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Visual Agent Builder for Customer Support
Found an idea? We can build it for you.
We design and develop SaaS, AI, and mobile products — from concept to launch in weeks.
Inspired by a conversation on:
Latent Space: The AI Engineer Podcast
DevDay 2025: Apps SDK, Agent Kit, MCP, Codex and why Prompting is More Important than Ever
Host: swyx + Alessio
Timestamp: 00:09:33 - 00:10:29
Found an idea? We can build it for you.
We design and develop SaaS, AI, and mobile products — from concept to launch in weeks.
Direct Quote
"We launched Agent Kit today, full set of solutions to build, deploy, and optimize agents."
Market Gap
Developers struggle to efficiently build AI agents for production.
Summary
Categorization
Potential MRR (18-24 months)
* Estimates assume solo founder/bootstrap scenario with competent execution
Scores
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Sign InHow should I validate this saas idea before building it?
2:34 PM
Great question! For a saas idea like this, I'd recommend starting with these validation steps:
- Customer interviews: Talk to Technical to understand their pain points
- MVP approach: Build a simple landing page to test demand
- Competitor analysis: Research existing solutions and identify gaps
Would you like me to help you create a specific validation plan for your medium difficulty idea?
2:35 PM
Yes, and what about the technical implementation? Should I build this myself or hire a team?
2:36 PM
Based on your idea's complexity and 1-3 months, here's my recommendation:
Technical Strategy:
- Start with no-code tools for rapid prototyping
- Consider your technical background and available $1,000-$10,000
- Plan for scalability from day one
I can help you create a detailed technical roadmap and resource allocation plan...
2:37 PM
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Drag-and-Drop AI Agent Builder
The drag-and-drop AI agent builder allows non-technical users to easily create and manage AI agents. By providing a visual interface, users can design workflows that leverage OpenAI's advanced models, reducing the technical barrier typically associated with AI development. This tool can be implemented as a SaaS solution where users subscribe to access the platform, enabling them to build tailored AI agents for various applications such as customer support, data analysis, or content generation. The target audience includes small to medium-sized businesses looking to adopt AI without hiring technical staff. This approach not only democratizes access to AI but also encourages innovation across industries.