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Helping B2B marketplaces in Göteborg get more from AI

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I noticed Europages connects buyers and suppliers through search and quote requests — a model that's been running largely the same way for years across most B2B directories. That's not a criticism; it's just where most platforms in this space still are, and it means there's a real window to get ahead before AI becomes table stakes in B2B discovery. A few food industry clients we work with in the Göteborg region have started using lightweight AI tools to prioritize inbound leads and surface better-fit supplier matches — nothing dramatic, just structured first steps that compound quickly. I'd love to share what's working in a 15-minute call if that's worth your time.

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Quick question about how your team handles data today

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I tried to get a read on what Kompass is working on publicly, but your site didn't give me much to go on — so I'll be straight with you. Most B2B directory and data platforms we talk to in the food and logistics space are sitting on a lot of structured company data but haven't yet explored what AI tools could do with it — things like smarter segmentation, lead scoring, or surfacing patterns across industries. It's not about replacing your current workflow, just understanding where the low-hanging fruit might be. Would a 15-minute call make sense to swap notes on where you are with this?

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Your distributor scorecard is useful — here's what could make it sharper

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I noticed your site includes a hands-on scorecard and timeline calculator for evaluating B2B distributors in Sweden — that's a genuinely useful tool for buyers navigating a fragmented market. What caught my attention is that all of it appears to be manually maintained, which works until the volume of updates, new entrants, or user questions starts outpacing one person's bandwidth. There are some lightweight AI approaches — nothing exotic — that could help you flag when directory entries go stale or surface patterns in how visitors are using the comparison tools. I'd love to spend 15 minutes walking through what that could look like in practice, no pitch involved.

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Your Everstream case study caught my eye — quick question

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I noticed your case study on supplying data to Everstream Analytics for AI and machine learning model training — it's a smart positioning move, putting BoldData squarely in the infrastructure layer of other companies' AI workflows. That middle ground — enabling AI without being an AI company yourself — is exactly where I see teams start to hit friction: the data delivery side scales, but the internal processes around scoping, qualifying, and converting data buyers often don't keep pace. I work with B2B data and infrastructure companies in this phase to build clearer sales and partnership structures that match how buyers actually evaluate data vendors today. Would a 15-minute call next week be worth it to compare notes on where that friction tends to show up for teams like yours?

Subject:

Quick question about how your team handles AI today

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I came across ensun's list of top food manufacturing companies in Sweden and noticed the platform does a solid job aggregating supplier and producer data across the sector. That kind of structured industry intelligence is exactly where AI tools are starting to add real leverage — things like automating supplier qualification, flagging procurement gaps, or surfacing growth signals before a sales team even picks up the phone. Most food and logistics companies in the Göteborg region we speak with are still in early stages with this, which means the window to build a meaningful advantage is still open. Would a 15-minute call make sense to swap notes on where you're seeing the biggest operational bottlenecks?

Subject:

Helping Swedish food suppliers get more from their listings

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I noticed that B2BMAP organizes a solid directory of Swedish food and beverage suppliers, but the listings themselves seem to rely entirely on manual input and static profiles — no signals about which suppliers are trending, active, or ready to do business. A lot of B2B directories in this space are starting to explore how simple AI-assisted tools can surface better matches between buyers and suppliers, reducing the manual back-and-forth that slows deals down. Given that your platform connects producers and distributors across Sweden, even a basic layer of intelligent filtering or lead-scoring could make the directory meaningfully more valuable to both sides. I'd love to share a couple of concrete examples from similar platforms — would 15 minutes this week make sense?

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How Nouryon's AI pilots could connect across your operations

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I noticed Nouryon is running BeautyCreations™ as an AI-driven formulation tool — that's a meaningful step, and it's clear there's appetite internally to experiment with AI in specific workflows. What we often see at this stage is that individual pilots like that sit in isolation, without a clear structure for how learnings transfer to adjacent areas like supply chain, order management, or production planning. Given that MyNouryon already handles order tracking digitally, there's a logical thread worth pulling on — connecting those touchpoints into something more coordinated isn't as heavy a lift as it sounds. I'd be glad to share how a few food and specialty chemical companies in the Nordics have done exactly this — would a 15-minute call next week make sense?