Avaelgo

We're co-organizing Microsoft Build //localhost Encore in Timișoara, together with ABQ.institute - and our GM, Mihai Tataran, is one of the speakers.

Mihai founded Avaelgo in 2006, right after graduating, and has spent the two decades since at the intersection of cloud infrastructure, enterprise AI, and Microsoft technologies. He holds Microsoft Regional Director status, a title held by fewer than 200 people worldwide, alongside his MVP status on Azure and AI.

At FABER, he's leading a deep-dive technical session on multi-agent systems and the agent harness in Microsoft Foundry.

📍 FABER, Timișoara
📅 Tuesday, 30 September 2026 - doors open at 15:30
🎟️ Register (free): https://lu.ma/abq-17j9

See you there! 🤝

Interest in AI isn't the problem anymore, but deciding what to do with it.

At DevTalks Romania 2026, our AI Business Consultant Radu Stefan takes the Main Stage in Cluj to explain this problem in detail.

His keynote, "AI Is Not Failing at the Model. It's Failing at the Decision Layer," breaks down the five decisions organizations need to get right before AI moves from individual productivity gains to tangible business value.

We see this pattern with almost every organization we work with: the models keep improving, the tools keep multiplying, and the impact still lags. That gap is not technical; it sits in how decisions get made.

See you at the Main Stage of DevTalks Romania 2026!

🗓️ September 24
📍 Cluj Innovation Park
🎟️ Get your ticket: https://bit.ly/4gNXxqo

Save your free spot at the link in the first comment 👇

Mihai Tataran spends most of his working hours helping leadership teams across CEE figure out where AI investment pays off, as opposed to where it looks impressive in a demo and quietly underperforms once it's live.

On 20 August, he's running Microsoft 365 Copilot and custom AI agents in realistic enterprise scenarios, and bringing the same value-versus-feasibility framework he uses in board conversations to a public session, so you can see where your own organization sits on the adoption curve.

As a Microsoft MVP and General Manager at Avaelgo, Mihai will help us understand what AI can realistically deliver in 2026, free and live, on 20 August, starting at 11:00 AM EEST.

Register now at the link in the first comment 👇

See you on 20 August!
Free registration at the link in the first comment 👇

Almost every enterprise AI conversation we sit in on eventually lands on the same question: Microsoft 365 Copilot, Azure AI Foundry, or a custom sovereign-by-design build, and which one fits best.

There's no universal answer, and we tell clients that directly rather than steering them toward whichever option is easiest to sell. It depends on what you're solving, how sensitive the data is, and how much control you need over where it lives.

On 20 August, we walk through all three, in plain terms, the way we'd walk a client through it.

Join us! 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄 at the link in the comments 👇

Free registration at the link in the first comment 👇

We spend a lot of time telling clients that 𝗮 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝗮𝗻𝗱 𝗮𝗻 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗮𝗴𝗲𝗻𝘁 𝗱𝗼 𝗻𝗼𝘁 𝗰𝗮𝗿𝗿𝘆 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗿𝗶𝘀𝗸, even though most governance conversations still treat them as if they do.

One works alongside a person who approves every action, while the other plans and executes steps on its own. A difference that changes what oversight needs to look like well before it changes anything about what the technology can do.

On 20 August, Mihai Tataran and Petru Jucovschi walk through this distinction live, then apply it to a real use-case prioritisation exercise the way they'd run it with an actual board.

Free of charge | + open Q&A | 11:00 to 11:45 AM EEST

𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄 at the link in the comments 👇

Most AI investment conversations in leadership teams start in the wrong place.

𝗧𝗵𝗲𝘆 𝘀𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝘁𝗼𝗼𝗹 (its licensing cost, its feature set, what the vendor is promising) 𝗿𝗮𝘁𝗵𝗲𝗿 𝘁𝗵𝗮𝗻 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗶𝘁 𝗶𝘀 𝗺𝗲𝗮𝗻𝘁 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝙖𝙣𝙙 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗱𝗲𝗽𝗹𝗼𝘆𝗶𝗻𝗴 𝗮𝗻𝗱 𝗴𝗼𝘃𝗲𝗿𝗻𝗶𝗻𝗴 𝗶𝘁 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲.

The total cost of enterprise AI adoption is the subscription, plus the integration work, plus the governance infrastructure, plus the change management, plus the ongoing model oversight, plus the cost of getting it wrong in a regulated environment.

𝗧𝗵𝗲 𝗿𝗲𝘁𝘂𝗿𝗻 𝗶𝘀 𝗲𝗾𝘂𝗮𝗹𝗹𝘆 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁 𝘁𝗼 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗶𝗳 𝘆𝗼𝘂 𝗵𝗮𝘃𝗲𝗻'𝘁 𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂'𝗿𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝘀𝘁𝗮𝗿𝘁: efficiency gains that haven't been baselined, time savings that aren't connected to revenue or cost outcomes, pilots that succeed on their own terms but can't make the case for the budget to scale.

𝗧𝗵𝗲 𝗔𝗜 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝘀 𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝘀𝗲𝘀𝘀𝗶𝗼𝗻 𝗼𝗻 𝗔𝗜 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗳𝗿𝗮𝗺𝗶𝗻𝗴 that will help you understand how to define value before vendor selection, build a business case that holds under board scrutiny, and measure what matters.

Details and booking in the comments. 👇

Healthcare AI presents one of the most compelling cases in enterprise technology, and one of the most complex to govern.

𝗧𝗵𝗲 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆: diagnostic support that surfaces relevant patterns faster than manual review, administrative automation that returns time to clinical staff, patient routing that reduces wait times, research assistance that processes literature at a scale no team can match.

𝗔𝗻𝗱 𝘁𝗵𝗲 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀: patient data protection that goes well beyond standard GDPR, liability frameworks that are still being tested in most jurisdictions, and a regulatory environment where the cost of a governance failure is not a fine, but clinical and reputational.

𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝘁𝗲𝗮𝗺𝘀 𝗻𝗮𝘃𝗶𝗴𝗮𝘁𝗶𝗻𝗴 𝗔𝗜 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗻𝗲𝗲𝗱 𝗮 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝘁𝗵𝗮𝘁 𝘁𝗮𝗸𝗲𝘀 𝗯𝗼𝘁𝗵 𝘀𝗶𝗱𝗲𝘀 𝘀𝗲𝗿𝗶𝗼𝘂𝘀𝗹𝘆, resulting in a leadership position that holds both the technology and the compliance cases in productive tension.

𝗧𝗵𝗲 𝗔𝗜 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗶𝘀 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗮𝘀 𝗮 𝘀𝗲𝗰𝘁𝗼𝗿-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗳𝗼𝗿 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀, with pre-workshop calibration for your regulatory and operational context.

Find out more and book your free 1-on-1 in the comments. 👇