Microsoft Ignite 2025 SMB Session Recap
Over the past several months, I’ve spent hundreds of hours working directly with teams—from small startups to mid-market innovators—who share the same aspiration: “We want to use AI, but where do we start?”
This question comes up everywhere. It crosses industries, geographies, skill levels, and team sizes. And as developers, we often feel the pressure to “solve AI” end-to-end—model selection, prompt engineering, security, deployment pipelines, integration…. The list is long, and the learning curve can feel even longer.
But here’s what we’ve learned through our work in the SMB space and what we recently shared at Microsoft Ignite (Session OD1210).
The first mile of AI doesn’t have to be complex.
You don’t need an army of engineers, and you don’t need to start from scratch.
You just need the right path.
In our Ignite on-demand session with UnifyCloud, we demonstrated two fast, developer-friendly ways to get your first AI workload running on Azure—both grounded in real-world patterns we see every day.
Path 1: Build Quickly with Microsoft Foundry Templates
Microsoft Foundry gives developers pre-built, customizable templates that dramatically reduce setup time. In the session, I walked through how to deploy a fully functioning AI chatbot using:
- Azure AI Foundry
- GitHub (via the Azure Samples “Get Started with AI Chat” repo)
- Azure Cloudshell for deployment
- And zero specialized infra prep
With five lines of code and a few clicks, you can spin up a secure internal chatbot tailored for your business. Want responses scoped to your internal content? Want control over the model, costs, or safety filters? Want to plug in your own data sources like SharePoint, Blob Storage, or uploaded docs?
You can do all of that—easily and on your terms.
This “build fast” path is ideal for:
- Developers who want control and extensibility
- Teams validating AI use cases
- Scenarios where data governance matters
- Lightweight experimentation without heavy architecture upfront
And most importantly, you can scale it later.
Path 2: Buy a Production-Ready Solution from a Trusted Partner
Not every team wants to build.
Not every team has the time, the resources, or the desire to compose their own AI stack.
That’s why we showcased the “buy” path with UnifyCloud’s AI Factory, a Marketplace-listed solution that lets customers deploy mature AI capabilities directly into their Azure environment, complete with optional support, management, and best practices.
In the demo, UnifyCloud’s founder Vivek Bhatnagar walked through:
- How to navigate Microsoft Marketplace
- How to evaluate solution listings
- How to review pricing plans and support tiers
- How to deploy a partner-built AI app with just a few clicks
- How customers can accelerate their time to value without implementation overhead
This path is perfect when you want:
- A production-ready AI solution
- A supported, maintained experience
- Minimal engineering lift
- Faster time to outcome
Why Azure? Why Now?
During the session, we also outlined three reasons developers are choosing Azure for their first AI workloads:
1. Secure, governed, safe by design
Azure mitigates risk with always-on guardrails and built-in commitments to security, privacy, and policy-based control.
2. Built for production with a complete AI platform
From models to agents to tools and data integrations, Azure provides an enterprise-grade environment developers can trust.
3. Developer-first innovation with agentic DevOps
Azure puts developers at the center, integrating AI across the software development lifecycle to help teams build faster and smarter.
The Session: Build or Buy—Two Paths, One Goal
Whether you build using Azure AI Foundry or buy through Marketplace, the goal is the same:
Help teams get to their first AI solution quickly, confidently, and securely.
You don’t need a massive budget.
You don’t need deep ML experience.
You don’t need a full-time AI team.
What you need is a path that matches your skills, your constraints, and your timeline.
Watch the Full Ignite Session
You can watch the full session on-demand now also on YouTube:
OD1201 — “Unlock Your First AI Solution on Azure”
It includes:
- The full build and buy demos
- Partner perspectives
- Deployment walkthroughs
- And guidance you can take back to your teams today
If you want to explore the same build path we showed at Ignite:
➡️ Azure Samples – Get Started with AI Chat
https://github.com/Azure-Samples/get-started-with-ai-chat
Deploy it, customize it, attach your data sources, and extend it.
It’s a great starting point.
If you’re curious about the Marketplace path:
➡️ Search for “UnifyCloud AI Factory” on Microsoft Marketplace
You’ll see support offerings, solution details, and deployment instructions.
Closing Thought
The gap between wanting to adopt AI and actually running AI in production is shrinking fast. Azure makes it possible for teams, especially those without deep AI experience, to take meaningful steps today.
No perfect architecture required.
No million-dollar budget.
No wait for a future-state roadmap.
Just two practical paths:
Build quickly. Buy confidently. Start now.
If you have questions, ideas, or want to share what you’re building, feel free to reach out here in the Developer Community. I’d love to hear what you’re creating.
— Joshua Huang
Microsoft Azure
Microsoft