🧠 Steps to Build a POC Locally with Windows AI Foundry

 🚀 Introduction

What is Foundry Local?

Foundry Local brings the power and trust of Azure AI Foundry to your device. It includes everything you need to run AI apps locally.

As AI adoption grows, developers are increasingly looking for ways to build intelligent applications that run efficiently on local machines. Windows AI Foundry, especially its Foundry Local feature, enables developers to create AI-powered Proof of Concepts (POCs) without relying on cloud infrastructure or Azure subscriptions. This article walks you through the step-by-step process of building a POC locally using Windows AI Foundry—and addresses common challenges along the way.

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🧰 Prerequisites

Before you begin, ensure you have:

• A Windows 11 machine with sufficient CPU/GPU/NPU resources.
• Internet access (for initial setup and model downloads).
• Familiarity with command-line tools and programming (Python, C#, or JavaScript).
• Installed tools:
  • Foundry CLI
  • Foundry Local SDK
  • ONNX Runtime (optional)

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🛠️ Step-by-Step Guide

Step 1: Install Foundry CLI and SDK

Install the Foundry CLI:

winget install FoundryCLI

Install the SDK for your preferred language (e.g., Python):

pip install foundry-sdk

Step 2: Choose and Download a Model

Foundry Local supports several optimized models:

• Phi-4 Reasoning
• Mistral
• Qwen 2.5 Instruct
• DeepSeek R1

Download a model:

foundry models download phi-4

Step 3: Run Inference Locally

Run inference directly from the CLI:

foundry model run phi-4 --input "Explain quantum computing in simple terms."

Step 4: Build Your Application

Example using Python:

from foundry import FoundryModel

model = FoundryModel("phi-4")

response = model.run("What is the capital of Karnataka?")

print(response)

Step 5: Test and Iterate

Test your application with different inputs. Monitor performance and refine prompts or model selection as needed.

⚠️ Common Challenges and Solutions

If winget is blocked by organization policies, try this:

🔁 Manual Installation

1. Visit the official Foundry Local page:
   Windows AI Foundry Dev Blog
2. Download the Foundry Local Installer (MSI or EXE).
3. Run the installer as Administrator.
4. Follow the prompts to complete installation.

🧪 Verify Installation

Open Command Prompt and run:

foundry --version

🤖 List Available Models

foundry model list

This will show models like:

• phi-3.5-mini
• phi-4
• mistral-7b
• qwen-2.5
• deepseek-r1

Challenge	Description	Solution
Hardware Limitations	Some models require significant memory or GPU/NPU support.	Use lightweight models like Phi-4 or quantized ONNX versions.
Model Compatibility	Not all models are optimized for local inference.	Stick to models officially supported by Foundry Local or convert models to ONNX format.
Latency Issues	Inference may be slow on older machines.	Use smaller models or optimize with ONNX Runtime and hardware acceleration.
Limited Documentation	Foundry Local is relatively new, so community support is still growing.	Refer to the official Foundry blog and GitHub issues for guidance.
Integration Complexity	Integrating AI into existing apps can be tricky.	Use SDKs and sample code provided by Microsoft to speed up development.

📈 Use Cases for Local POCs

• Customer Support Bots
• Offline Educational Tools
• Secure Enterprise Assistants
• Healthcare Decision Support (with local data)

To run Windows AI Foundry (Foundry Local) effectively on your Tata Communications machine, here are the minimum and recommended hardware requirements for CPU, GPU, and NPU:

✅ Minimum Requirements

These are sufficient for basic model inference (e.g., small models like Phi-3.5-mini):

• Operating System: Windows 10 (x64), Windows 11 (x64/ARM), or Windows Server 2025
• CPU: Any modern x64 processor (Intel i5/Ryzen 5 or better)
• RAM: 8 GB
• Disk Space: 3 GB free
• Acceleration (Optional): None required—CPU-only inference is supported 
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🌟 Recommended Requirements

For smoother performance and support for larger models:

• CPU: Intel i7/Ryzen 7 or better
• RAM: 16 GB or more
• Disk Space: 15–20 GB free (for model caching)
• GPU:
  • NVIDIA: RTX 2000 series or newer
  • AMD: Radeon 6000 series or newer
• NPU:
  • Qualcomm Snapdragon X Elite (with 8 GB or more VRAM)
  • Apple Silicon (for macOS users)

Foundry Local automatically detects your hardware and downloads the most optimized model variant (CPU, GPU, or NPU) accordingly

🧩 Conclusion

Windows AI Foundry’s local capabilities make it easier than ever to build powerful, privacy-preserving AI applications without cloud dependencies. By understanding the setup process and proactively addressing common challenges, developers can rapidly prototype and deploy intelligent solutions on Windows devices.

https://github.com/microsoft/Foundry-Local/blob/main/docs/README.md

https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-local/get-started

Link: Get started with Azure AI Foundry

https://learn.microsoft.com/en-us/azure/ai-foundry/quickstarts/get-started-code?tabs=azure-ai-foundry&pivots=fdp-project

Monitoring CrowdStrike Falcon Sensor on Linux and Windows Servers

 CrowdStrike Falcon is a leading endpoint protection solution used across enterprise environments to detect and respond to threats in real time. Ensuring that the Falcon Sensor is active and functioning on both Linux and Windows servers is essential for maintaining a secure infrastructure.

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Why Sensor Monitoring Matters

The Falcon Sensor is the agent that communicates with CrowdStrike’s cloud-based platform. If the sensor is inactive, misconfigured, or not installed, the server may be exposed to threats and lack visibility in the CrowdStrike dashboard.

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Checking Sensor Status on Linux Servers

Method 1: Using Falcon Control Tool

CrowdStrike provides a command-line utility called falconctl:

sudo /opt/CrowdStrike/falconctl -g --status

his command displays the sensor’s configuration and operational status, including registration and connectivity.

Method 2: Using systemd

sudo systemctl status falcon-sensor

Expected output:

● falcon-sensor.service - CrowdStrike Falcon Sensor
   Loaded: loaded (/etc/systemd/system/falcon-sensor.service; enabled)
   Active: active (running) since ...

To start or enable the service:

sudo systemctl start falcon-sensor

sudo systemctl enable falcon-sensor

Checking Sensor Status on Windows Servers

Method 1: Using PowerShell

Run the following command:

Get-Service -Name CSFalconSensor

Expected output:

Status   Name               DisplayName
------   ----               -----------
Running  CSFalconSensor     CrowdStrike Falcon Sensor

Method 2: Listing All Services

If the above command throws an error, list all services and search manually:

Get-Service

Look for:

Running  CSFalconSensor     CrowdStrike Falcon Sensor

If the service is not running, you can start it with:

Start-Service -Name CSFalconSensor

Troubleshooting Tips

• Sensor Not Found: Ensure the sensor is installed in the correct directory (/opt/CrowdStrike/ on Linux or listed in services on Windows).
• Service Fails to Start: Check logs (journalctl -u falcon-sensor on Linux or Event Viewer on Windows).
• Connectivity Issues: Use falconctl or check CrowdStrike dashboard for registration status.

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Conclusion

Regular monitoring of the CrowdStrike Falcon Sensor across both Linux and Windows servers is a vital part of maintaining endpoint security. These simple checks help ensure that your systems are protected and visible in the CrowdStrike console.

🗂️ Migrating Files from SharePoint Online to OneDrive: Methods, Challenges & Solutions

Migrating files from SharePoint Online to OneDrive for Business is a common task for IT teams aiming to streamline collaboration, reorganize data, or decommission legacy sites. While the process can be straightforward with the right tools, it also presents several challenges that require careful planning and execution.

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🚚 Migration Methods

1. SharePoint Migration Tool (SPMT)

• Best for: Structured, bulk migrations.
• Pros: Retains metadata, supports folder/site-level migration, provides logs.
• Cons: Requires setup and may need scripting for complex scenarios.

2. OneDrive Sync App

• Best for: Small-scale or manual migrations.
• Pros: Easy to use, no special setup.
• Cons: Not scalable, no metadata retention.

3. PowerShell Automation

• Best for: Custom, automated migrations.
• Pros: Highly flexible, supports scripting and scheduling.
• Cons: Requires technical expertise.

4. Manual Download & Upload

• Best for: Very small migrations.
• Pros: Simple and direct.
• Cons: Time-consuming, risk of data loss.

5. Third-Party Tools

• Best for: Enterprise-grade migrations.
• Pros: Advanced features, granular control, support for hybrid environments.
• Cons: Licensing costs, learning curve.

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⚠️ Common Challenges & ✅ Solutions

🔄 Challenge 1: Volume of Data (e.g., 1TB+)

• Problem: Large migrations can be slow and error prone.
• Solution: Use SPMT or third-party tools with throttling and retry mechanisms. Break migration into department-wise batches.

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🧩 Challenge 2: Folder Structure Preservation

• Problem: Losing hierarchy during migration can confuse users.
• Solution: Pre-create folder structures in OneDrive using PowerShell or manually. Map SharePoint folders to OneDrive destinations in SPMT.

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🔐 Challenge 3: Permissions and Access

• Problem: OneDrive is personal; SharePoint is collaborative.
• Solution: Use shared folders or Microsoft 365 Groups. Post-migration, assign access manually or via scripts.

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📄 Challenge 4: Metadata Loss

• Problem: Manual methods don’t retain metadata (created by, modified date, etc.).
• Solution: Use SPMT or third-party tools that preserve metadata during migration.

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🧪 Challenge 5: File Integrity Verification

• Problem: Files may be corrupted or incomplete.
• Solution: Use SPMT logs, checksum tools, or spot-check files. Maintain a migration checklist.

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👥 Challenge 6: User Confusion Post-Migration

• Problem: Users may not know where files are or how to share them.
• Solution: Conduct training sessions, provide documentation, and set up support channels.

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🗑️ Challenge 7: Decommissioning Old SharePoint Sites

• Problem: Risk of deleting active or needed content.
• Solution: Archive sites before deletion. Confirm with stakeholders and maintain backups.

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✅ Post-Migration Checklist

• 🔍 Verify file integrity and completeness.
• 🔐 Review and assign permissions.
• 📘 Train users on OneDrive usage and sharing.
• 🗑️ Archive or decommission old SharePoint sites.

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📌 Final Thoughts

Migrating from SharePoint to OneDrive is more than just moving files—it’s about ensuring continuity, usability, and security. By understanding the challenges and applying the right solutions, organizations can achieve a smooth transition that empowers users and improves collaboration.