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OrgMind AI extracts scattered company knowledge from Slack, Notion, Drive, and meetings into a living knowledge graph, so institutional memory is current, connected, and executable.
We cut onboarding time by 70%, eliminate repeat mistakes, and preserve knowledge when people leave. You pay $15/user/mo base + $50 per knowledge gap eliminated. We’re building the operating system for organizational intelligence.
A living knowledge graph that auto-extracts, connects, and executes.
1. Auto-Ingests: Slack, Notion, GitHub, Google Drive, Zoom, Email
2.Maps Context: Who knows what? Why was this decision made? How does this process work?
3.Answers Questions: “How do we deploy?” = Gets runbook + owner + recent changes
4.Preserves Memory: Auto-captures knowledge when employees depart
5.Outcome: 70% faster onboarding, 60% less repeat work, zero institutional amnesia.
It’s like having a senior engineer who attended every meeting, read every doc, and wrote every commit : available 24/7.
We didn’t just build a search tool. We created a demo and proved we can capture tacit knowledge and make it executable. Teams are productive in days, not months.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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NeuralOS The AI-Native Operating System
NeuralOS is a concept for a next-generation operating system built around autonomous AI agents rather than traditional applications. Instead of manually switching between tools and workflows, users simply provide a goal, and the system coordinates specialized agents to research, analyze, organize knowledge, and generate complete deliverables.
At the center of the experience is the Intelligence Core, a living system that orchestrates communication between agents, manages knowledge networks, and transforms user intent into actionable results.
The project explores a future where operating systems become intelligent collaborators rather than passive software environments.
NeuralOS is a conceptual AI-native operating system designed around autonomous intelligence rather than traditional applications. Instead of manually navigating between different tools, users provide a goal, and the system coordinates specialized AI agents to research information, analyze data, organize knowledge, and generate complete results. At the center of the experience is the Intelligence Core, which acts as the operating system's brain, orchestrating communication between agents and managing the flow of information across the platform.
How I Used Google Stitch
Google Stitch was used throughout the entire design process, from initial ideation to final refinement.
My workflow included:
Generating the initial operating system concept
Exploring multiple layout and interaction directions
Refining screens through iterative prompting
Building a consistent visual language across the product
Designing complex agent orchestration workflows
Creating a connected multi-screen user journey
Rapidly testing and evolving ideas without rebuilding screens from scratch
Stitch allowed me to move from a rough concept to a complete product vision significantly faster than a traditional design workflow.
Design Goals
The challenge theme was "Build interfaces that feel alive."
To support this theme, NeuralOS focuses on:
Living intelligence systems
Dynamic agent collaboration
Spatial knowledge visualization
Real-time orchestration workflows
Motion-driven feedback
AI-native interaction patterns
Rather than creating another dashboard, I wanted the interface to feel like an intelligent ecosystem that continuously thinks, learns, and evolves.
## Feedback on Google Stitch
My experience with Stitch was extremely positive. The platform made it easy to rapidly explore ideas, iterate on layouts, and build a cohesive product experience across multiple screens.
One area I would improve in future projects is the use of generated icons and decorative assets. While they are useful during ideation, I found that replacing them with established icon libraries and design systems creates stronger visual consistency and makes the final product feel more realistic and production-ready.
The strongest results came from combining Stitch's AI-assisted generation with thoughtful human refinement. This balance allowed me to move quickly while still maintaining creative control over the final experience.
GitHub Repository:
https://github.com/MHK-123/NeuralOS
Google Stitch Project:
https://stitch.withgoogle.com/projects/1582384152650609720
Why Small Automations Make Big Teams Faster
Most teams don’t need a huge system rebuild.
They need small, smart automations that remove the daily repeat work: updating boards, sending reminders, syncing data, organizing leads, or moving information between tools.
That’s where AI automation becomes powerful.
Not because it replaces people, but because it gives people more time to focus on real work, better decisions, and better client communication.
A good automation should feel invisible: simple, reliable, and easy to manage.
That’s the kind of system I like building.
#AIautomation #WorkflowAutomation #NoCode #n8n #Make #Zapier #SaaS #Productivity #InternalTools
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