contentSlug

type

ContentSlug_ContentQuery

slug

ContentPageContentQuery

content

trendingContent

query ContentSlug_ContentQuery(
  $contentSlug: String!
  $type: [ContentType!]
) {
  ...ContentPageContentQuery_13QmVO
}

fragment CompanyDetails_Content on Content {
  __isContent: __typename
  companies {
    name
    description
    pageUrl
    id
  }
}

fragment ContentBasicInfo on Content {
  __isContent: __typename
  id
  type
  title
  lang
  companies {
    viewerIsFollowing
    id
    name
    pageUrl
  }
  tags {
    viewerIsFollowing
    id
    name
    pageUrl
  }
  ...PublishingDetails
  ...Reactions
}

fragment ContentMetadata on Content {
  __isContent: __typename
  type
  title
  lang
  pageUrl
  alternatePageUrls: translations {
    __typename
    pageUrl
    lang
  }
  imgUrl
  description
  ... on Video {
    liveTime
    videoUrl
  }
  ... on Webcast {
    liveTime
    videoUrl
  }
}

fragment ContentPageContentQuery_13QmVO on Query {
  content(slug: $contentSlug, type: $type) {
    __typename
    id
    type
    title
    isPremium
    lang
    htmlBody
    summary
    companies {
      forum {
        latestPosts {
          ...ForumPosts
        }
      }
      name
      id
      viewerIsFollowing
      pageUrl
      defaultInstrument {
        isin
        id
        marketOpen
        marketClose
        marketplace {
          region
        }
        returns {
          total
        }
      }
    }
    tags {
      viewerIsFollowing
      id
      name
      pageUrl
    }
    createdAt
    ... on Video {
      liveTime
    }
    ... on Webcast {
      liveTime
    }
    slug
    ... on CompanyReport {
      reportUrl
    }
    ... on ThirdPartyCompanyReport {
      reportUrl
    }
    ... on StockExchangeRelease {
      reportUrl
    }
    ...ContentBasicInfo
    ...ContentMetadata
    ...PriceAndRecommendation_Content
    ...CompanyDetails_Content
    ...ReportLink_Content
    ...KeyFigures_Content
  }
  ...TrendingContent_1jQ2Cn
}

fragment ForumPosts on ForumPost {
  text
  likesCount
  url
  author
  postedAt
  authorImgUrl
}

fragment KeyFigures_Content on Content {
  __isContent: __typename
  companies {
    defaultInstrument {
      estimateData {
        modelType
        reportingCurrency
      }
      snapshot {
        transaction {
          date
          actualized {
            year
            quarter
            revenue
            revenueGrowth
            ebitAdjusted
            ebitReported
            ebitda
            enterpriseValue
            epsAdjusted
            dividend
            dividendYield
            sharePrice
          }
          estimates {
            year
            quarter
            revenue
            revenueGrowth
            ebitAdjusted
            ebitReported
            ebitda
            enterpriseValue
            epsAdjusted
            dividend
            dividendYield
            sharePrice
          }
        }
      }
      id
    }
    id
  }
}

fragment PriceAndRecommendation_Content on Content {
  __isContent: __typename
  createdAt
  companies {
    name
    pageUrl
    defaultInstrument {
      priceData {
        tradeCurrency
      }
      snapshot {
        priceData {
          date
          lastPrice
          tradeCurrency
        }
        transaction {
          date
          recommendation
          targetPrice
        }
        prevTransaction {
          recommendation
        }
      }
      id
    }
    id
  }
}

fragment PublishingDetails on Content {
  __isContent: __typename
  createdAt
  publishers {
    name
    imgUrl
  }
  authors {
    __typename
    id
    name
    slug
    imgUrl
    jobTitle
  }
  ... on Video {
    liveTime
  }
  ... on Webcast {
    liveTime
  }
}

fragment Reactions on Content {
  __isContent: __typename
  id
  reactionGroups {
    reactionType
    reactionsCount
    viewerReacted
  }
}

fragment ReportLink_Content on Content {
  __isContent: __typename
  type
  isPremium
  ... on CompanyReport {
    reportUrl
  }
  ... on ThirdPartyCompanyReport {
    reportUrl
  }
  ... on StockExchangeRelease {
    reportUrl
  }
}

fragment TrendingContent_1jQ2Cn on Query {
  trendingContent(type: ARTICLE) {
    __typename
    id
    title
    lang
    pageUrl
    createdAt
    type
    imgUrl
    companies {
      squareLogoUrl
      name
      id
    }
    authors {
      __typename
      imgUrl
      id
    }
    publishers {
      imgUrl
    }
  }
}


__typename

title

isPremium

lang

htmlBody

summary

companies

createdAt

publishers

authors

reactionGroups

pageUrl

translations

imgUrl

description

Analyst

Juha Kinnunen

Mikael Rautanen

Revenio is a global provider of comprehensive eye care diagnostic solutions. The group offers fast, user-friendly, and reliable tools for diagnosing glaucoma, diabetic retinopathy, and macular degeneration (AMD). Revenio’s ophthalmic diagnostic solutions include intraocular pressure (IOP) measurement devices (tonometers), fundus imaging devices, and perimeters as well as software solutions under the iCare brand.

In 2023, the Group’s net sales totaled EUR 96.6 million, with an operating profit of EUR 26.3 million. Revenio Group Corporation is listed on Nasdaq Helsinki with the trading code REG1V.

It seems clear that AI will to a large extent replace all human diagnostics. Pattern recognition is not a particularly inherent skill for humans, and even before the transformer revolution, AI has outperformed humans by far in various diagnostic tasks. Even pigeons are on par with humans in diagnosing cancer from tissue samples:                   BBC News              Pigeons identify breast cancer 'as well as humans'    A study finds that pigeons, with training, can identify breast cancer in mammagrams just as accurately as human experts.                             The only obstacle (or perhaps rather a slowdown) to the realization of the hypothesis is the industry’s conservatism. It is telling that Revenio has had to weaken the sensitivity of disease diagnoses given by its AI devices because, compared to the gold standard comparison of 70-year-old legacy perimeters, Revenio’s devices identify “too many” diseases. (As the spouse of a diabetic, I personally think it would be nice if, for example, symptoms of retinopathy were identified from even the smallest signs as early as possible, but the FDA seems to think otherwise). As for those scenarios, it is very hard to believe that:  Scanners will become a commodity device like a blood pressure monitor. Tech giants are very interested in taking over a reasonably narrow AI domain. A potential AGI / ASI is unlikely to be optimal in healthcare if/when its operation cannot be easily understood or adjusted in the desired way. Domain-specific models will likely remain viable even in a possible AGI era.  I also believe that the regulated forced bundling of the device and the AI algorithm will remain the standard in the future. Thus, hardware and data create a moat for AI software. Regarding these image recognition AI algorithms, it is good to understand that they aren’t exactly “rocket science”. Based on public information, RetCAD’s algorithm is a very basic CNN (Convolutional Neural Network) solution that is taught to practically every computer science student during their undergraduate studies. So, in my book, this isn’t a moat except due to the aforementioned forced bundling and the resulting switching cost. Depending on how much data asset Revenio gains from this RetCAD ownership, the moat might indeed grow (this has not been disclosed). Summa summarum: I 100% agree with the hypothesis, but I don’t quite subscribe to the logical chains of events in these scenarios. However, I am definitely in favor of the optimistic scenario if we can eventually get rid of this Luddite attitude plaguing the industry.

I’ll tell you a true story. Life is funny. DONE = Revenio bought a company called Regio from Estonia because of its map positioning software. This is how Revenio got Estonian owners. By chance, back in the Soviet era in 1990, I had met the CEO of Regio. DONE famously bought Regio through a share swap, and a lock-up period prevented the Estonians from selling for 2 years. In the meantime, the share value dropped by over 90 percent. What did the former CEO of Regio do? He pulled a “crucian carp” (ruutana) and it paid off. Regio’s price took off, as you know. How I’m involved in this is that when this CEO and a good Estonian friend of mine, who both owned DONE, told me they owned Revenio, I also got interested in this “general store” (yeah—I mean, from milk processing lines to rubber boats). So I bought 100 euros worth of shares and went to the annual general meeting. Excellent catering—haven’t really experienced anything like it since 1994. Anyway, it turned out at the meeting that they had some kind of patent for intraocular pressure measurement. I got excited about it and immediately bought 5,000 euros worth of shares. Well, it took a while before the price started to react, after they had cleared out—what was it, up to 5 different side businesses? At this stage, I told my Estonian friends that this really is starting to be worth owning. Of course, I bought shares aggressively at various prices into three portfolios. The latest ones were probably around 8 euros. You know what happened. The price rose excellently from my initial purchase price of 1.45 euros. And since these Estonian friends of mine had received the shares “for free.” When the Covid euphoria faded. I realized myself that the price had gone too high. So I’m being honest—I missed the peak completely. I sold 95% of the shares at a price of 38-31 euros and all the time I was messaging my Estonian friends that this was it and they should sell. But these “crucian carps” (ruutanat) have stayed stuck in the “crucian carp” (ruutana) mindset that it will still rise back to 60 euros, since it previously rose from nearly zero to 70 euros. SIGH! It’s miserable trying to teach market economics to those born in the Soviet Union. They have lost huge amounts of euros by not believing my advice. I will sell my last Revenio shares in January with a good profit. So this “story” is probably coming to an end—what did we learn from it? At the peak, it’s hard to sell and you have to settle for some profit, and it’s not worth waiting for former peaks; instead, move on to new pastures. Happy New Year to everyone—meaning, off to new pastures.

In analyzing Revenio’s growth regarding the analysis of clinical findings, I believe a key factor is how effectively Revenio can lock in its device users to use only Revenio’s algorithms and software for analysis, rather than those of a competitor. In my opinion, the best way to lock users into this pipeline would be for Revenio to turn the software into a “one-stop shop”—where data from the diagnostic device goes directly into Revenio’s software, allowing both fundus images and perimetry results to be viewed in the same program. And why not OCT images later as well, if Revenio eventually expands into OCT devices. Just add tabs to the top bar of the software for viewing different diagnostic results. I, for one, would welcome the option of being able to do everything with a single software. No time is wasted waiting for another program to start when, for instance, you want to check the perimetry findings right after viewing an OCT.

I have been trying for a long time to form an understanding of the impact of the ongoing AI revolution on Revenio’s business in the long term. My investment hypothesis is that AI will enable the identification of systemic diseases from the fundus (eye ground) significantly more broadly than before. Eye scanning will become a procedure comparable to measuring blood pressure, used to monitor general health and diagnose numerous different diseases. Based on this hypothesis, I have drafted two scenarios for Revenio. Optimistic scenario Revenio’s moat in easy-to-use imaging devices deepens further as scans are needed extensively in healthcare and are performed mainly by personnel other than eye specialists. Regardless of which party has produced the AI, it is completely dependent on the high-quality data generated by Revenio. AI used in health technology is clinically validated and strictly regulated, which keeps general-purpose AIs at bay. AI development in general is moving in a direction where Big Tech’s AI models are not the best at everything; instead, specific winners emerge for different scientific fields. Pessimistic scenario AI develops so far that it can extract the data it needs even from lower-quality scans or images, and expensive measurement technology is no longer required. Big Tech AIs overtake Revenio’s algorithms and make better diagnoses from eye scans. Revenio’s own algorithms become worthless. Conclusions Personally, I emphasize the growth opportunities of the optimistic scenario and believe that health technology will remain strictly regulated in the future. However, I must admit that painting the pessimistic scenario felt frighteningly easy. I would be interested to hear thoughts from those more familiar with Revenio regarding my hypothesis and scenarios. Am I exaggerating the opportunities or the risks?

Hi @MolskisPabrai, I looked into this directly with Revenio, as one always has to be careful with these FDA interpretations. I received some sensible answers, which I’ve tried to put into “plain language” here without the fancier terms. Hopefully, I’ve understood the details correctly myself and haven’t oversimplified them too much. If I were to summarize, it’s a good thing, but not a silver bullet by any means. The company mentioned that it had already used this opportunity previously when obtaining marketing authorization for the IC200 tonometer’s new feature, Quick Measure. This was possible even before this new relaxation regarding the use of “real-world” data because the data was traceable (data collected in connection with a clinical trial). In the future, Revenio could use clinical data, for example, in connection with post-market surveillance or to demonstrate the effectiveness of HOME2 in the care pathway—or something similar. According to the company, this won’t necessarily have an impact on marketing authorizations. This is because data is primarily only collected from measurements, and the software doesn’t systematically collect data from, for example, corresponding GAT measurements or CCT. So, there needs to be a reference in the study, unless I misunderstood. The company could likely better utilize this relaxation, for example, in connection with the RedCad marketing authorization. However, this requires that care practices and device usage be consistent, for example, in the EU (cf. USA). We could strengthen our data and potential clinical evidence with device data already accumulated in the EU and other countries. The US vs. EU comparison won’t be easy here because, for example, disease classifications are different. Furthermore, the guidelines governing software and clinical validation remain in effect for that application. Additionally, the analysis must be reproducible and the origin of the data verifiable, even though the patient does not need to be identifiable. Demonstrating efficacy this way specifically might still not be realistic, but this will certainly be useful in demonstrating safety and usability, usage rates, and the like. FDA reviewers apparently also get more flexibility, as the announcement stated that discretion can be used on an “application by application” basis. However, some general guidance is forthcoming, after which a clearer policy on the matter will start to form. The company did not comment on the potential data of other companies or their lack thereof.

Inderes              Muutos F-Securen johtoryhmässä – Talousjohtaja vaihtuu - Inderes    Muutos F-Securen johtoryhmässä – Talousjohtaja vaihtuuF-Secure Oyj | Pörssitiedote | 18.12.2025 klo 9.00F-Securen talousjohtaja ja johtoryhmän jäsen Sari Somerkallio on päättänyt jättää F-Securen...                             Robin seems to be joining F-Secure

Jouni and Robin were a powerful duo. They inspired trust when you met them. It’s difficult to find a replacement, but let’s hope for the best.

Revenio Group

Revenio is known as the global beacon of tonometers but these days the company is a noteworthy challenger in more extensive ophthalmic health technology. Imaging tools (previous CenterVue) play...

<p>Revenio is known as the global beacon of tonometers but these days the company is a noteworthy challenger in more extensive ophthalmic health technology. Imaging tools (previous CenterVue) play an increasing role in future growth and HOME products, as well as software business offer longer term growth promises. Business is growing very profitably, the market has sound growth drivers, and the products have strong competitive advantages. In addition, the company has an excellent track record of its ability to create value with investments in product development, structural reorganization, and new long-term growth templates</p> 

	2020	21e	22e
Revenue	61.1	79.3	102.5
growth-%	23.4 %	29.9 %	29.2 %
EBIT (adj.)	19.2	27.2	37.1
EBIT-% (adj.)	31.4 %	34.3 %	36.2 %
EPS (adj.)	0.58	0.82	1.10
Dividend	0.32	0.40	0.55
Dividend %	0.6 %	1.8 %	2.4 %
P/E (adj.)	86.6	27.5	20.6
EV/EBITDA	61.5	21.3	15.0

Revenio: Not a one-trick pony

Key Estimate Figures08.06.2021

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