Author: azeeadmin

Now valued at $5.6 billion, zero-fee stock trading app and cryptocurrency exchange Robinhood is starting preparations to go public. Just a year and a half ago, it was still largely under the radar. But then it raised a $110 million Series C at a $1.3 billion valuation in April 2017 and then just a year later scoring a $363 million Series D, both led by Russian firm DST Global. Combined with the growth of its premium subscription for trading on margin called Robinhood Gold, the startup now has the firepower and revenue to make a viable Wall Street debut.

Today during Robinhood CEO Baiju Bhatt’s talk at TechCrunch Disrupt SF, he revealed that his company is on the path to an IPO and has begun its search for Chief Financial Officer. It’s also undergoing constant audits from the SEC, FINRA, and its security team to make sure everything is kosher and locked up tight.

The CFO hire could help the five-year-old Silicon Valley startup pitch itself as the cheaper youthful alternative to E*Trade and traditional stock brokers. They’d also have to convince potential investors that even though cryptocurrency prices are in a downturn, allowing people to trade them for cheaper than competitors like Coinbase is a powerful user acquisition funnel.

Robinhood now has 5 million customers tracking, buying, and selling stocks, options, ETFs, American depositary slips receipts of international companies, and cryptos like Bitcoin and Ethereum. That’s twice as many customers as its incumbent competitor E*Trade despite it having 4000 employees compared to Robinhood’s 250.

The startup has raised a total of $539 million to date from presitigious investors like Andreessen Horowitz, Kleiner Perkins, Sequoia, and Google’s Capital G, allowing it to rapidly role out products before its rivals can react. This rapid rise in valuation can go to some founders’ heads, or crush them under the pressure, but Bhatt cited “friendship” with his co-CEO Vlad Tenev as what keeps him sane.

The startup has three main monetization streams. First, it earns interest on money users keep in their Robinhood account. Second, it sells order flow to stock exchanges who want more liquidity for their traders. And it sells Robinhood Gold subscriptions which range from $10 per month for $2000 in extra buying power to $200 per month for $50,000 in margin trading, with a 5 percent APR charged for borrowing over that. Gold was growing its subscriber count at 17 percent per month earlier this year, showing the potential of giving trades away for free and then charging for extra services.

But Robinhood is also encountering renewed competition as both startups and incumbents wise-up. European banking app Revolut is building a commission free stock trading, and Y Combinator startup Titan just launched its app that lets you buy into a  managed portfolio of top stocks. Finance giant JP Morgan now gives customers 100 free trades in hopes of not being undercut by Robinhood.

Over on the crypto side, Coinbase continues to grow in popularity despite its 1.4 percent to 4 percent fees on trades. It’s rapidly expanding its product offering and the two fintech startups are destined to keep clashing. Robinhood may also be suffering from the crypto downturn, which is likely dissuading the mainstream public from dumping cash into tokens after seeing people lose fortunes as Bitcoin and Ethereum’s prices tumbled this year.

There’s also the persistent risk of a security breach that could tank Robinhood’s brand. Meanwhile, the startup uses both human and third-party software-based systems to moderate its crypto chat rooms to make sure pump and dump schemes aren’t running rampant. Bhatt says he’s proud of making cryptocurrency more accessible, though he didn’t say he felt reponsible for prices plummeting which could mean many of Robinhood Crypto’s users have lost money.

Fundamentally, Robinhood is using software to make the common but expensive behavior of stock trading much cheaper and more accessible to a wider audience. Traditional banks and brokers have big costs for offices and branches, trading execs, and TV commercials. Robinhood has managed to replace much of that with a lean engineering team and viral app that grows itself. Once it finds its CFO, that could give it an efficiency and growth rate that has Wall Street seeing green.

Alex Stamos has been at the helm of some of the world’s most powerful companies for the past half-decade and is widely regarded as one of the smartest people working in the security space.

Now, just a month into his new gig as an academic, he can look back at his time with a dose of brutal honesty.

“It’s kinda a crappy job to be a chief security officer,” said Stamos, Facebook’s former security chief, in an interview with TechCrunch at Disrupt SF on Thursday.

“It’s like being a [chief financial officer] before accounting was invented,” he said.

“When you decide to take on the [chief security officer] title, you decide that you’re going to run the risk of having decisions made above you or issues created by tens of thousands of people making decisions that will be stapled to your resume,” he said.

Stamos, who recently joined Stanford University after three years as Facebook’s security chief. Before then, he was Yahoo’s chief information security officer for less than a year before he departed the company, reportedly in conflict with then-Yahoo chief executive Marissa Meyer over the company’s complicity with a secret government surveillance program.

His name is synonymous to many as a fierce defender of user security and rights, but he was at the helm when both his former employers were hit by security scandals. Yahoo had a a three billion user data breach, and Facebook with the Cambridge Analytica voter profiling incident. Although inherited, he said it wasn’t going to “shirk” the blame.

“I was the CSO when all this stuff happened — it was my responsibility,” he said.

“I also hope I was able to make things better,” he said. “If you’re making individual decisions that you believe are ethical and moral that are pushing the ball in the right direction, in the end if things are imperfect, you have to live with yourself and continue to do good things.”

He said most companies have to navigate security, but also privacy and misuse of their products.

Stamos admits that while he came from a “traditional CSO” background, he quickly learned that the the vast majority of harm caused by technology “does not have any interesting technical component.”

Speaking to disinformation, child abuse, and harassment, he said that it’s the “technically correct use of the things we build that cause harm.”

He said that the industry needs to vastly expand how companies deal with issues that encompass but don’t fall within the strict realm of cybersecurity. “There’s not really a field around it,” he said, talking to the need to redefine “cybersecurity” to also include issues of trust, safety, and privacy — three things that are important for companies are working to ensure, but don’t necessarily fit into the traditional security model.

“There’s not a tech company starting up right now that is not going to have to worry about these trust, safety and privacy issues,” he said. “And hopefully we can take some of those lessons and spread them out a bit more.”

“I’ve learned a lot of things from the failures I’ve seen up close and I want other people to learn about them,” he said. That, he said, is one of the things he wants to help teach at Stanford, where he’s likely to stay for some time.

Asked if he would ever go back to a previous role as a chief security officer, “not for quite a long time,” he said.

Alex Stamos has been at the helm of some of the world’s most powerful companies for the past half-decade and is widely regarded as one of the smartest people working in the security space.

Now, just a month into his new gig as an academic, he can look back at his time with a dose of brutal honesty.

“It’s kinda a crappy job to be a chief security officer,” said Stamos, Facebook’s former security chief, in an interview with TechCrunch at Disrupt SF on Thursday.

“It’s like being a [chief financial officer] before accounting was invented,” he said.

“When you decide to take on the [chief security officer] title, you decide that you’re going to run the risk of having decisions made above you or issues created by tens of thousands of people making decisions that will be stapled to your resume,” he said.

Stamos, who recently joined Stanford University after three years as Facebook’s security chief. Before then, he was Yahoo’s chief information security officer for less than a year before he departed the company, reportedly in conflict with then-Yahoo chief executive Marissa Meyer over the company’s complicity with a secret government surveillance program.

His name is synonymous to many as a fierce defender of user security and rights, but he was at the helm when both his former employers were hit by security scandals. Yahoo had a a three billion user data breach, and Facebook with the Cambridge Analytica voter profiling incident. Although inherited, he said it wasn’t going to “shirk” the blame.

“I was the CSO when all this stuff happened — it was my responsibility,” he said.

“I also hope I was able to make things better,” he said. “If you’re making individual decisions that you believe are ethical and moral that are pushing the ball in the right direction, in the end if things are imperfect, you have to live with yourself and continue to do good things.”

He said most companies have to navigate security, but also privacy and misuse of their products.

Stamos admits that while he came from a “traditional CSO” background, he quickly learned that the the vast majority of harm caused by technology “does not have any interesting technical component.”

Speaking to disinformation, child abuse, and harassment, he said that it’s the “technically correct use of the things we build that cause harm.”

He said that the industry needs to vastly expand how companies deal with issues that encompass but don’t fall within the strict realm of cybersecurity. “There’s not really a field around it,” he said, talking to the need to redefine “cybersecurity” to also include issues of trust, safety, and privacy — three things that are important for companies are working to ensure, but don’t necessarily fit into the traditional security model.

“There’s not a tech company starting up right now that is not going to have to worry about these trust, safety and privacy issues,” he said. “And hopefully we can take some of those lessons and spread them out a bit more.”

“I’ve learned a lot of things from the failures I’ve seen up close and I want other people to learn about them,” he said. That, he said, is one of the things he wants to help teach at Stanford, where he’s likely to stay for some time.

Asked if he would ever go back to a previous role as a chief security officer, “not for quite a long time,” he said.

Marijuana may still be on shaky legal ground, but the therapeutic benefits of the psychoactive molecules — cannabinoids — inside the plant are solidly established. Unfortunately, cultivation of that plant is resource-intensive and yields only tiny amounts of some useful medicines. CB Therapeutics, a new biotech company launching today at the Disrupt SF Startup Battlefield, aims to change the game with cannabinoids produced cleanly and cheaply in the lab — out of sugar.

Co-founder and CEO Sher Ali Butt says the idea struck him when he was working at cannabis testing lab Steep Hill. CBD, a compound found in the plant but in much lower concentrations than THC, the primary intoxicant, was producing extremely helpful pain and anxiety alleviation for some people without a high. The medicinal possibilities were obvious, but high-CBD strains of cannabis are not only uncommon, but a pain to cultivate and process for that purpose.

“CBD had all these applications, and I just thought that there’s got to be a better way to do this. The idea just stuck in my brain,” he told me.

After working on the problem on and off for years he decided to pursue it in earnest. Serendipitously, around this time he ran into Jacob Vogan, an old friend from college who was working in the field of bioengineering. It seemed like a natural fit to them to start the company together.

What CB Therapeutics has done is bioengineer microorganisms — specifically yeast — to manufacture cannabinoids out of plain-old sugars. This type of bioreactor isn’t a new idea; yeast and other organisms are used to create and isolate lots of drugs and substances.

“The vitamin C that we take in tablets, for instance — they didn’t squeeze oranges and lemons to get that,” Butt points out. “There isn’t enough agriculture to supply the global demand. It was produced synthetically and put in a box.”

CB Therapeutics is just doing the same thing for cannabinoids, and not just CBD.

“There are 118 cannabinoids, and only five have been studied,” Butt says. “These compounds are like .1, .01, even .001 percent in the cannabis bud. When you want to extract these, a kilogram can be like $100,000 to $350,000. How is someone supposed to do research with that?”

But the yeast don’t care. They take in sugar and output whatever molecule their biosynthesis pathway has been modified to produce — within reason, of course. You couldn’t output large, complex non-organics, but cannabinoids — even the rare ones — are well within their capabilities.

“The only thing we need to add is sugar — that’s the beauty of what we’ve done,” Butt beamed. “The yeast platform is agnostic, it makes everything for the same price.”

This has several benefits. First, it can bring down the price of a known and useful cannabinoid like CBD. Second, it allows the rarer ones to be studied for a reasonable price, and eventually distributed as well. And third, it takes pressure off the agricultural component of the cannabis industry.

That last is not only good from an ecological perspective, since demand is growing and these plants require a lot of water and land, but from the health side as well. Butt points out that a huge majority of cannabis products tested are found to be contaminated to some degree with pesticides and other unwanted compounds.

[gallery ids="1706832,1706833,1706835,1706811,1706810"]

It’s getting better as the marijuana industry becomes an above-board one, but the problem is far from eliminated, and at any rate pesticides and other potentially harmful chemicals don’t cease to be a nuisance just because something is legal. The risk is there for the foreseeable future that, ironically, the “natural” option of using the plant itself is going to produce more impurities in the product, not less. But the yeast don’t — can’t, really — taint the product. So what comes out of the bioreactor should theoretically be as pure as the driven snow. (CB Therapeutics does test it, of course.)

It’s worth noting that the company’s main intellectual property is is the cannabinoid biosynthesis pathway it has developed. That hadn’t been fully documented or explored, Butt says, until their work.

Butt sees this change as more or less just the latest example of a useful class of molecules going from difficult to relatively easy to acquire.

“When you aren’t able to provide for the demand, that makes prices artificially high. People are going out and spending tens of thousands on CBD, for medical applications,” he said. “Insulin used to be harvested from pig pancreases, then Genentech solved that. Aspirin used to come from tree bark. This is inevitable for many compounds. We need to bring the cannabis price down to where anybody can use it.”

The pricing and volume are still somewhat of a question mark — once testing and the regulatory hurdles are taken care of, like any pharmaceutical it’s going to be a moving target. But scaling production shouldn’t be hard should the demand grow, and the backlog of new cannabinoids to isolate for testing should provide a source of income as well.

Medicine can be a risky sector for startups but CB Therapeutics seems to have it as close to sewn up as one can reasonably expect; in a way it’s almost alchemical, this ability to cheaply produce something so valuable. But really, it’s just science.

Marijuana may still be on shaky legal ground, but the therapeutic benefits of the psychoactive molecules — cannabinoids — inside the plant are solidly established. Unfortunately, cultivation of that plant is resource-intensive and yields only tiny amounts of some useful medicines. CB Therapeutics, a new biotech company launching today at the Disrupt SF Startup Battlefield, aims to change the game with cannabinoids produced cleanly and cheaply in the lab — out of sugar.

Co-founder and CEO Sher Ali Butt says the idea struck him when he was working at cannabis testing lab Steep Hill. CBD, a compound found in the plant but in much lower concentrations than THC, the primary intoxicant, was producing extremely helpful pain and anxiety alleviation for some people without a high. The medicinal possibilities were obvious, but high-CBD strains of cannabis are not only uncommon, but a pain to cultivate and process for that purpose.

“CBD had all these applications, and I just thought that there’s got to be a better way to do this. The idea just stuck in my brain,” he told me.

After working on the problem on and off for years he decided to pursue it in earnest. Serendipitously, around this time he ran into Jacob Vogan, an old friend from college who was working in the field of bioengineering. It seemed like a natural fit to them to start the company together.

What CB Therapeutics has done is bioengineer microorganisms — specifically yeast — to manufacture cannabinoids out of plain-old sugars. This type of bioreactor isn’t a new idea; yeast and other organisms are used to create and isolate lots of drugs and substances.

“The vitamin C that we take in tablets, for instance — they didn’t squeeze oranges and lemons to get that,” Butt points out. “There isn’t enough agriculture to supply the global demand. It was produced synthetically and put in a box.”

CB Therapeutics is just doing the same thing for cannabinoids, and not just CBD.

“There are 118 cannabinoids, and only five have been studied,” Butt says. “These compounds are like .1, .01, even .001 percent in the cannabis bud. When you want to extract these, a kilogram can be like $100,000 to $350,000. How is someone supposed to do research with that?”

But the yeast don’t care. They take in sugar and output whatever molecule their biosynthesis pathway has been modified to produce — within reason, of course. You couldn’t output large, complex non-organics, but cannabinoids — even the rare ones — are well within their capabilities.

“The only thing we need to add is sugar — that’s the beauty of what we’ve done,” Butt beamed. “The yeast platform is agnostic, it makes everything for the same price.”

This has several benefits. First, it can bring down the price of a known and useful cannabinoid like CBD. Second, it allows the rarer ones to be studied for a reasonable price, and eventually distributed as well. And third, it takes pressure off the agricultural component of the cannabis industry.

That last is not only good from an ecological perspective, since demand is growing and these plants require a lot of water and land, but from the health side as well. Butt points out that a huge majority of cannabis products tested are found to be contaminated to some degree with pesticides and other unwanted compounds.

[gallery ids="1706832,1706833,1706835,1706811,1706810"]

It’s getting better as the marijuana industry becomes an above-board one, but the problem is far from eliminated, and at any rate pesticides and other potentially harmful chemicals don’t cease to be a nuisance just because something is legal. The risk is there for the foreseeable future that, ironically, the “natural” option of using the plant itself is going to produce more impurities in the product, not less. But the yeast don’t — can’t, really — taint the product. So what comes out of the bioreactor should theoretically be as pure as the driven snow. (CB Therapeutics does test it, of course.)

It’s worth noting that the company’s main intellectual property is is the cannabinoid biosynthesis pathway it has developed. That hadn’t been fully documented or explored, Butt says, until their work.

Butt sees this change as more or less just the latest example of a useful class of molecules going from difficult to relatively easy to acquire.

“When you aren’t able to provide for the demand, that makes prices artificially high. People are going out and spending tens of thousands on CBD, for medical applications,” he said. “Insulin used to be harvested from pig pancreases, then Genentech solved that. Aspirin used to come from tree bark. This is inevitable for many compounds. We need to bring the cannabis price down to where anybody can use it.”

The pricing and volume are still somewhat of a question mark — once testing and the regulatory hurdles are taken care of, like any pharmaceutical it’s going to be a moving target. But scaling production shouldn’t be hard should the demand grow, and the backlog of new cannabinoids to isolate for testing should provide a source of income as well.

Medicine can be a risky sector for startups but CB Therapeutics seems to have it as close to sewn up as one can reasonably expect; in a way it’s almost alchemical, this ability to cheaply produce something so valuable. But really, it’s just science.

YouTube TV introduced a new feature to its service Thursday that allows users to pause their service between four week and six month periods at any time, as reported by Android Police. Unlike canceling and reopening your YouTube TV account, which users can also do at any time, the new pause option allows YouTubers to return to their saved content after a break.

While not standard across all streaming services, YouTube TV is joining Hulu in allowing users to take this further action in controlling how and when they consume streaming content.

To pause their account, users can go to tv.youtube.com, navigate to the membership settings and under Deactivate Membership select Pause membership. If a user decides to reactive their account before their selected break is up, the day they resume will become their new billing date.

In addition to premium YouTube creator content, YouTube TV also offers streaming from channels like ABC, CW, ESPN, AMC, Syfy, MSNBC, Telemundo, Sprout, Freeform and NatGeo, among others. After adding more networks in March, the price of the service has risen to $40/month — on par with some other streaming service prices.

YouTube TV introduced a new feature to its service Thursday that allows users to pause their service between four week and six month periods at any time, as reported by Android Police. Unlike canceling and reopening your YouTube TV account, which users can also do at any time, the new pause option allows YouTubers to return to their saved content after a break.

While not standard across all streaming services, YouTube TV is joining Hulu in allowing users to take this further action in controlling how and when they consume streaming content.

To pause their account, users can go to tv.youtube.com, navigate to the membership settings and under Deactivate Membership select Pause membership. If a user decides to reactive their account before their selected break is up, the day they resume will become their new billing date.

In addition to premium YouTube creator content, YouTube TV also offers streaming from channels like ABC, CW, ESPN, AMC, Syfy, MSNBC, Telemundo, Sprout, Freeform and NatGeo, among others. After adding more networks in March, the price of the service has risen to $40/month — on par with some other streaming service prices.

Twitter has finally put an end to the ongoing controversy over how it has refused to completely shut down the accounts of Alex Jones and his online media site Infowars after a number of people complained about abusive content posted by both: it has finally banned both, on Twitter and its video platform Periscope.

“Today, we permanently suspended @realalexjones and @infowars from Twitter and Periscope,” the Twitter Safety account Tweeted moments ago. “We took this action based on new reports of Tweets and videos posted yesterday that violate our abusive behavior policy, in addition to the accounts’ past violations.

“As we continue to increase transparency around our rules and enforcement actions, we wanted to be open about this action given the broad interest in this case. We do not typically comment on enforcement actions we take against individual accounts, for their privacy.

“We will continue to evaluate reports we receive regarding other accounts potentially associated with @realalexjones or @infowars and will take action if content that violates our rules is reported or if other accounts are utilized in an attempt to circumvent their ban.

The last 24 hours of Jones’ Twitter feed, which you can still see in its cached form on Google, include Tweets calling CNN fake news, criticism of Marco Rubio and Bob Woodward, and questioning the authenticity of the anonymous source writing in the New York Times about the turmoil in the Trump White House. This is, in one regard, relatively mild compared to some of what Jones has put out in the past.

But the last 24 hours also saw CEO Dorsey appear on Capitol Hill, interrogated by the House Energy Committee over its policies of “shadow banning” and general attitude to conservative politics. The company agreed yesterday to a civil rights audit and abuse transparency reports, so this might potentially be seen as Twitter finally trying way of getting ahead of the process, in what has already become a messy and very tough situation for the company.

The company and Dorsey have been roundly criticised by people in recent weeks, who believed that the company was not being strict enough with enforcing its abusive content policies when it came to Jones. While Dorsey had said that he was doing it in the name of “free speech,” cynics believed it was more related to a reluctance to alienate supporters who make up a substantial chunk of Twitter users. (And to be fair, the criticism has been going on for years at this point, with many people quitting the platform in protest.)

Instead, Twitter took incremental steps to try to handle the situation, including 7-day read-only bans and longer explanations to justify why it was not doing more.

Twitter was essentially the last holdout among a throng of social media platforms — including Facebook and YouTube — that had stopped allowing Jones and Infowars from peddling what many believed not just to be “fake news”, but outright damaging and dangerous false information.

 

Twitter has finally put an end to the ongoing controversy over how it has refused to completely shut down the accounts of Alex Jones and his online media site Infowars after a number of people complained about abusive content posted by both: it has finally banned both, on Twitter and its video platform Periscope.

“Today, we permanently suspended @realalexjones and @infowars from Twitter and Periscope,” the Twitter Safety account Tweeted moments ago. “We took this action based on new reports of Tweets and videos posted yesterday that violate our abusive behavior policy, in addition to the accounts’ past violations.

“As we continue to increase transparency around our rules and enforcement actions, we wanted to be open about this action given the broad interest in this case. We do not typically comment on enforcement actions we take against individual accounts, for their privacy.

“We will continue to evaluate reports we receive regarding other accounts potentially associated with @realalexjones or @infowars and will take action if content that violates our rules is reported or if other accounts are utilized in an attempt to circumvent their ban.

The last 24 hours of Jones’ Twitter feed, which you can still see in its cached form on Google, include Tweets calling CNN fake news, criticism of Marco Rubio and Bob Woodward, and questioning the authenticity of the anonymous source writing in the New York Times about the turmoil in the Trump White House. This is, in one regard, relatively mild compared to some of what Jones has put out in the past.

But the last 24 hours also saw CEO Dorsey appear on Capitol Hill, interrogated by the House Energy Committee over its policies of “shadow banning” and general attitude to conservative politics. The company agreed yesterday to a civil rights audit and abuse transparency reports, so this might potentially be seen as Twitter finally trying way of getting ahead of the process, in what has already become a messy and very tough situation for the company.

The company and Dorsey have been roundly criticised by people in recent weeks, who believed that the company was not being strict enough with enforcing its abusive content policies when it came to Jones. While Dorsey had said that he was doing it in the name of “free speech,” cynics believed it was more related to a reluctance to alienate supporters who make up a substantial chunk of Twitter users. (And to be fair, the criticism has been going on for years at this point, with many people quitting the platform in protest.)

Instead, Twitter took incremental steps to try to handle the situation, including 7-day read-only bans and longer explanations to justify why it was not doing more.

Twitter was essentially the last holdout among a throng of social media platforms — including Facebook and YouTube — that had stopped allowing Jones and Infowars from peddling what many believed not just to be “fake news”, but outright damaging and dangerous false information.

 

Building a B2B AI startup is hard enough between struggling to obtain training data and fighting with major tech companies to secure talent. Building a B2B AI startup held to the well-established software-as-a-service (SaaS) metrics is even harder. While many AI businesses deliver value via software monetized by a recurring subscription like their SaaS counterparts, the similarities between the two types of businesses end there.

AI startups are a different animal

SaaS products built without data and AI offer generalized solutions to their customers. AI businesses more closely resemble a services business or consultancies because they provide solutions that become tailored to that customer’s specific needs. Like services providers or consultants, an AI product improves as it knows a customer better (as in, as it collects more data from customers with continued usage), and as it serves a broader customer base, from which it can collect best practices and make better predictions over a bigger data set.

Services revenue has been the antithesis of venture-style growth because it yields lower margins and lacks repeatability and scalability; as your services business brings on more customers, you will need to scale headcount accordingly to support those accounts, which keeps margins low. Palantir, a big data analytics unicorn, is one company mired in services demands. Unlike services providers, AI businesses have the potential to deliver that targeted and greater ROI at scale.

AI businesses are not scalable right out of the gate: AI models take time and require data to train. Moreover, not all AI businesses will scale. Here are the metrics we use to tell the difference early on.

AI metrics

Intervention ratio
Hype will make enterprise customers trigger-happy to pilot AI solutions, but at the end of the day, enterprise buyers buy the best solution available to address their problems and don’t care whether that solution comes in the form of SaaS software, a consultancy or an AI product. It is very difficult to build a high-performing MVP version of an AI model without data from customers. In order to demonstrate value right out of the box and be competitive against other vendors, you might automate which processes you can right off the bat using a rules engine, and provide a human operator to perform the rest of the work while simultaneously labeling the collecting data in order to train the AI.

As the AI improves over time, the human operator will offload more of the work and only jump in to intervene when the AI falls below a predetermined accuracy or confidence threshold. This enables you to serve an increasing number of customers with a limited number of staff. Lilt, which provides machine translation for enterprise, uses professional translators in this role. The translation AI automatically translates a text excerpt from one language to another. A human translator goes over the text looking for errors in translation or contextual corrections. As the translation AI improves, the human translator will have to make fewer corrections per translation task. More generally, the ratio of human interventions over total automated tasks should be decreasing.

ROI curve
As with SaaS products, exactly how that compounding AI performance increase is tied to bringing value for the customer is key to the startup’s long-term stickiness. The key difference with AI products is once the AI’s performance ramps up, it could very quickly exhaust all low-hanging fruit opportunities. If the AI cannot continue to provide value to the customer, the difference in value from one renewal cycle to the next may seem stark to the customer, who may decide to not renew.

Choosing the right applications of AI to enable long-term payoffs and avoiding hitting a wall with ROI is key. Typically, applications that improve the customer’s bottom line face finite opportunities for improvement, and applications that improve the customer’s top line have no ceiling on opportunities to grow. For example, once an AI improves the operating efficiency of a production line to the point where it is rate-limited by the time it takes for the raw materials to chemically react, the AI can no longer find value for the customer for that specific application.

There are only so many opportunities to take out costs before you are constrained by the laws of physics. An AI that helps customers find new opportunities for revenue like, Constructor.io, which provides AI-powered site search as a service and helps customers such as Jet.com increase cart conversions, will not hit that wall.

You should closely track the cumulative ROI for each customer over time to make sure the curve does not plateau and lead the customer to churn. Sometimes the long-term application is harder to sell because the value is difficult to demonstrate immediately, and you might get a foot in the door with the cost take-out value proposition. Understanding its ROI curve would enable you to design a longer contract period so that the AI has time to ramp on new problems before it exhausts the initial application. To ensure customer retention, you should make sure that the customer ROI increases over time and not plateau or taper off.

Rev-up costs
Deploying an AI product is a complicated process that leaves you at the mercy of each customer’s idiosyncratic tech stack and org chart. AI needs data to train, so an AI product may take more time than a SaaS product to deliver value. Acquiring or creating data for the AI model, integrating the product into the customer’s tech stack and workflows and getting the product to deliver value before the model is sufficiently trained on the customer’s data may significantly impact your own bottom line.

Many sectors have only recently begun to digitize, and valuable data might be in difficult-to-extract formats, such as handwritten notes, unstructured observation logs or PDFs. In order to capture this data, you may have to spend significant manpower on low-margin data preparation services before AI systems can be deployed. Depending on how the data is captured and organized, your deployment engineer may have to build new integrations to a data source before the model can be fully functional.

The way data is structured might also vary from one customer to the next, requiring AI engineers to spend additional hours normalizing the data or converting it to a standardized schema so the AI model can be applied. Over time, these costs may decrease as you build up a library of reusable integrations and ETL pipelines.

Products sold by SaaS companies either work or they don’t. AI performance is not binary; it works less well out of the box and improves with more data. Each application and each customer will accept a different minimum algorithmic performance (MAP). The deployment process should make sure to get the product to that customer’s specific MAP, and you might revert back to Wizard of Oz stop-gap approaches to deliver MAP until the model can perform at MAP on its own.

If you are selling to customers that allow you to pool anonymized data or use a model trained on their data with other customers, the AI product will perform better “out of the box” with each subsequent customer. Inside sales customers, for example, can get immediate suggestions on how to optimally target a sales lead using its sales acceleration platform thanks to that data pooled from its customer network.

AI products incur more significant rev-up costs than a typical SaaS product rollout and may have as much impact on margins as customer acquisition costs (CAC). You should carefully track how much time these rollouts and ramp-ups take, and how much it costs for each new customer. If there are true data network effects, these numbers should decrease over time.

Data moat
Unlike SaaS businesses that compete on new features, AI startups have an opportunity to build long-term defensibility. The AI startups that can scale will kick off a virtuous loop where the better the product performs, the more customers come on board to contribute and generate data, which improves the product’s performance. This reinforcement loop builds a compounding defensibility that was previously unheard of for SaaS businesses.

It’s too simplistic to merely aim for the largest volume of data. A defensible data strategy takes into account whether the appropriate data is being collected at a pace that is appropriate for the problem at hand. Ask yourselves these questions about your data to determine where you can strengthen your data strategy on the following dimensions:

• Accessibility: how easy was it to get?
• Time: how quickly can the data be amassed and used in the model?
• Cost: how much money is needed to acquire and/or label this data?
• Uniqueness: is similar data widely available to others who could then build a model and achieve the same result?
• Dimensionality: how many different attributes are described in a data set?
• Breadth: how widely do the values of attributes vary, such that they may account for edge cases and rare exceptions?
• Perishability: will the data be useful for a long time?

AI models perform better with more data, but that performance may plateau over time. You should take care to track the time and volume of data necessary to achieve an incremental unit of value for your customer, to make sure that the data moat continues to grow. In short, how much time, and how much data, would a copycat need to match your level of performance?

SaaS metrics aren’t enough

The higher upfront work necessary to launch an AI business means that most will look more like services businesses or will appear to underperform when they are evaluated under the framework of SaaS metrics. A small subset of AI startups will resemble SaaS businesses from the beginning, before AI is deployed in the product. In order to collect data for their AI models, some businesses first sell SaaS workflow tools and can even achieve meaningful revenue from that workflow tool alone. By SaaS metrics, that company may be blowing the competition out of the water. Without the reinforcement loop generating a compounding volume of data and an increasingly powerful AI over time, however, that company’s product remains vulnerable to copycats and will eventually be commoditized.

AI metrics captures this difference. AI offers the opportunity to deliver the customized and specialized ROI of a services business with the scalability of software, with the ability to defend against copycats. The high start-up costs of this approach to company-building may mean you will realize smaller profits and build the company prioritizing different elements than what has worked before. Vertical AI is so new as a category that many companies are not yet tracking these metrics, so we don’t yet have enough data points to establish benchmarks. In the meantime, these numbers will serve as helpful barometers for you to monitor the health and performance of this new type of company.