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Engineered and maintained Azure cloud environments supporting DevOps, identity, and machine learning workloads. Built and managed CI/CD pipelines, automated deployments, configured infrastructure and access policies through Microsoft Entra ID, and supported ML lifecycle workflows using Azure ML and Azure AI Foundry. Helped deliver secure, scalable, and production-ready cloud solutions for application and AI services.
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I built AstraOS — Not another basic Notion AI wrapper.
AstraOS is a full AI Team living inside Notion with 7 specialist modes that actually work together:
• Productivity Coach (Essentialism + GTD)
• Strategist (OKRs, Pre-mortems, First Principles)
• Content Writer & Social Media Re-worker
• Researcher
• Personal Assistant
• Specialist Colleague (co-founder level feedback)
• Advanced Workspace Assistant (auto-creates databases & organizes workspace)
The real differentiators:
• Smart auto-logging (no more “log this” every time)
• Built-in memory via databases
• Proper onboarding + personalization
• Can combine multiple modes in one response
• Everything stays under one clean AstraOS HQ
Most custom agents are just fancy prompts. AstraOS feels like a real team member who knows you, remembers your goals, and proactively saves your plans, research & decisions. Built for heavy Notion users who want to 10x their output. 🚀
🔗 Agent: AstraOS (pending review)
Agent is live : https://www.notion.so/marketplace/custom-agents/astraos
notion.so
Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.
A tool that connects everyday work into one space. It gives you and your teams AI tools—search, writing, note-taking—inside an all-in-one, flexible workspace.
Freelancers lose thousands of dollars every year to scope creep. You say "yes" to a quick favor, and suddenly you're doing hours of unpaid work. 💸
Enter NeuraFlow 🧠 — an autonomous CI/CD pipeline for your freelance contracts. No chatting with AI bots. No manually copying prompts.
Just drop a client proposal or change request into your database, change the status to "Pending Signature," and NeuraFlow runs completely in the background to:
🔍 Audit Proposals: Flags dangerous, vague phrases and provides concrete, copy-paste rewrites to protect your boundaries.
⚖️ Guard Your Scope: Compares mid-project requests directly against your original signed SOW.
🛑 Push Back Professionally: Automatically verdicts requests as "Out of Scope" and drafts a diplomatic email with a calculated change order estimate ($).
🚩 Track "Repeat Offenders": Detects clients who constantly ask for free work across multiple projects.
⚡ Fire Real-Time Alerts: Sends instant Gmail & Slack notifications when a high-risk scope threat is detected.
Why it's reusable (Build Once, Reuse Forever):
NeuraFlow works for any freelancer, agency, or consultant in any industry. A vague scope is a universal threat.
✅ Zero setup per client: The text is the context. Just paste and protect.
✅ Database-driven autonomy: No chat interfaces. Just change a Notion status and walk away.
Your profitability, guarded autonomously. 🚀
🔗 Try the Agent: https://www.notion.so/marketplace/custom-agents/neuraflow
📁 Duplicate the Database: https://www.notion.so/3338770f9c6d80b4bf6cd11df38527fd?v=3338770f9c6d80fba613000c8957e5f7&source=copy_link
notioncustomagentbuildathonNotionAIAI AutomationPrompt EngineeringBusiness Workflow AutomationNotionSlack
Most teams we work with want to say their product is AI-powered. Few have asked whether their organisation is ready to support that claim.
We have observed a recurring pattern where a team commits to building a machine learning system and, after months, discovers that their data isn't clean enough to train on. The infrastructure then fails to reliably serve a model.
In such cases, our diagnosis has often concluded that the foundation is the problem. Machine learning readiness is a precondition, and one must begin with a straightforward question - "Do we have the data pipeline, infrastructure and cross-functional alignment to make this sustainable beyond a PoC?"
That question is what prompted our first article titled "The Machine Learning Readiness Checklist".
We cover everything a team needs, from data and infrastructure to the right kind of team members. All of this must be done before committing serious engineering time and budgets.
If you're a founder, engineering lead or a decision maker within your organisation who wants to build things correctly, we encourage you to read the full piece here:
https://www.algorithmic.co/blogs/the-machine-learning-checklist
We'll be sharing more each week. Follow along if this is relevant to what you're building.
P.S. This article is from late 2025 but more than ever relevant.
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