This is the Apheris pitch deck to raise a $4.5m seed round in 2019.
About
Apheris AI was founded by Robin Rohm and Michael Höh with a shared dream to empower companies to run analytics on decentralized datasets. Michael developed software infrastructure for distributed data during his PhD at Forschungszentrum Julich and his time at BCG. Robin has a background in algebraic theories for data linkage and data privacy and has experienced the complexity of centralizing sensitive personal healthcare data firsthand in one of his previous start-ups.
Through their work, they encountered barriers that limit progress within data-driven industries: data is often stored in silos and most companies work in closed data ecosystems. Therefore, Apheris strives to connect the world’s data to extract better insights.
Patrick Pichette, the chair of Twitter’s board of directors and Google’s ex-CFO has backed deep tech startup Apheris in a $3 million seed funding round alongside other investors.
Founded in 2019, Apheris helps clients analyze data without risking privacy infractions. The free flow of internal data can be a minefield for private businesses, with large bulks of valuable information remaining unusable or unshareable due to privacy, compliance, legal or security concerns.
Apheris is a software-as-a-service company and CEO and cofounder Robin Rohm told Business Insider its pricing structure depended “on the use case and the data ecosystem that it’s empowered”.
“There are other companies that focus on federated machine learning to enable computing on static and structured data, but they do not enable a data scientist to do data science on third-party data,” he added.
“Apheris provides an interface to data scientists that allows them to do real R&D and data science while preserving data privacy and ownership.”
The firm said that less than one year after launch, it had worked with around seven clients, including “top pharmaceutical, chemical, telecommunication, and manufacturing companies.”
Seed investor LocalGlobe led the round alongside Dig Ventures and Pichette. Additional investors include another. VC, System.One, and angel investors Charles Songhurst, NaturalMotion founder Torsten Reil, and Songkick founder Ian Hogarth.
Funding Rounds
As of 2020, they raised a EUR2.5m round from LocalGlobe.
Pitch Deck Review Summary
Structured Summary Review
Words
Generally, they have a solid use of words.
Slide length
The deck is on the short end at 11 slides. They don’t cover everything that they need to.
Headers
They write their headers better than pretty much all the decks you will see.
Appearance
It’s a solid, functional deck. Like it. I don’t like fancy decks.
Narrative
I wouldn’t say that there is a particularly strong narrative but the deck works well.
Structure
Pretty much all the slides are structured quite well.
Slides
I feel like they have only covered the story part of the deck and there is nothing about the execution section. There’s pretty much nothing on the product, how they make money, traction, market size, go to market etc…
Slide by Slide Review
The logo is too large. You want to lean back a little to look at it.
I like simple words and sentences. What they write in the blue box may be correct, but it’s a mouthful. What are privacy-preserving data ecosystems?
The slide is structured very well but there are a few too many elements.
The text under who we are, what, why is a little too small.
The who we are text is blah. I hate superlatives such as “stunning early traction”. Let me decide that for myself.
To be honest, I don’t like exec summary slides as they are hard to do well. In your pitch deck you should be able to cover all these points, so why reiterate them on the cover? It’s just not needed.
I would just start out with what I call a “one-liner” slide and explain what it is you do in simple English. Decks aren’t meant to be that long so all these exec points should be covered soon.
Ok cool, they use the headers well. I can’t stand it when people write “The Problem”.
6 points is too much. There’s too much on the slide. You do not need to be completely exhaustive in a deck. You just need to say enough to capture attention. You can talk about details when investors ask (if they ask).
Don’t write text vertically (Exemplary AI use cases). Turning your head is not a good look.
The text is generally just a smidge too small. They do get to the point and pretty much every bullet is only two words (that is amazing btw!). I would add 6/12 points space after paragraph to separate the bullets, but that’s a small point.
It’s a funny thing, you can tell really early on if a deck is going to be good or garbage.
The text in the blue on the right isn’t needed. It’s written in the header.
The chart needs to be explained more simply. It’s clear that they screenshot the image. If you can, I would format it natively and make it larger along the horizontal. Sometimes you can do that – this would be a lot of effort.
They could have explained how people struggle without data. I just feel something is missing on the slide.
I know a bit about the AI space, so I have a bet on what they are doing or trying to enable. I worked on setting up an AI company like this 5 years ago.
This slide is good, but it is not how I would go about explaining it. They’re doing a solid job though.
This is the crux of it. Numerai built a hedge fund on this principle. Wait maybe I am wrong. I am not sure that they are encrypting the data.
This is a good slide but I still don’t quite understand the details, which is probably all you need to do actually.
The first thing I noticed is the bottom copy is a bit too small.
This has the foundation for a good slide, I would like to see some more examples though. Who did they sign contracts with?
Ergh, world-class AI wonks are not cheap. They are raising 2m and that is not going to go too far!
I’m not a fan of this slide. It’s not terrible though. I don’t really like the timeline plopped on the bottom.
They are throwing around the word expert quite liberally.
Michael has some work experience, is Robin an academic, or did he just graduate?
Our team has learned from the best- learned? Dropping all the logos at the bottom is something a lot of people do on slides and it isn’t terrible, but it is a bit misleading. I mean, you have one old fogey on the team and he could have worked at 90% of those companies!
Don’t bother with these end slides. I do things in a different way.
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