Rebolt Lets Anyone in the Company Build Apps by Talking to AI

The Macro: No-Code Solved the Wrong Problem

The no-code movement had a beautiful pitch: anyone can build software without writing code. Retool, Appsmith, Bubble, Airtable, n8n. The category exploded. Hundreds of millions in venture funding. Entire teams of “citizen developers” inside enterprises dragging and dropping their way to internal tools.

Here is what actually happened. No-code tools replaced one kind of complexity with another. Instead of writing Python, you are configuring components in a visual editor. Instead of debugging code, you are debugging logic flows in a node-based interface. Instead of reading documentation for an API, you are reading documentation for the no-code platform’s API connector. The skill floor dropped, but not by as much as the marketing promised.

The people who got really good at Retool or n8n became a new kind of specialist. They are not developers, but they are not regular business users either. They are the Retool person. Every company has one. When marketing needs a dashboard or ops needs a workflow, they go to the Retool person. The bottleneck moved but it did not disappear.

AI changes this equation because it can absorb the complexity that no-code tools merely redistributed. Instead of learning how to configure a visual workflow builder, you describe what you want in plain language. The AI handles the configuration, the API connections, the data modeling, the UI layout. If the output is wrong, you say what is wrong and the AI fixes it. The interface is a conversation, and conversations are something every employee already knows how to do.

This is not hypothetical anymore. The code generation capabilities of current LLMs are good enough to build real internal tools from natural language descriptions. The question is not whether AI can do this. The question is who builds the best product around it.

The Micro: A Salesforce Architect and a Stack AI Founding Engineer Walk Into a Startup

Rebolt is a platform where anyone in a company can build apps, workflows, and AI agents by describing what they want in natural language. You talk to the AI, it builds the thing, and it integrates with your existing tools: Microsoft 365, Slack, Salesforce, Jira, and more. The code is visible and exportable to GitHub, which is a smart move that reduces vendor lock-in anxiety.

The security posture is serious for an early-stage product. SOC 2 Type II, ISO 27001, GDPR certified. AES 256-bit encryption at rest, TLS 1.2 in transit. SSO, SAML, audit logs, role-based access control. HIPAA compliance is available. That is an enterprise-ready security stack, and it signals that the founders understand what it takes to sell into large organizations.

The product includes a spreadsheet-like database editor, which is a pragmatic choice. Business users think in spreadsheets. Giving them a familiar interface for the data layer while using AI for the logic and UI layer is a good balance.

Celia Manzano and Javier Sanchez are the co-founders. Celia was a cloud architect at Salesforce, leading technical sales on accounts ranging from $150K to $3M. Before that, she was a solution engineer at Apryse and built a torque vectoring ECU for a Formula SAE racing team. She has an aerospace engineering degree from UPM. Javier was a founding engineer at Stack AI (YC W23), where he helped steer core product development from seed to Series A at $2M ARR. He also worked as a software engineer at Ubuntu. They are a three-person team, part of YC’s Winter 2025 batch.

The Stack AI connection is relevant because Stack AI is one of the more credible AI app-building platforms. Javier saw what worked and what did not at close range, and is now building his own version. That is the kind of domain expertise that matters.

Competitors include Retool and Appsmith for internal tools, n8n and Zapier for workflow automation, and newer AI-native entrants like Dust and various “AI app builder” startups. The positioning of replacing both no-code tools and bloated SaaS is aggressive but clear.

The Verdict

I think Rebolt is attacking the right market at the right time. Internal tools and workflow automation are genuinely being disrupted by AI, and the incumbents are bolting AI features onto products that were designed for a pre-AI world. A product built from scratch around natural language as the primary interface has a structural advantage.

The enterprise security certifications this early are a strong signal. Most startups at this stage have a “we will get SOC 2 later” attitude. Rebolt already has it, which means they can sell into the enterprises that actually pay for this kind of tooling.

The risk is the same risk every horizontal platform faces: doing everything means competing with everyone. Retool for dashboards, n8n for automation, Salesforce for CRM workflows. Each of those tools has years of feature depth in their specific domain. Can an AI-first approach deliver enough quality across all of those use cases, or will it be good enough for simple cases and fall apart for complex ones?

Thirty days, show me a case study. One real company replacing one real tool with something built on Rebolt. Sixty days, I want to see the complexity ceiling. What is the most sophisticated thing someone has built on the platform, and did it actually work in production? Ninety days, the question is whether the “everyone builds” promise holds up. Are actual non-technical employees using Rebolt, or is it just developers who prefer talking to an AI over configuring Retool? If it is the latter, that is still a business, but it is a different and smaller one.