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Enterprise AI platform Dataiku launches managed service for smaller companies
Dataiku is going downstream with a new product today called Dataiku Online. As the name suggests, Dataiku Online is a fully managed version of Dataiku. It lets you take advantage of the data science platform without going through a complicated setup process that involves a system administrator and your own infrastructure.
If you’re not familiar with Dataiku, the platform lets you turn raw data into advanced analytics, run some data visualization tasks, create data-backed dashboards and train machine learning models. In particular, Dataiku can be used by data scientists, but also business analysts and less technical people.
The company has been mostly focused on big enterprise clients. Right now, Dataiku has more than 400 customers, such as Unilever, Schlumberger, GE, BNP Paribas, Cisco, Merck and NXP Semiconductors.
There are two ways to use Dataiku. You can install the software solution on your own, on-premise servers. You can also run it on a cloud instance. With Dataiku Online, the startup offers a third option and takes care of setup and infrastructure for you.
“Customers using Dataiku Online get all the same features that our on-premises and cloud instances provide, so everything from data preparation and visualization to advanced data analytics and machine learning capabilities,” co-founder and CEO Florian Douetteau said. “We’re really focused on getting startups and SMBs on the platform — there’s a perception that small or early-stage companies don’t have the resources or technical expertise to get value from AI projects, but that’s simply not true. Even small teams that lack data scientists or specialty ML engineers can use our platform to do a lot of the technical heavy lifting, so they can focus on actually operationalizing AI in their business.”
Customers using Dataiku Online can take advantage of Dataiku’s pre-built connectors. For instance, you can connect your Dataiku instance with a cloud data warehouse, such as Snowflake Data Cloud, Amazon Redshift and Google BigQuery. You can also connect to a SQL database (MySQL, PostgreSQL…), or you can just run it on CSV files stored on Amazon S3.
And if you’re just getting started and you have to work on data ingestion, Dataiku works well with popular data ingestion services. “A typical stack for our Dataiku Online Customers involves leveraging data ingestion tools like FiveTran, Stitch or Alooma, that sync to a cloud data warehouse like Google BigQuery, Amazon Redshift or Snowflake. Dataiku fits nicely within their modern data stacks,” Douetteau said.
Dataiku Online is a nice offering to get started with Dataiku. High-growth startups might start with Dataiku Online as they tend to be short on staff and want to be up and running as quickly as possible. But as you become bigger, you could imagine switching to a cloud or on-premise installation of Dataiku. Employees can keep using the same platform as the company scales.
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Emotion-detection software startup Affectiva acquired for $73.5M
Smart Eye, the publicly traded Swedish company that supplies driver monitoring systems for a dozen automakers, has acquired emotion-detection software startup Affectiva for $73.5 million in a cash-and-stock deal.
Affectiva, which spun out of the MIT Media Lab in 2009, has developed software that can detect and understand human emotion, which Smart Eye is keen to combine with its own AI-based eye-tracking technology. The companies’ founders see an opportunity to expand beyond driver monitoring systems — tech that is often used in conjunction with advanced driver assistance systems to track and measure awareness — and into the rest of the vehicle. Together, the technology could help them break into the emerging “interior sensing” market, which can be used to monitor the entire cabin of a vehicle and deliver services in response to the occupant’s emotional state.
Under the terms of the deal, $67.5 million will be paid with 2,354,668 new Smart Eye shares, of which 2,015,626 are to be issued upon closing of the transaction. The remaining 339,042 Smart Eye shares will be issued within two years of closing. About $6 million will be paid in cash once the deal closes in June 2021.
Affectiva and Smart Eye were competitors. A meeting at the technology trade show CES in 2020 put the two companies on a path to merge.
“Martin and I realized like, wow, we are on a path to compete with each other — and wouldn’t it be so much better if we joined forces?” Affective co-founder and CEO Dr. Rana el Kaliouby said in an interview Tuesday. “By joining forces, we kind of check all the boxes for what the OEMs are looking for with interior sensing, we leapfrog the competition and we have an opportunity to do this better and faster than we could have done it on our own.”
Boston-based Affectiva brings its emotion-detection software to the deal, which will allow Smart Eye to offer its existing automotive partners a variety of products. Smart Eye helps Affectiva move beyond the development and prototype work and into production contracts. Smart Eye has won 84 production contracts with 13 OEMs, including BMW and GM. Smart Eye, which has offices in Gothenburg, Detroit, Tokyo and Chongqing, China, also has a division that provides research organizations such as NASA with high-fidelity eye tracking systems for human factors research.
Smart Eye founder and CEO Martin Krantz said that European manufacturers building luxury and premium vehicles led the charge for driver monitoring systems.
“We see the same pattern repeating itself now for interior sensing,” Krantz said. “I think a large part of the early contracts will be European premium OEMs such as Mercedes, BMW, Audi, JLR, Porsche.” Krantz added that there are a number of other premium brands it will target in other regions, including Cadillac and Lexus.
The opportunity will initially be in passenger vehicles driven by humans and will eventually expand as greater levels of automated driving enter the market.
Affectiva, which employs 100 people at its offices in Boston and Cairo, also has another business unit that applies its emotio-detection software to media analytics. This division, which will be part of the deal and will operate separately, is profitable, Kaliouby said, noting the software is used by 70% of the world’s largest advertisers to measure and understand emotional responses to media content.
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Mental health app Wysa raises $5.5M for ’emotionally intelligent’ AI
It’s hard enough to talk about your feelings to a person; Jo Aggarwal, the founder and CEO of Wysa, is hoping you’ll find it easier to confide in a robot. Or, put more specifically, “emotionally intelligent” artificial intelligence.
Wysa is an AI-powered mental health app designed by Touchkin eServices, Aggarwal’s company that currently maintains headquarters in Bangalore, Boston and London. Wysa is something like a chatbot that can respond with words of affirmation, or guide a user through one of 150 different therapeutic techniques.
Wysa is Aggarwal’s second venture. The first was an elder care company that failed to find market fit, she says. Aggarwal found herself falling into a deep depression, from which, she says, the idea of Wysa was born in 2016.
In March, Wysa became one of 17 apps in the Google Assistant Investment Program, and in May, closed a Series A funding round of $5.5 million led by Boston’s W Health Ventures, the Google Assistant Investment Program, pi Ventures and Kae Capital.
Wysa has raised a total of $9 million in funding, says Aggarwal, and the company has 60 full-time employees and about three million users.
The ultimate goal, she says, is not to diagnose mental health conditions. Wysa is largely aimed at people who just want to vent. Most Wysa users are there to improve their sleep, anxiety or relationships, she says.
“Out of the 3 million people that use Wysa, we find that only about 10% actually need a medical diagnosis,” says Aggarwal. If a user’s conversations with Wysa equate with high scores on traditional depression questionnaires like the PHQ-9 or the anxiety disorder questionnaire GAD-7, Wysa will suggest talking to a human therapist.
Naturally, you don’t need to have a clinical mental health diagnosis to benefit from therapy.
Wysa isn’t intended to be a replacement, says Aggarwal (whether users view it as a replacement remains to be seen), but an additional tool that a user can interact with on a daily basis.
“Sixty percent of the people who come and talk to Wysa need to feel heard and validated, but if they’re given techniques of self help, they can actually work on it themselves and feel better,” Aggarwal continues.
Wysa’s approach has been refined through conversations with users and through input from therapists, says Aggarwal.
For instance, while having a conversation with a user, Wysa will first categorize their statements and then assign a type of therapy, like cognitive behavioral therapy or acceptance and commitment therapy, based on those responses. It would then select a line of questioning or therapeutic technique written ahead of time by a therapist and begin to converse with the user.
Wysa, says Aggarwal, has been gleaning its own insights from more than 100 million conversations that have unfolded this way.
“Take for instance a situation where you’re angry at somebody else. Originally our therapists would come up with a technique called the empty chair technique where you’re trying to look at it from the other person’s perspective. We found that when a person felt powerless or there were trust issues, like teens and parents, the techniques the therapists were giving weren’t actually working,” she says.
“There are 10,000 people facing trust issues who are actually refusing to do the empty chair exercise. So we have to find another way of helping them. These insights have built Wysa.”
Although Wysa has been refined in the field, research institutions have played a role in Wysa’s ongoing development. Pediatricians at the University of Cincinnati helped develop a module specifically targeted toward COVID-19 anxiety. There are also ongoing studies of Wysa’s ability to help people cope with mental health consequences from chronic pain, arthritis and diabetes at The Washington University in St. Louis and The University of New Brunswick.
Still, Wysa has had several tests in the real world. In 2020, the government of Singapore licensed Wysa, and provided the service for free to help cope with the emotional fallout of the coronavirus pandemic. Wysa is also offered through the health insurance company Aetna as a supplement to Aetna’s Employee Assistance Program.
The biggest concern about mental health apps, naturally, is that they might accidentally trigger an incident, or mistake signs of self harm. To address this, the U.K.’s National Health Service (NHS) offers specific compliance standards. Wysa is compliant with the NHS’ DCB0129 standard for clinical safety, the first AI-based mental health app to earn the distinction.
To meet those guidelines, Wysa appointed a clinical safety officer, and was required to create “escalation paths” for people who show signs of self harm.
Wysa, says Aggarwal, is also designed to flag responses to self-harm, abuse, suicidal thoughts or trauma. If a user’s responses fall into those categories Wysa will prompt the user to call a crisis line.
In the U.S., the Wysa app that anyone can download, says Aggarwal, fits the FDA’s definition of a general wellness app or a “low risk device.” That’s relevant because, during the pandemic, the FDA has created guidance to accelerate distribution of these apps.
Still, Wysa may not perfectly categorize each person’s response. A 2018 BBC investigation, for instance, noted that the app didn’t appear to appreciate the severity of a proposed underage sexual encounter. Wysa responded by updating the app to handle more instances of coercive sex.
Aggarwal also notes that Wysa contains a manual list of sentences, often containing slang, that they know the AI won’t catch or accurately categorize as harmful on its own. Those are manually updated to ensure that Wysa responds appropriately. “Our rule is that [the response] can be 80%, appropriate, but 0% triggering,” she says.
In the immediate future, Aggarwal says the goal is to become a full-stack service. Rather than having to refer patients who do receive a diagnosis to Employee Assistant Programs (as the Aetna partnership might) or outside therapists, Wysa aims to build out its own network of mental health suppliers.
On the tech side they’re planning expansion into Spanish, and will start investigating a voice-based system based on guidance from the Google Assistant Investment Fund.
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Forecast nabs $19M for its AI-based approach to project management and resource planning
Project management has long been a people-led aspect of the workplace, but that has slowly been changing. Trends in automation, big data and AI have not only ushered in a new wave of project management applications, but they have led to a stronger culture of people willing to use them. Today, one of the startups building a platform for the next generation of project management is announcing some funding — a sign of the traction it’s getting in the market.
Forecast, a platform and startup of the same name that uses AI to help with project management and resource planning — put simply, it uses artificial intelligence to both “read” and integrate data from different enterprise applications in order to build a bigger picture of the project and potential outcomes — has raised $19 million to continue building out its business.
The company plans to use some of the funding to expand to the U.S., and some to continue building out its platform and business, headquartered in London with a development office also in Copenhagen.
This funding, a Series A, comes less than a year after the startup’s commercial launch, and it was led by Balderton Capital, with previous investors Crane Ventures Partners, SEED Capital and Heartcore also participating.
Forecast closed a seed round in November 2019 and then launched just as the pandemic was kicking off. It was a time when some projects were indeed put on ice, but others that went ahead did so with more caution on all sorts of fronts — financial, organizational and technical. It turned out to be a “right place, right time” moment for Forecast, a tool that plays directly into providing a technical platform to manage all of that in a better way, and it tripled revenues during the year. Its customers include the likes of the NHS, the Red Cross, Etain and more. It says over 150,000 projects have been created and run through its platform to date.
Project management — the process of planning what you need to do, assigning resources to the task and tracking how well all of that actually goes to plan — has long been stuck between a rock and a hard place in the world of work.
It can be essential to getting things done, especially when there are multiple departments or stakeholders involved; yet it’s forever an inexact science that often does not reflect all the complexities of an actual project, and therefore may not be as useful as it could or should be.
This was a predicament that founder and CEO Dennis Kayser knew all too well, having been an engineer and technical lead on a number of big projects himself. His pedigree is an interesting one: One of his early jobs was as a developer at Varien, where he built the first version of Magento. (The company was eventually rebranded as Magento and then acquired by eBay, then spun out, then acquired again, this time by Adobe for nearly $1.7 billion, and is now a huge player in the world of e-commerce tools.) He also spent years as a consultant at IBM, where among other things he helped build and formulate the first versions of ikea.com.
In those and other projects, he saw the pitfalls of project management not done right — not just in terms of having the right people on a project at the right time, but the resource planning needed, better calculations of financial outcomes in the event of a decision going one way or the other, and so on.
He didn’t say this outright, but I’m sure one of the points of contention was the fact that the first ikea.com site didn’t actually have any e-commerce in it, just a virtual window display of sorts. That was because Ikea wanted to keep people shopping in its stores, away from the efficiency of just buying the one thing you actually need and not the 10 you do not. Yes, there are plenty of ways now of recirculating people to buy more when you select one item for a shopping cart — something the likes of Amazon has totally mastered — but this was years ago when there was still even more opportunities for innovation than there are now. All of this is to say that you might very reasonably argue that had there been better project managing and resource planning tools to give forecasts of potential outcomes of one or another route taken, people advocating for a different approach could have made their case better. And maybe Ikea would have jumped on board with digital commerce far sooner than it did.
“Typically you get a lot of spreadsheets, people scattered across different tools that include accounting, CRM, Gitlab and more,” Kayser said.
That became the impetus for trying to build something that can take all of that into account and make a project management tool that — rather than just being a way of accounting to a higher-up, or reflecting only what someone can be bothered to update in the system — something that can help a team.
“Connecting everything into our engine, we leverage data to understand what they are working on and what is the right thing to be working on, what the finances are looking like,” he continued. “So if you work in product, you can plan out who is where, and what resourcing you need, what kind of people and skills you require.” This is a more dynamic progression of some of the other newer tools that are being used for project management today, targeting, in his words, “people who graduate from Monday and Asana who need something more robust, either because they have too many people working on a project or because it’s too complicated, there is just too much stuff to handle.”
More legacy tools he said that are used include Oracle “to some degree” and Mavenlink, which he describes as possibly Forecast’s closest competitor, “but its platform is aging.”
Currently the Forecast platform has some 26 integrations of popular tools used for projects to produce its insights and intelligence, including Salesforce, Gitlab, Google Calendar, and, as it happens, Asana. But given how fragmented the market is, and the signals one might gain from any number of other resources and apps, I suspect that this list will grow as and when its customers need more supported, or Forecast works out what can be gleaned from different places to paint an even more accurate picture.
The result may not ever replace an actual human project manager, but certainly starts to then look like a “digital twin” (a phrase I have been hearing more and more these days) that will definitely help that person, and the rest of the team, work in a smarter way.
“We are really excited to be an early investor in Forecast,” said James Wise, a partner at Balderton Capital, in a statement. “We share their belief that the next generation of SaaS products will be more than just collaboration tools, but use machine learning to actively solve problems for their users. The feedback we got from Forecast’s customers was quite incredible, both in their praise for the platform and in how much of a difference it had already made to their operations. We look forward to supporting the company to scale this impact going forward.”
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Dabbel gets $4.4M to cut CO2 by automating HVAC for commercial buildings
Düsseldorf-based proptech startup Dabbel is using AI to drive energy efficiency savings in commercial buildings.
It’s developed cloud-based self-learning building management software that plugs into the existing building management systems (BMS) — taking over control of heating and cooling systems in a way that’s more dynamic than legacy systems based on fixed set-point resets.
Dabbel says its AI considers factors such as building orientation and thermal insulation, and reviews calibration decisions every five minutes — meaning it can respond dynamically to changes in outdoor and indoor conditions.
The 2018-founded startup claims this approach of layering AI-powered predictive modelling atop legacy BMS to power next-gen building automation is able to generate substantial energy savings — touting reductions in energy consumption of up to 40%.
“Every five minutes Dabbel reviews its decisions based on all available data,” explains CEO and co-founder, Abel Samaniego. “With each iteration, Dabbel improves or adapts and changes its decisions based on the current circumstances inside and outside the building. It does this by using cognitive artificial intelligence to drive a Model-Based Predictive Control (MPC) System… which can dynamically adjust all HVAC setpoints based on current/future conditions.”
In essence, the self-learning system predicts ahead of time the tweaks that are needed to adapt for future conditions — saving energy vs a pre-set BMS that would keep firing the boilers for longer.
The added carrot for commercial building owners (or tenants) is that Dabbel squeezes these energy savings without the need to rip and replace legacy systems — nor, indeed, to install lots of IoT devices or sensor hardware to create a ‘smart’ interior environment; the AI integrates with (and automatically calibrates) the existing heating, ventilation, and air conditioning (HVAC) systems.
All that’s needed is Dabbel’s SaaS — and less than a week for the system to be implemented (it also says installation can be done remotely).
“There are no limitations in terms of Heating and Cooling systems,” confirms Samaniego, who has a background in industrial engineering and several years’ experience automating high tech plants in Germany. “We need a building with a Building Management System in place and ideally a BACnet communication protocol.”
Average reductions achieved so far across the circa 250,000m² of space where its AI is in charge of building management systems are a little more modest but a still impressive 27%. (He says the maximum savings seen at some “peak times” is 42%.)
The touted savings aren’t limited to a single location or type of building/client, according to Dabbel, which says they’ve been “validated across different use cases and geographies spanning Europe, the U.S., China, and Australia”.
Early clients are facility managers of large commercial buildings — Commerzbank clearly sees potential, having incubated the startup via its early-stage investment arm — and several schools.
A further 1,000,000m² is in the contract or offer phase — slated to be installed “in the next six months”.
Dabbel envisages its tech being useful to other types of education institutions and even other use-cases. (It’s also toying with adding a predictive maintenance functionality to expand its software’s utility by offering the ability to alert building owners to potential malfunctions ahead of time.)
And as policymakers around the global turn their attention to how to achieve the very major reductions in carbon emissions that are needed to meet ambitious climate goals the energy efficiency of buildings certainly can’t be overlooked.
“The time for passive responses to addressing the critical issue of carbon emission reduction is over,” said Samaniego in a statement. “That is why we decided to take matters into our own hands and develop a solution that actively replaces a flawed human-based decision-making process with an autonomous one that acts with surgical precision and thanks to artificial intelligence, will only improve with each iteration.”
If the idea of hooking your building’s heating/cooling up to a cloud-based AI sounds a tad risky for Internet security reasons, Dabbel points out it’s connecting to the BMS network — not the (separate) IT network of the company/building.
It also notes that it uses one-way communication via a VPN tunnel — “creating an end-to-end encrypted connection under high market standards”, as Samaniego puts it.
The startup has just closed a €3.6 million (~$4.4M) pre-Series A funding round led by Target Global, alongside main incubator (Commerzbank’s early-stage investment arm), SeedX, plus some strategic angel investors.
Commenting in a statement, Dr. Ricardo Schaefer, partner at Target Global, added: “We are enthusiastic to work with the team at Dabbel as they offer their clients a tangible and frictionless way to significantly reduce their carbon footprint, helping to close the gap between passive measurement and active remediation.”
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SightCall raises $42M for its AR-based visual assistance platform
Long before COVID-19 precipitated “digital transformation” across the world of work, customer services and support was built to run online and virtually. Yet it too is undergoing an evolution supercharged by technology.
Today, a startup called SightCall, which has built an augmented reality platform to help field service teams, the companies they work for, and their customers carry out technical and mechanical maintenance or repairs more effectively, is announcing $42 million in funding, money that it plans to use to invest in its tech stack with more artificial intelligence tools and expanding its client base.
The core of its service, explained CEO and co-founder Thomas Cottereau, is AR technology (which comes embedded in their apps or the service apps its customers use, with integrations into other standard software used in customer service environments including Microsoft, SAP, Salesforce and ServiceNow). The augmented reality experience overlays additional information, pointers and other tools over the video stream.
This is used by, say, field service engineers coordinating with central offices when servicing equipment; or by manufacturers to provide better assistance to customers in emergencies or situations where something is not working but might be repaired quicker by the customers themselves rather than engineers that have to be called out; or indeed by call centers, aided by AI, to diagnose whatever the problem might be. It’s a big leap ahead for scenarios that previously relied on work orders, hastily drawn diagrams, instruction manuals and voice-based descriptions to progress the work in question.
“We like to say that we break the barriers that exist between a field service organization and its customer,” Cottereau said.
The tech, meanwhile, is unique to SightCall, built over years and designed to be used by way of a basic smartphone, and over even a basic mobile network — essential in cases where reception is bad or the locations are remote. (More on how it works below.)
Originally founded in Paris, France before relocating to San Francisco, SightCall has already built up a sizable business across a pretty wide range of verticals, including insurance, telecoms, transportation, telehealth, manufacturing, utilities and life sciences/medical devices.
SightCall has some 200 big-name enterprise customers on its books, including the likes of Kraft-Heinz, Allianz, GE Healthcare and Lincoln Motor Company, providing services on a B2B basis as well as for teams that are out in the field working for consumer customers, too. After seeing 100% year-over-year growth in annual recurring revenue in 2019 and 2020, SightCall’s CEO says it’s looking like it will hit that rate this year as well, with a goal of $100 million in annual recurring revenue.
The funding is being led by InfraVia, a European private equity firm, with Bpifrance also participating. The valuation of this round is not being disclosed, but I should point out that an investor told me that PitchBook’s estimate of $122 million post-money is not accurate (we’re still digging on this and will update as and when we learn more).
For some further context on this investment, InfraVia invests in a number of industrial businesses, alongside investments in tech companies building services related to them such as recent investments in Jobandtalent, so this is in part a strategic investment. SightCall has raised $67 million to date.
There has been an interesting wave of startups emerging in recent years building out the tech stack used by people working in the front lines and in the field, a shift after years of knowledge workers getting most of the attention from startups building a new generation of apps.
Workiz and Jobber are building platforms for small business tradespeople to book jobs and manage them once they’re on the books; BigChange helps manage bigger fleets; and Hover has built a platform for builders to be able to assess and estimate costs for work by using AI to analyze images captured by their or their would-be customers’ smartphone cameras.
And there is Streem, which I discovered is a close enough competitor to SightCall that they’ve acquired AdWords ads based on SightCall searches in Google. Just ahead of the COVID-19 pandemic breaking wide open, General Catalyst-backed Streem was acquired by Frontdoor to help with the latter’s efforts to build out its home services business, another sign of how all of this is leaping ahead.
What’s interesting in part about SightCall and sets it apart is its technology. Co-founded in 2007 by Cottereau and Antoine Vervoort (currently SVP of product and engineering), the two are long-time telecoms industry vets who had both worked on the technical side of building next-generation networks.
SightCall started life as a company called Weemo that built video chat services that could run on WebRTC-based frameworks, which emerged at a time when we were seeing a wider effort to bring more rich media services into mobile web and SMS apps. For consumers and to a large extent businesses, mobile phone apps that work “over the top” (distributed not by your mobile network carrier but the companies that run your phone’s operating system, and thus partly controlled by them) really took the lead and continue to dominate the market for messaging and innovations in messaging.
After a time, Weemo pivoted and renamed itself as SightCall, focusing on packaging the tech that it built into whichever app (native or mobile web) where one of its enterprise customers wanted the tech to live.
The key to how it works comes by way of how SightCall was built, Cottereau explained. The company has spent 10 years building and optimizing a network across data centers close to where its customers are, which interconnects with Tier 1 telecoms carriers and has a lot of latency in the system to ensure uptime. “We work with companies where this connectivity is mission critical,” he said. “The video solution has to work.”
As he describes it, the hybrid system SightCall has built incorporates its own IP that works both with telecoms hardware and software, resulting in a video service that provides 10 different ways for streaming video and a system that automatically chooses the best in a particular environment, based on where you are, so that even if mobile data or broadband reception don’t work, video streaming will. “Telecoms and software are still very separate worlds,” Cottereau said. “They still don’t speak the same language, and so that is part of our secret sauce, a global roaming mechanism.”
The tech that the startup has built to date not only has given it a firm grounding against others who might be looking to build in this space, but has led to strong traction with customers. The next steps will be to continue building out that technology to tap deeper into the automation that is being adopted across the industries that already use SightCall’s technology.
“SightCall pioneered the market for AR-powered visual assistance, and they’re in the best position to drive the digital transformation of remote service,” said Alban Wyniecki, partner at InfraVia Capital Partners, in a statement. “As a global leader, they can now expand their capabilities, making their interactions more intelligent and also bringing more automation to help humans work at their best.”
“SightCall’s $42M Series B marks the largest funding round yet in this sector, and SightCall emerges as the undisputed leader in capital, R&D resources and partnerships with leading technology companies enabling its solutions to be embedded into complex enterprise IT,” added Antoine Izsak of Bpifrance. “Businesses are looking for solutions like SightCall to enable customer-centricity at a greater scale while augmenting technicians with knowledge and expertise that unlocks efficiencies and drives continuous performance and profit.”
Cottereau said that the company has had a number of acquisition offers over the years — not a surprise when you consider the foundational technology it has built for how to architect video networks across different carriers and data centers that work even in the most unreliable of network environments.
“We want to stay independent, though,” he said. “I see a huge market here, and I want us to continue the story and lead it. Plus, I can see a way where we can stay independent and continue to work with everyone.”
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Shift Technology raises $220M at a $1B+ valuation to fight insurance fraud with AI
While incumbent insurance providers continue to get disrupted by startups like Lemonade, Alan, Clearcover, Pie and many others applying tech to rethink how to build a business around helping people and companies mitigate against risks with some financial security, one issue that has not disappeared is fraud. Today, a startup out of France is announcing some funding for AI technology that it has built for all insurance providers, old and new, to help them detect and prevent it.
Shift Technology, which provides a set of AI-based SaaS tools to insurance companies to scan and automatically flag fraud scenarios across a range of use cases — they include claims fraud, claims automation, underwriting, subrogation detection and financial crime detection — has raised $220 million, money that it will be using both to expand in the property and casualty insurance market, the area where it is already strong, as well as to expand into health, and to double down on growing its business in the U.S. It also provides fraud detection for the travel insurance sector.
This Series D is being led by Advent International, via Advent Tech, with participation from Avenir and others. Accel, Bessemer Venture Partners, General Catalyst and Iris Capital — who were all part of Shift’s Series C led by Bessemer in 2019 — also participated. With this round, Paris-and-Boston-based Shift Technology has now raised some $320 million and has confirmed that it is now valued at over $1 billion.
The company currently has around 100 customers across 25 different countries — with the list including Generali France and Mitsui Sumitomo, to give you an idea of where it’s pitching its business — and says that it has already analyzed nearly two billion claims, data that’s feeding its machine learning algorithms to improve how they work.
The challenge (or I suppose, opportunity) that Shift is tackling, however, is much bigger. The Coalition Against Insurance Fraud, a nonprofit in the U.S., estimates that at least $80 billion of fraudulent claims are made annually in the U.S. alone, but the figure is likely significantly higher. One problem has, ironically, been the move to more virtualized processes, which open the door to malicious actors exploiting loopholes in claims filing and fudging information. Another is the fact that insurance has grown as a market, but so too has the amount of people who are in financial straights, leading to more desperate and illegal acts to gain an edge.
Shift is also not alone in tackling this issue: the market for insurance fraud detection technology globally was estimated to be worth $2.5 billion in 2019 and projected to be worth as much as $8 billion by 2024.
In addition to others in claims management tech such as Brightcore and Guidewire, many of the wave of insurtech startups are building in their own in-house AI-based fraud protection, and it’s very likely that we’ll see a rise of other fraud protection services, built out of adjacent areas like fintech to guard against financial crime, making their way to insurance. As many a fintech entrepreneur has said to me in the past, the mechanics of how the two verticals work and the compliance issues both face are very closely aligned.
“The entire Shift team has worked tirelessly to build this company and provide insurers with the technology solutions they need to empower employees to best be there for their policyholders. We are thrilled to partner with Advent International, given their considerable sector expertise and global reach and are taking another giant step forward with this latest investment,” stated Jeremy Jawish, CEO and co-founder, Shift Technology, in a statement. “We have only just scratched the surface of what is possible when AI-based decision automation and optimization is applied to the critical processes that drive the insurance policy lifecycle.”
For its backers, one key point with Shift is that it’s helping older providers bring on more tools and services that can help them improve their margins as well as better compete against the technology built by newer players.
“Since its founding in 2014, Shift has made a name for itself in the complex world of insurance,” said Thomas Weisman, an Advent director, in a statement. “Shift’s advanced suite of SaaS products is helping insurers to reshape manual and often time-consuming claims processes in a safer and more automated way. We are proud to be part of this exciting company’s next wave of growth.”
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How are VCs handling diligence in a world where deals open and close in days, not months?
The global venture capital market had a cracking start to the year. Coming off a 2020 high, VC totals in the United States, in Europe, and among competitive verticals like insurtech and AI are on pace to set new records in 2021.
The rapid-fire deal-making and trend of larger venture checks at higher valuations that The Exchange has tracked for some time require private-market investors to make decisions faster than ever. For venture capitalists, the timeline for reaching conviction around a startup’s thesis and executing due diligence has become compressed.
Some venture capitalists are turning to data to move more quickly. Some are spending more time preparing to be vetted themselves. And some investors are simply doing the work beforehand.
The Exchange explores startups, markets and money.
Read it every morning on Extra Crunch or get The Exchange newsletter every Saturday.
We were tipped off to the concept of pre-diligence during the reporting process for a look into recent fundraising trends in the AI/ML space. Sapphire investor Jai Das, when asked about how he was handling a competitive and swiftly moving market for AI startup investments, said that “most firms are completing their due diligence way before the financing actually happens.”
How does that work in practice? Per Das, startups that raise quick Series A and B rounds are “tracked by [early-stage] investors as soon as they raise their seed financings. So there is no need to do any due diligence during the financing and hence most of these financings are pre-emptive.”
Venture capital: Now more about sales than ever before!
This morning, The Exchange is digging into the question of how VCs are handling diligence in a world where the most attractive deals can open and close faster than ever, and old models of deep diligence and paced deal-making are outmoded.
Getting to yes
One way that investors are betting on themselves in a bid to speed their diligence and decision-making is by investing in their own tech. That may sound obvious, given that venture capital dollars often land in the accounts of tech-focused companies, but in a business that was previously known for its relationship focus — more on that shortly — the trend is worth considering.
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Expect an even hotter AI venture capital market in the wake of the Microsoft-Nuance deal
Microsoft’s huge purchase of health tech AI company Nuance led the technology news cycle this week. The $19.7 billion transaction is Microsoft’s second-largest to date, only beaten by its purchase of LinkedIn some years ago.
For the AI space, the sale is a coup. Nuance was already a public company, but to see Microsoft offer a firm premium over its public-market value demonstrates the value that AI technology can have to wealthy companies. For startups working in the AI space, the Nuance deal is good news; the value of AI revenue was repriced by the acquisition’s announcement — and for the better.
In light of the megadeal, The Exchange dug into the AI venture capital market. What’s happening on the startup side of the coin in the artificial intelligence and machine learning (AI/ML) space?
The Exchange explores startups, markets and money. Read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
To get a handle on the situation, we’ve compiled Q1 2021 and historical venture capital investment data via PitchBook, spoken to an active venture capitalist with a focus on AI-powered startups, and heard from a couple of startups recently featured on CB Insights’ list of leading AI upstarts for their take on the recent news.
The picture that emerges is one of strong investor interest and the expectation of even more in the wake of the Microsoft-Nuance tie-up. For AI startups, it’s a great time to be in the market.
This morning, we’ll start with a look into recent venture capital activity in the AI/ML market and its historical context. Then we’ll talk to Zetta Ventures’ Jocelyn Goldfein and a few companies in the AI space. Let’s go!
A venture capital rush
According to historical data compiled by PitchBook, venture capital investment into U.S.-based, AI-focused startups is enjoying a strong start to the year. Per the group’s provided dataset, from the start of 2021 through April 12, or the first 101 days of the year, 442 deals in the space were worth $11.65 billion.
In 2020, the same query for U.S.-based startups working in the AI and ML space — the line between ML and AI is blurrier than ever — turned up 1,601 rounds worth $27.49 billion.
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With a team that helped build the brain behind Alexa, HomeX raises $90M
HomeX, a home services platform for homeowners and service providers, has raised $90 million in a funding round led by New Mountain Capital.
New Mountain Capital, a New York-based investment firm with more than $30 billion in assets under management, was the only institutional investor to put money in this round alongside company executives. The company was bootstrapped until a 2019 $50 million-plus debt financing.
Founded in 2017, Chicago-based HomeX aims to “radically improve” home services by pairing service workers with homeowners, both virtually and in person. It also has built software, and offers services for, contractors that are aimed at helping them drive and manage demand “more efficiently.”
Notably, one of the company’s co-founders, CTO Simon Weaver, and several team members were on the development team of Evi, a startup that had built an AI program that can be communicated with using natural language via an app, that was acquired by Amazon in 2012. That technology was essentially the brain behind Amazon’s virtual assistant Alexa.
HomeX uses artificial intelligence to diagnose home issues virtually before a contractor even goes out to a home, with the goal of helping them resolve a problem faster (by having the necessary equipment ahead of time for example), which in turn makes customers happier.
“We’re using machine-generated content to create solutions that are specific to a homeowner’s issues,” said co-founder and president Vincent Payen. “Using machines to understand symptoms, the questions to ask and to actually get to a diagnosis and a recommendation or resolution is where AI absolutely shines and allows us to do things that were not possible even three or five years ago.”
Founder and CEO Michael Werner worked in the $500 billion services industry for years (his family founded Werner Ladders) and recognized just how fragmented it was. He also acknowledges that, especially in certain markets, “there’s a terrible imbalance between very high demand and not enough contractors to do the work, or rather, a terrible labor shortage.”
HomeX Remote Assist in particular virtually connects homeowners (via phone, video or chat) with HomeX’s licensed technicians to diagnose and repair common home issues. That business unit has experienced more than 400% growth in less than a year, according to Werner. Last year, the company grew by “about 5x” the number of contractors on its platform. It declined to reveal revenue figures.
Image courtesy of HomeX
“For homeowners, we’re making home maintenance less complicated,” Werner said. “At the same time, we want to help the contractor succeed. Similar to how telemedicine has changed how medicine is delivered, HomeX Remote Assist is going to change the service experience for taking care of your home.”
Another area of HomeX’s business that is growing rapidly is its B2B offering. Home warranty and insurance companies see remote services “as very additive to make their business more efficient,” notes Payen.
“We are using some of our capital toward a pilot program and a number of business development opportunities there,” he said.
For now, while the company is not profitable overall, it is profitable in the services side of its business, according to Werner. In the last 12 months alone, it has served “hundreds of thousands” of clients via its platform, defined by unique virtual and physical appointments.
New Mountain Capital Managing Director Harris Kealey said his firm viewed HomeX as a business that is primed to reshape the home and commercial services industry.
“The market is massive and the need for change and innovation is substantial,” he said in a written statement.
Another company in the space, Thumbtack, recently expanded into video home checkups. Thumbtack, a marketplace where you can hire local professionals for home improvement and other services such as repairs, in December acquired Setter, a startup which provided its customers with video home checkups conducted by experts, and then offered personalized plans for how to address any issues.
Thumbtack had laid off 250 employees at the end of March 2020, after the company saw big declines in its major markets. Since then, however, CEO Marco Zappacosta told TechCrunch there’s been “a renewed focus on the home and an acceleration of digital adoption.”
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