How to Pivot a Deep Tech Startup: When Technology Becomes Business

Plus recommendations for deep tech startups looking for investments.

Dima Shvets
Aug 7, 2020 · 11 min read

Tech founders will agree: there are always things that could be improved in a tech product. That part of the job—tweaking and messing with technology indefinitely—can be fun and challenging. Trying to find a market for your technology is also challenging, but not always fun.

The bottom line is this:

Eventually, a deep technology startup needs to start bringing in money, even if that means a hard pivot to business in contrast to concentrating on the technical side of things.

What is the pivot and what you can learn from it

The best definition of a pivot that I’ve found was offered by Kevin Chou (CEO of Kabam). He compared a startup to a house with four “pillars”:

  • Product
  • Market (customers and users)
  • Go-to-market strategy (how your audience finds out about you/products)
  • Business model

A pivot is a significant change in at least one of these pillars while supporting yourself on the remaining, solid ones.

This doesn’t necessarily have to be about changing your product. You can change the value proposition or pricing; you can turn the product into service (or vice versa) to follow a better idea or a newly discovered demand from paying customers.

In RefaceAI, we’ve faced serious challenges and changes in all our “pillars” but the “true” pivot point was in the go-to-market. Luckily, our team knows how to adapt to trends and has the full-stack tech stamina for fast optimization across various demand sectors.

Focus on the technology with a vision, not just on the technology

Technology doesn’t need to be very complex to have a vision. Sometimes concentrating on a simpler, single solution is a better idea. It’s essential to understand the mission behind what you’re doing or planning to do to get the support of investors and find business opportunities.

We started working with machine learning in 2011, long before the hype. In the beginning, the various incarnations of RefaceAI tried different things related to visual media (converting 2D to 3D, one of our weirdest moments being a visualization of Wikipedia fragments with the help of AI).

Back in 2011, Snapchat by Snap looked kind of creepy, but the founder had a vision and an understanding for it as for a platform for applying filters. And the new generation of users loves this technology.

Another example, Atlassian, successfully pivoted from a service company to a product company, creating and popularizing the task/issue tracking tools most of us use every day through the initial use of aggressive freemium distribution of their software products.

We have always been a technology-driven company, willing to create products based on generative adversarial networks (GANs — among well-known companies, only Snap and FaceApp use them) since the moment they were invented. We started with photo processing web interface, advanced to face-swap web app for static images, and — after further perfecting the underlying technology — “broke the Internet” with a viral REFACE (Doublicat at the moment of launching) face-swap mobile app for GIFs.


Our grand vision for our face-swapping technology spans beyond entertainment, to other industries. We work on a deep fake detection tool because we don’t want the technology itself — which we think is incredible — to be further misused and discredited by malicious uses (think fake political speeches or fake porn). This is our social responsibility, a part of our mission.

How to know when it’s time to pivot

We started our pivot by serving the needs and finding solutions for the entertainment industry. In the past, we worked with Hollywood post-production companies. At some point, they started asking about face-swapping tech to reduce the cost of their pipelines.

In the process, we learned about the existing limitations and realized that we could develop more progressive face-swapping technology and use it for better purposes. As a result, we created the first conditional and scalable state-of-art technology for face-swapping, applicable to many possible use cases.

But no matter how cool, it was still only technology and not a product ready to be sold. So I got down to work on the interaction between the product and the business customers. The feedback we received on each step helped us understand which industries would embrace our technology not just as a “vitaminizer” but as a game-changing killer feature.

This was a moment where our technology pivot started. Still, the pivot of the company as a whole began when we realized that with the change of the direction of the technology, we would have to change all the other “pillars” described by Kevin Chou to a certain extent.

We believe in the model of the future world, where you act as an independent solution and grow with your biggest markets and clients.

An example of such a strategy is ElasticSales, which pivoted after needing and building an internal sales team for themselves. They realized that other companies faced a similar need and pivoted, turning into B2B SaaS startup Our pivot to B2B is the ML B2B product Reface Studio (currently in the works).

Understand what investors are looking for

Big ambitious things usually require funding. That means that your grand vision needs to be appealing for — or at least understood — by investors. I’ve been on both sides of the barricade working in VC funds and investing in dozens of powerful tech startups.

Going over 10K+ projects while working in an investment fund allowed me to see a bigger picture of what the investors and venture funds are looking for and spot the common industry trends. Startup founders usually cannot gain such insight because they are too involved in their projects.

When measuring the potential of a tech startup, investors are very interested to know if your distribution system is reliant on some other external activities or devices (like travel, events, or complicated physical installation in our progressively remote-centered world). They want to know if the deep tech is autonomous, capable of generating various long-term recurring revenue streams. Startups capable of affirming the latter will win.

Another important thing I realized is how different VCs think compared to entrepreneurs.

An entrepreneur’s job is to have a vision and never give up.

In a place where these two approaches intersect, a unique critical outlook is born. Using this knowledge, I’ve formulated a list of my top 5 recommendations for deep tech startups looking for investments.

1. Build long-term trusting relations, be good and trustworthy. This is the underlying principle behind venture capitalism. As a VC, you often need to wear different hats, including those of an HR manager and a psychologist. I’ve brought such skills to the table when joining RefaceAI as a co-founder. Taking care of investor relations, business development, strategy, and B2B relations are just as important (or even more so) than developing your technology.

2. Remember that dealing with deep tech is hard. The deep tech market is not a mature one. The entrepreneurs who have grown their IT product or business from scratch don’t understand how hard it is to create a true ML product (in contrast to various other tech startups like email automation or basic marketplaces) while retaining your team.

3. Always have a plan B, plan C, and all other kinds of backup plans. The uniqueness and quality of your technology are crucial. However, the market and the investment landscape can change suddenly, and you need to be prepared to deal with that.

4. Non-technical expertise and skills are crucial (and can make or break your product). Don’t just concentrate on the technology itself; it doesn’t exist in a vacuum. You need to take care of the “human” and “marketing” side of things so often despised by the tech people, too.

5. Iterate fast and choose the right things to do while rejecting the wrong things. The main advantage that my VC experience gave me is that after seeing so many projects fail, the software in my internal neural network (a.k.a. “brain”) has learned to compute what is going and what is not going to work. You must learn to choose the right variants, move fast, and think through your opportunity cost.

Build an MVP and go live

Not all small startups need to become the next Apple, disrupt industries, or create new markets. Many tech startups never become public — but they create the initial underlying technology used by other companies to build upon. Alphabet Inc. has myriads of such companies in its investment portfolio. And that is OK.

But you won’t know if that’s your scenario and you won’t find your product-market fit while sitting behind closed doors, tweaking your tech, never launching.

Going live for a startup is not always accompanied by mass advertising campaigns with billboards on Times Square. But it still includes preparing the technology to the extent where it can be demonstrated to others for testing and evaluation. This doesn’t have to take 50 onsite engineers and two years of tireless crunch.

After a live launch and subsequent analysis of the results, it’s the by-product of the main technology that can become the new main focus as a result. Bringing us back to the matter of a successful pivot.

Consider Slack, basically a by-product of a game by Tiny Speck. After about a year after the launch of the Glitch game in 2011, it was killed off. And the messenger for the internal communications between the US and Canadian offices has grown into one of the current golden standards for business communication. Slack became a unicorn with an estimated worth of $2.8 billion the very next year after the official launch in 2015.

A task arising before a startup that wants to find (or test) a business niche is not to make the engineers come up with perfect technology. But it’s also essential to understand that an MVP still doesn’t mean “an unfinished” or a “bad” version of a future product, which “will (hopefully!) get better!”

I prefer to think of a good MVP as of a “minimum lovable product.”

At RefaceAI, we did several live launches, because, in contrast to IP-based technologies, the products that we launched ( and REFACE apps) actually have end-users. Both our public projects ( and were wildly successful. This realization gave us the push forward that we needed for working more actively in the direction of B2B because if end-users wanted to use our technology, companies who have their own end-users would want it, too.

From B2B to B2C

After finding that there was no stable demand for our technology, we realized that there was no clear understanding of it and how it could be integrated into other technologies. While aiming for the B2C go-to-market, we realized the need to start B2B partnerships first.

Previously, only big companies could afford to use deep fake and face swap for their multimedia products, spending a lot of money and effort on content creation and post-production. By simplifying it with machine learning, we created the technology 30x cheaper and 10k times faster than deepfake outsourcing.

We created Reface Studio as a part of our new go-to-market strategy.

Technology illustration

Now, we are finalizing the product and adapting our tech pipeline to markets that are actively growing or even just starting to develop.

Pivoting to large-scale B2B after coming up with a few successful B2C products is tricky.

Tips for pivoting a deep tech startup

Every startup is different, and every deep tech startup thinks it’s unique, but there are universal points for pivoting that have worked for us:

  1. When pivoting, concentrate on your strong points. Focusing on too many things at once will drag you down.
  2. Have faith in people (who are willing to stick it out with you). When developing a totally unique technology, people behind it are truly irreplaceable.
  3. Find one metric to improve upon at a time. Focus on one thing, improve, test against real users, repeat.
  4. Don’t cater to the ambivalent. Haters are less dangerous to your business because you know from the start that you don’t need to try to satisfy them. Users who “kinda like” your technology, but wouldn’t be “utterly devastated” if it disappears are not your target audience either. Find your passionate supporters, people who want to use you as their main thing. Listen to them, make them happy; they are what will help you succeed.
  5. Don’t polish your tech at the expense of your business. Instead of tweaking the backend forever and never launching, optimize the expenses and efforts in such a way that will enable you to respond to both technology and business opportunities when they arise.
  6. Think about things that could go wrong and make your decisions based on that. A healthy dose of pessimism can save your business. Several times.
  7. Don’t try to pivot a “dead horse.” For a successful pivot, you need to change your focus from what you thought was the main thing to something that started secondary, but what obviously can bring more value and is loved by the users. If the users hate everything about your product, consider switching to a different business idea.

Final thoughts

Pivot is neither a failure nor a silver bullet for magically saving a lousy business idea. It is about changing your focus to something that can bring better results and allow you to scale and grow over time. During the pivot, the “deep tech” element in your deep tech startup will most likely stay unchanged, while the rest of the “pillars” of your business will undergo drastic changes.

And there is nothing to be afraid of. According to statistics, you have a better chance of winning the business game of your startup if you pivot.

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Dima Shvets

Written by

co-founder Reface / tech investor

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