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Numun.io AI Platform Overview
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Picture a workflow that captures information, remembers it, and then sends you insights automatically.
Your input is stored in memory, so over time the workflow builds a growing knowledge base.
Whenever you want, the workflow can retrieve all stored memories and create a concise summary, distilling the key points without you having to dig through everything.
Once the summary is ready, it’s sent directly to your email, giving you a digest of relevant information delivered automatically.
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In Numun.io (http://Numun.io), workflows are first designed and validated in Agent Studio as structured, multi-step graphs—made up of agents, tools, conditionals, loops, and outputs. Once a workflow is complete, it doesn’t live in isolation.
By toggling the workflow on in Agent+ Mode, users can execute that same workflow directly from the AI chat interface.
Instead of receiving a simple text response, the AI runs the full workflow behind the scenes and returns structured run results, including tool outputs, decisions taken, and final outcomes.
The result is an AI experience that goes beyond conversation, turning chat into a live interface for executing and inspecting real autonomous workflows.
In this example, Python code is generated and executed via Fly.io (http://Fly.io), returning a structured summary of results.
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Agent Store is a hub where users can discover, test, and share autonomous agents and workflows.
With Try Mode, users can interact with agents in a safe, sandboxed environment before installing them, exploring functionality and confirming performance without risk.
The platform also supports public sharing, enabling creators to publish agents and workflows for the broader community.
This promotes collaboration, learning, and adoption of tested, reliable workflows while giving developers visibility and feedback on their creations.
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Talent XYZ is a modern talent matching and recruiting platform designed to connect high-quality talent with the right opportunities—faster and more precisely.
The platform focuses on moving beyond keyword-based resumes and shallow filters by incorporating richer candidate profiles, structured role requirements, and intelligent matching logic. The goal is to reduce noise, shorten hiring cycles, and improve signal quality for both candidates and hiring teams.
Talent XYZ is built to support real recruiting workflows, including talent discovery, evaluation, and pipeline management, with an emphasis on clarity and efficiency as hiring needs evolve.
This project includes full-stack platform development, data modeling for talent and roles, matching logic, and scalable infrastructure designed for real-world hiring environments.
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Wander & Wonder is a full-featured web app designed to help users explore destinations, experiences, and adventures in a curated, personalized way. The platform transforms travel discovery into an interactive, user-friendly experience.
The project demonstrates how a web app can turn exploration into a seamless digital experience, combining rich content, interactivity, and scalable architecture.
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SoulSync is a human alignment platform designed to help people connect, collaborate, and relate with greater depth and clarity.
Rather than relying on static profiles or surface-level preferences, SoulSync builds adaptive digital representations of individuals across psychological, emotional, cognitive, and behavioral dimensions. These profiles evolve over time, enabling more accurate compatibility, personalization, and long-term alignment.
The system is built to support real-world applications where understanding people matters—dating and relationships.
This project includes full-stack platform development, identity and profile modeling, matching logic, and scalable infrastructure focused on trust and longevity.
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Keat.info (http://Keat.info) is a custom‑built personal portfolio website created end‑to‑end to showcase professional experience, skills, and work history. The site was designed with clarity, performance, and user focus in mind—making it easy for visitors to understand career background, technical strengths, and contact information at a glance.
This build demonstrates how a polished, professional personal site can serve as a clear signal of capability and credibility—turning a resume into an accessible, scalable web presence that reflects technical and strategic thinking.
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Using AI Builder in Agent Studio, I designed and generated a multi-step workflow that orchestrates agents, tools, conditionals, loops, and parallel execution in a single graph.
The workflow interprets user input, plans tasks, executes actions via integrated tools, and produces structured outputs, fully autonomously.
It’s a powerful example of moving from AI-generated plan to real-world actionable execution.
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Orbs are collaborative workspaces where teams or individuals can run projects with the support of specialized AI agents.
Public Orbs allow open collaboration and discovery, while private Orbs keep sensitive work secure.
AI assistants in each Orb can execute workflows, manage tasks, and automate complex logic. Turning ideas into reliable, actionable outcomes.
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AI Builder + Agent Studio is a system for designing, testing, and deploying AI agents and autonomous workflows as structured, production-ready graphs, not fragile prompts.
At the core is Agent Studio, where workflows are defined as explicit graphs made up of agents, tools, conditionals, loops, routers, and outputs.
The AI Builder sits on top of this system and generates complete workflows automatically. Instead of writing code or wiring nodes manually, users describe the goal—and the AI Builder constructs a valid workflow graph.
Every workflow can be tested using a test harness, ensuring agents execute correctly before deployment.
This project demonstrates how AI agents can be treated like real software systems—versioned, validated, and orchestrated—instead of one-off prompt chains.
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Built a responsive, full-stack website showcasing seasonal lighting services with clear service tiers, lead capture, and mobile optimization. The site communicates trust and warmth, helping a local family business attract customers and convert visitors into requests efficiently.
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The Autonomous Browser in Numun.io (http://Numun.io) is a fully actionable AI agent embedded in a live browser session. Users interact through natural language, and the agent executes real tasks online, like navigating websites, filling forms, extracting data, and interacting with web applications—without manual coding or scripting.
This is not just a “chatbot.” It’s a production-grade autonomous operator: the system interprets intent, plans multi-step workflows, and performs actions reliably in real time, bridging the gap between AI reasoning and web-based execution.
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Numun Labs is a physics and technology laboratory focused on translating first-principles research into measurable, testable, and deployable systems.
The lab develops foundational models, research software, and experimental frameworks that turn abstract physical laws into operational tools. Work spans mathematical modeling, simulation engines, verification-grade analytics, and software systems designed to validate theory against real-world data.
Numun Labs operates at the boundary between discovery and implementation—building systems that don’t just hypothesize, but measure, predict, and close loops between theory and reality. Projects emphasize rigor, falsifiability, and reproducibility, with an engineering mindset toward long-term applicability.
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Numun.io (http://Numun.io) is an autonomous agent and workflow execution platform designed to turn intent into action—reliably, securely, and at scale.
Numun enables users and teams to design, deploy, and run AI-powered agents and workflows that browse the web, call tools, orchestrate systems, and complete real tasks end to end. At its core is a contract-based execution model that emphasizes determinism, observability, and accountability—bringing production-grade discipline to AI agents.
Numun is built for developers, operators, and founders who need agents that actually work in the real world—not demos that break under pressure.
This project includes full-stack platform development, execution infrastructure, agent runtime design, workflow orchestration, and system-level reliability engineering.
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RailRadar is a real-time train detection and arrival prediction system built for communities impacted by rail crossings.
Using a distributed network of camera-based tripwire sensors, RailRadar detects train movements at the edge and generates bias-corrected ETAs that adapt to real-world conditions. The system delivers timely, reliable alerts without relying on railroad-provided data or centralized tracking feeds.
RailRadar is designed for resilience and accuracy in the field. The platform supports community alerts, operational monitoring, and future integrations with municipal and transportation systems.
This project includes full-stack system design, edge sensing logic, backend services, alerting infrastructure, and deployment workflows focused on real-world reliability, not demos.
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