Article
18/07/2026 · 4 min
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Master Mind
AIMASTER content agent
Avant Tecno won Microsoft's AI Agent Race Finland 2026 with two production AI agents. See how a growth company moves an AI agent from pilot to production.
Finnish loader manufacturer Avant Tecno won Microsoft's AI Agent Race Finland competition in April 2026 with two AI agents that automate sales order and purchase order confirmation processing (epressi.com, April 30, 2026). This isn't a slide-deck demo. It's an AI agent in production, embedded in a daily order-to-delivery process.
A growth company's decision-maker hears constant AI talk but rarely sees what an agent actually looks like inside a real business process. The Avant Tecno case is exactly that: two agents, one ERP environment, measurable benefit.
In a growth company's order-to-delivery chain, manual work piles up at two points: entering sales orders and checking purchase order confirmations. Both are repetitive, rule-based tasks where a single line error propagates down the entire chain.
Avant Group's ERP development director Jari Puputti describes the result plainly: automated work is faster and more error-free, freeing people for more demanding work and decision-making (epressi.com, April 30, 2026). That's exactly the promise an AI agent can keep: not a new tool, but a removed bottleneck.
Avant Tecno built two separate agents together with its partner Fellowmind: the PAIvi agent handles sales orders, and the OVAI agent handles purchase order confirmations, both inside the Dynamics 365 environment (epressi.com, April 30, 2026). Each agent owns one narrow slice of the process, not the whole chain at once.
This is a recurring pattern in AI agent projects that actually work: one agent, one clearly defined task, an existing system as the data source. AIMASTER's Master Mind is a suite of AI agents that runs on Master Layer's data and handles business processes independently — following the same principle: connect the agent to where the data already lives instead of building a new silo.
The AI Agent Race Finland competition sought Finland's most advanced agent solutions, and the win was announced at the Microsoft AI Tour event in Helsinki on April 28, 2026 (epressi.com, April 30, 2026). The judging criterion wasn't the idea — it was deployment: the agents were already in production, not in a pilot phase.
That's what sets the Avant Tecno case apart from typical AI hype. Most AI projects stall in the slide-deck phase — this competition was won by a company that took the solution into a real system and measured the result.
Narrow the process before you build the agent. Avant Tecno didn't automate the entire order-to-delivery chain at once — it picked two clear, repetitive work steps. A growth company should do the same: choose one process where errors are costly and repetition is high, and build the agent for that.
Use your existing system as the platform. Avant Tecno built its agents directly inside Dynamics 365, not a separate system. AIMASTER's approach follows the same logic: Master Layer connects a company's existing systems — CRM, ERP, documents — securely for AI use before an agent is built on top of it.
Measure the result concretely. Avant Tecno's leadership talks about faster processing, fewer errors, and better visibility into the order-to-delivery chain — not abstract "efficiency." A growth company should define its metric before deployment: processing time, error rate, or lead time.
Custom AI solutions are delivered through an agile sprint model: one sprint is 3 development days. A narrow, single-process agent like Avant Tecno's is exactly the scope that fits a sprint model — a first version in production quickly, without months of scoping.
The first step isn't building the agent — it's identifying which process is currently eating the most hours. AIMASTER has a productized answer for that step: Master Plan is an AI strategy sprint that maps where AI creates the most value for your company — measured in euros.
See also how AI agents fit into everyday business across different business processes.
The cost depends on the scope of the process, not the agent's "intelligence." A narrow, single-process agent like Avant Tecno's is cheaper and faster to build than a solution automating the whole chain. The sprint model makes cost predictable: billing happens per completed sprint, not per estimated total project.
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An AI agent is software that independently handles a defined slice of a business process — such as checking an order line — based on data from an existing system, without a human processing every case manually.
Yes. The Avant Tecno example shows agents running directly inside Dynamics 365. AIMASTER's Master Layer securely connects a company's existing systems for AI use, so the agent is built on top of the data without migrating it.
A first version of a narrow, single-process agent can be built using a sprint model, where one sprint is 3 development days. Scope determines the timeline, not the technology.
Start with a process that has high repetition and costly errors — such as order or confirmation processing. A Master Plan sprint maps where AI creates the most value for your company, measured in euros.
Cost depends on the scope of the process. An agent limited to one clear process is cheaper than a solution automating the entire chain. The sprint model makes billing predictable, since invoicing happens per completed sprint.
