception: the gap between what looks good in a demo and what actually works when real users, real data, and real security requirements enter the picture.
Business software — client portals, CRMs, internal operational tools, inventory management systems — requires authentication, role-based permissions, database integrity, and workflow automation that must function reliably every single time. When an AI-generated prototype fails in these areas, fixing it typically requires a developer, which defeats the purpose of the no-code promise entirely.
“One prompt might break 10 previous steps that you’ve already completed,” Hakobyan said, describing the experience non-technical users face on vibe coding platforms. “You keep prompting, keep trying to fix errors that the AI generated, and you end up maintaining something you didn’t even sign up for in the first place.”
This critique targets a real structural limitation in how many AI app builders work today. Platforms that fully rely on AI to generate application code from scratch leave users with a codebase they cannot read, debug, or maintain without technical expertise. To connect those generated apps to real databases, login systems, or third-party services, users often must integrate tools like Supabase and make API calls — tasks that effectively require them to become developers. Softr’s position is that these platforms have replaced one form of coding with another, swapping programming languages for English-language prompts that carry all the same fragility.
How Softr’s building block architecture avoids the hallucination problem that plagues AI code generators
Rather than generating raw code, Softr’s platform uses what Hakobyan describes as “proven and structured building blocks” — pre-built components for standard application functions like Kanban boards, list views, tables, user authentication, and permissions. The AI interprets a user’s requirements, guides them through targeted questions about login functionality, permission types, and user roles, then assembles these tested building blocks in a constrained, intelligent way. Only when a user requests functionality that falls outside the standard 80% covered by these blocks does the system build a custom component with AI.
“It basically never hallucinates, because it’s all built on an infrastructure that’s secure and constrained,” Hakobyan explained. “It doesn’t generate code or leave you with code, because underneath, it uses our existing building block model.”
The result is not a code repository. It is a live application running on Softr’s infrastructure, with a visual editor that users can continue to modify — either by prompting the AI further or by directly manipulating the no-code interface. This dual-editing model is a deliberate design decision that Hakobyan frames as the platform’s core differentiator. “It almost combines the best of both worlds of AI and no code, and really lets users to either continue iterating with AI or then continue working with the app visually, which is much simpler and easier and for them to have control,” she said.
Core platform foundations — authentication, user roles, permissions, hosting, and SSL — are built in from the start, eliminating what Hakobyan calls the “blank canvas problem” that plagues vibe coding platforms, where every user must architect fundamental application infrastructure from scratch via prompts. The platform uses a SaaS subscription pricing model, with each plan including a set number of AI credits and the option to purchase more — though the visual editor means users don’t always need to consume credits, since direct manipulation of the no-code interface is often faster and more precise.
Inside the five-year journey from Airtable interface to profitable AI-native platform
Softr’s journey to this moment has been a gradual, disciplined expansion that stands in contrast to the rapid fundraising cycles common among AI startups. The company launched in 2020 as a no-code interface layer on top of Airtable, the popular enterprise database product. Co-founded by Armenian entrepreneurs Hakobyan and CTO Artur Mkrtchyan, the startup raised a $2.2 million seed round in early 2021 led by Atlantic Labs, followed by a $13.5 million Series A in January 2022 led by FirstMark Capital.
What happened next is notable for its restraint. Softr has not raised additional capital since that 2022 Series A. Instead, it has grown to profitability. “We have been profitable for the past whole year, and we’re about 50 people team,” Hakobyan told VentureBeat. “We have grown to eight-digit revenue fully PLG, no sales team, mostly through word of mouth, organic growth.”
That financial profile — eight-figure annual revenue, profitable, 50 employees, no sales team — is striking in a market where many AI-powered competitors are spending heavily to acquire users. Over the past year, the company has steadily expanded its technical capabilities, moving beyond its original Airtable dependency to support Google Sheets, Notion, PostgreSQL, MySQL, MariaDB, and other databases.
In February 2025, TechCrunch reported on this expansion, with Hakobyan explaining that many potential customers had “data scattered across many different tools” and needed a single platform to unify that fragmented infrastructure. Today, Softr offers 15-plus native integrations with external databases, plus a REST API connector for additional data sources. The new AI Co-Builder represents the culmination of this multi-year evolution — combining the building block architecture, the broad data integration layer, and a new AI interface into a single platform for business application creation.
How Softr positions itself against both no-code incumbents and vibe coding startups
Softr’s launch lands in a rapidly fragmenting competitive landscape, and Hakobyan is deliberate about where she draws the lines. On one side sit traditional no-code platforms like Bubble, which offer deep customization and design freedom but require users to build everything from scratch — database schemas, pixel-level layouts, authentication systems — creating a steeper learning curve. A TechRadar review noted that while Softr’s blocks don’t offer the same design freedom as Bubble, the platform’s simplicity makes it accessible to genuinely non-technical users. In a comparison published by Business Insider Africa in June, Softr was characterized as offering “minimal learning curve, especially for internal or web-based tools,” though with limitations in scalability for more complex applications.
On the other side sit the AI-first code generation tools that Hakobyan views as fundamentally misaligned with business software requirements. “Before people were coding, then they were coding through APIs, now they are coding almost through a human language interface, right, just by with English,” Hakobyan said. “But what Softr does is fundamentally different. It abstracts all of that and makes the creation simple.”
She also distinguishes Softr from developer-focused AI coding assistants like Anthropic’s Claude Code, positioning those as tools that make professional developers more efficient rather than tools that enable non-developers to build software.”There are amazing tools for developers — that’s great. The target audience is developers,” Hakobyan acknowledged. Instead, Softr targets a specific and potentially enormous market: businesses that need custom internal and external-facing operational tools and currently rely on spreadsheets, email, or rigid off-the-shelf software that doesn’t match their actual processes. Hakobyan described use cases ranging from asset production workflows for film companies — where internal teams, external agencies, and approvers interact across a multi-stage process — to lightweight CRM replacements for teams that don’t need the full complexity of Salesforce. “There’s not even a vertical solution for this type of process,” she said. “It’s very custom to each organization.”
What Netflix, Google, and thousands of non-tech companies actually build on the platform
Many of Softr’s highest-profile customers — Netflix, Google, Stripe, UPS — were using the platform before the AI Co-Builder even existed, building on the company’s original no-code foundation. But the user base extends far beyond Silicon Valley. Non-tech organizations in real estate, manufacturing, and logistics represent a significant portion of Softr’s customer base — companies that often still manage core processes with pen, paper, and spreadsheets.
“A lot of these companies — you might think they already have the solutions, but they don’t,” Hakobyan noted. “In tech companies, most of the time, CRM and project management tools are already established. But most of our customers are using Softr for internal operational tooling or workflow tooling, where the use case involves lots of different departments and even external parties.”
The company is SOC 2 (Type II) compliant and GDPR compliant, with additional compliance capabilities in development. Hakobyan noted that auditing and governance functionality can be built directly into applications using the platform’s database and workflow tools, with a native logging and auditing system expected to ship in the near term.
Softr’s billion-user ambition and the Canva analogy that explains its strategy
Softr’s stated mission — to empower billions of business users to create production-ready software — is audacious, but Hakobyan frames the AI Co-Builder launch as a fundamental acceleration of the trajectory the company has been on for five years. “Everything people would have to spend hours doing is done within five minutes,” she said. “And obviously that helps more people to actually build real software.”
The company plans to layer a product-led sales motion on top of its existing PLG engine, targeting larger enterprise customers with higher average contract values. This represents a deliberate strategic expansion from the small and mid-sized businesses that have formed Softr’s core customer base — a segment that TechCrunch identified as natural Softr customers as far back as the company’s 2022 Series A, given that those firms are most likely to be priced out of the competitive developer market.
Hakobyan draws an analogy that has apparently become common among the company’s users: Softr as “Canva for web apps.” Just as Canva made professional design accessible to non-designers, Softr aims to make business software creation accessible to non-developers. Whether the company can translate its disciplined growth and profitable foundation into a platform that genuinely serves that enormous addressable market remains to be seen. Softr faces intensifying competition from both traditional no-code incumbents adding AI capabilities and well-funded AI-native startups approaching the problem from the code-generation side.
But Softr enters this next phase with advantages that many competitors lack: a profitable business, a million-user base already shipping production software, and an architectural approach that treats AI as an accelerant layered on top of proven infrastructure rather than an unpredictable replacement for it. “No code alone had its own problems, and AI alone also just can’t do the job,” Hakobyan said. “The combination is what’s going to be making it really powerful.”
For the past five years, Softr bet that the hardest part of software wasn’t writing the code — it was getting the databases, permissions, and business logic right. Now the company is betting that in the age of AI, that conviction matters more than ever. The millions of business users who have never written a line of code but desperately need custom software are about to find out whether Softr is right.
