AI-workflows.io's answer

Most automation tools treat AI as just another step in a rigid if-then chain. AI Workflows is different because the AI agent IS the orchestrator. Instead of building 15-step workflows with branches and filters, you connect a trigger to an agent and let it read context, make decisions, and execute actions autonomously. The visual canvas makes complex AI orchestration feel like dragging blocks on a whiteboard. Built-in knowledge base (RAG), agent memory, and reasoning traces mean your workflows actually understand your business, not just move data between apps.

Gitmore.io's answer:

Gitmore represents a thoughtful approach to democratizing Git repository intelligence, successfully addressing the common challenge of extracting actionable insights from complex development activities. The platform’s combination of AI-powered analysis, cross-platform compatibility, and business-friendly reporting creates compelling value for teams seeking to improve visibility into development progress without investing in comprehensive engineering analytics platforms.

AI-workflows.io's answer

Three reasons. First, AI agents replace the logic layer entirely. Where Zapier needs 15 steps with filters and branches, AI Workflows needs 3 nodes: trigger, agent, output. Second, the knowledge base is native. Upload your docs and the agent references them on every run, no Pinecone or vector database setup needed. Third, you can watch the AI think. Reasoning traces show exactly why an agent made each decision, so you can debug and improve instead of guessing. All of this with no code, starting at €59 per month.

AI-workflows.io's answer

Founders, small business operators, marketing teams, and revenue operations leaders at companies with 1 to 50 people. They are tech-savvy enough to have tried Zapier or Make but frustrated by the limits of rules-based automation. They want AI that understands their business context and makes judgment calls, not just moves data between apps. Typically running sales, support, content, or back-office operations and looking to do more with a lean team.

AI-workflows.io's answer

We kept seeing the same pattern: teams bolting ChatGPT onto their Zapier workflows and hoping for the best. It worked for simple tasks but fell apart the moment they needed AI to actually understand context, reference company docs, or make decisions across multiple steps. So we built the platform we wished existed. A visual canvas where AI agents are first-class citizens, not afterthoughts. Where you can upload your knowledge base, watch agents reason in real-time, and deploy workflows that genuinely think. We are currently in early access, building in public with our founding members shaping the roadmap.

AI-workflows.io's answer

1) Next.js (React) for the web application 2) React Flow for the visual workflow canvas 3) Supabase (PostgreSQL) for the database and authentication 4) OpenAI, Google Gemini, and Anthropic Claude for AI model providers 5) Vercel for hosting and edge delivery 6) Stripe for payments and billing 7) Resend for transactional email 8) Upstash Redis for rate limiting and caching 9) TypeScript end to end

AI-workflows.io's answer

We are currently in early access and building our founding member base. We don't publicly disclose individual customer names at this stage, but our early users include:

Solo founders automating lead qualification and outreach Marketing agencies repurposing content across channels E-commerce operators managing reviews and inventory Small law firms extracting clauses and generating NDAs Recruiting teams screening resumes and scheduling interviews Operations managers turning meeting notes into action items