Adastra

The same pattern shows up in almost every company experimenting with AI agents: At first, it works great – a few use cases, quick wins, real excitement. Then it grows. More agents. More connections. More automation. And suddenly… no one really knows what’s running, what depends on what, or who’s responsible for what. That’s the point where “smart automation” quietly turns into a mess because there’s no structure around it. Download our whitepaper to learn: – What AI agents can realistically do today – Why companies end up in an “agent zoo” – Where the biggest risks appear as agents scale – How to govern agents without slowing innovation – Real examples beyond theory – Why waiting is often the biggest risk 👉 https://lnkd.in/dGpZwmFK #AI #AgenticAI #AIGovernance #EnterpriseAI

Adastra is now a Databricks Gold Tier Partner. This recognition reflects our proven enterprise delivery, certified Databricks expertise, and measurable customer outcomes on the Databricks Data Intelligence Platform. For our clients, Gold tier means: • Faster, safer implementations • Reduced risk and accelerated time to value • Stronger alignment with Databricks on roadmap, support, and co-selling We’re excited to help more organizations modernize data platforms and operationalize AI with Databricks. Learn more: https://lnkd.in/ds6Rt5Mu . . . #Databricks #Adastra #GoldTierPartner #DataIntelligence #AI

NLB d.d. (the largest banking and financial group in Slovenia) was not experimenting with AI. They were already using it in real scenarios – processing large volumes of documents, supporting credit and compliance decisions, and helping employees act faster. The real question was: How to scale this safely in a banking environment? Because without a system in place: – teams start building agents on their own → shadow IT – approvals are inconsistent → compliance risk – agents multiply → inconsistent outputs – costs grow → no clear control Standard GenAI tools don’t solve this. They are built for usage, not for governance. What was necessary was a control layer above models and providers. So instead of scaling isolated use cases, we built a platform that standardizes how AI agents are designed, approved, and operated across the bank. At the core is Adastra #AGate, which provides visibility, control, and cost management across AI models and agents: - Every agent follows the same path from idea to production. - Access is tied to identity and approvals (Entra ID). - Every action is traceable and auditable. - Usage and costs are monitored, including rate limits and spend caps. ⏱️ Delivered in 5 months, including the first AI use case in production. 🏆 Result: 80% reduction in time and cost to implement AI use cases, with full auditability, traceability, and cost control. This is what it takes to scale AI in a regulated environment. Full story: https://lnkd.in/d5m63WBz #nlb #agenticAI #successstory #usecase #AIagent #fintech #banking

What started as a project at an AI hackathon in Prague last year has now earned a European award 🏆 Team AOS from Prague has now been named one of the global winners of DigiEduHack 2025, receiving the Experienced Award. DigiEduHack is a European Commission initiative focused on innovation in education. Standing out among nearly 800 solutions from 31 countries, the team’s success highlights how international collaboration combined with strong local talent can drive meaningful innovation in education. Their platform, EduVhled Engine, turns internal school documents and feedback into clear insights, helping reduce administrative workload and support better decision-making. The project began as a 24-hour challenge during the AI Days hackathon at 42 Prague and was later recognized at the European level. The team will officially receive the award in Brussels in June. Adastra supported the Prague DigiEduHack hackathon as a partner, with Daniel Urbanek, Michaela Nová, Roman Liebich and Lukáš Žatečka contributing as mentors, jury members, and active contributors. We are proud to have contributed to this initiative. 👉 Read more in the official announcement: https://lnkd.in/dq25Vq7T #AI #Education #DigiEduHack #Data We Are Adastra CZ

AI voice agent that can handle difficult calls as well as a human—while having instant access to all data and never “losing its nerve.” This is one of the real use cases from the logistics company DHL. In the new podcast episode, Jan Vacek talks about: – how to set up an AI strategy in a large organization – why security matters more than speed – and how to prevent AI from turning into an uncontrolled “agent zoo” 👉 Listen to the full interview here: https://lnkd.in/dtm9tV_u #ADASTRApodcast #logistics #agenticAI

We’ve been officially recognized by Microsoft for our expertise in Chat with Your Data in a Day. 🏆 This recognition validates our ability to help organizations: • Build employees a secure AI copilot that can answer questions in natural language using their own documents, policies, and data • Connect disparate data sources into one unified, conversational experience • Deploy AI inside their existing Microsoft 365 and Azure environment, aligned with their security, governance, and compliance requirements If you’re exploring how to put a real, Microsoft-backed copilot on top of your data, contact Adastra to discuss what this could look like in your environment. . . . #Adastra #MicrosoftPartner #AzureOpenAI #ChatWithYourData #Copilot #EnterpriseAI

Most organizations now have an “AI mandate.” Far fewer have AI in production delivering real business value. In a recent Register webinar, Breakthru Beverage Group (a $10B distributor), AWS and Adastra shared how they are moving from AI hype and pilots to concrete use cases that impact revenue, efficiency and risk. Our core lessons: • Why “we need to do AI” is not a strategy • How Breakthru moved from “spaghetti” systems to a 3-layer AI stack • Why they started with an AI summit, not a model • The scrappy first use cases they chose (and why) • How they measure success beyond “we ran a POC” If you are serious about getting AI out of pilot mode and into production, that first wave of use cases matters more than the next fifty. Contact us to get started. . . . AWS for Retail and Consumer Goods #ArtificialIntelligence #GenerativeAI #DataAnalytics #CloudComputing

From hours to seconds: how Tornatech is transforming access to business‑critical data with AI When employees can’t easily access the information they need, even simple questions can slow down processes. That’s the challenge Tornatech set out to solve. Together, we built a smart assistant using #AmazonBedrock that lets teams ask everyday questions in plain language and get quick, accurate answers from their business systems. Searching for data like inventory levels, work order status, pricing, invoices, and internal documents are now available in seconds, without having to wait on IT or search across multiple tools. The impact has been meaningful: ● Faster decisions ● Quicker customer responses ● Less time spent tracking down information Even better, this solution is helping teams rethink how AI can support their day-to-day work. As Tornatech’s IT Director put it, the real impact goes beyond time savings: it’s inspiring new ways to think about how AI can transform everyday work. 👉 Read the full success story: https://lnkd.in/dyHk4Eb2 #CustomerSuccess #Manufacturing #Chatbot

In many organizations, important choices still rely heavily on intuition and incomplete information. By using data and AI more effectively, you can: • Get a clearer view of what is really happening • Understand risks and opportunities sooner • Support decisions with evidence, not just opinion The real opportunity is to let data and AI handle complexity so people can focus on the conversations, decisions, and ideas that move the organization forward. . . . #HappyEaster #Easter2026 #DataandAI #DecisionMaking #DataInsights

We are proud to reveal our new IntuitionIQ™ Forecasting Engine. ⭐ It forecasts off vibes, opinions, and last year’s slide deck. Launching this April 31, 2026. … If only it were that easy. Behind every “overnight” AI success story is months (or years) of collecting, cleaning, and actually understanding the data. On April 1, we can joke about vibe-based forecasting. On April 2, it’s back to making sure our models are built on something much more solid. . . . #AprilFools #AIForecasting #AIReadyData #DataGovernance #AIGovernance