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Peak raises $75M for a platform that helps non-tech companies build AI applications
As artificial intelligence continues to weave its way into more enterprise applications, a startup that has built a platform to help businesses, especially non-tech organizations, build more customized AI decision-making tools for themselves has picked up some significant growth funding. Peak AI, a startup out of Manchester, England, that has built a “decision intelligence” platform, has raised $75 million, money that it will be using to continue building out its platform, expand into new markets and hire some 200 new people in the coming quarters.
The Series C is bringing a very big name investor on board. It is being led by SoftBank Vision Fund 2, with previous backers Oxx, MMC Ventures, Praetura Ventures and Arete also participating. That group participated in Peak’s Series B of $21 million, which only closed in February of this year. The company has now raised $119 million; it is not disclosing its valuation.
(This latest funding round was rumored last week, although it was not confirmed at the time and the total amount was not accurate.)
Richard Potter, Peak’s CEO, said the rapid follow-on in funding was based on inbound interest, in part because of how the company has been doing.
Peak’s so-called Decision Intelligence platform is used by retailers, brands, manufacturers and others to help monitor stock levels and build personalized customer experiences, as well as other processes that can stand to have some degree of automation to work more efficiently, but also require sophistication to be able to measure different factors against each other to provide more intelligent insights. Its current customer list includes the likes of Nike, Pepsico, KFC, Molson Coors, Marshalls, Asos and Speedy, and in the last 12 months revenues have more than doubled.
The opportunity that Peak is addressing goes a little like this: AI has become a cornerstone of many of the most advanced IT applications and business processes of our time, but if you are an organization — and specifically one not built around technology — your access to AI and how you might use it will come by way of applications built by others, not necessarily tailored to you, and the costs of building more tailored solutions can often be prohibitively high. Peak claims that those using its tools have seen revenues on average rise 5%, return on ad spend double, supply chain costs reduce by 5% and inventory holdings (a big cost for companies) reduce by 12%.
Peak’s platform, I should point out, is not exactly a “no-code” approach to solving that problem — not yet at least: It’s aimed at data scientists and engineers at those organizations so that they can easily identify different processes in their operations where they might benefit from AI tools, and to build those out with relatively little heavy lifting.
There have also been different market factors that have played a role. COVID-19, for example, and the boost that we have seen both in increasing “digital transformation” in businesses and making e-commerce processes more efficient to cater to rising consumer demand and more strained supply chains have all led to businesses being more open and keen to invest in more tools to improve their automation intelligently.
This, combined with Peak AI’s growing revenues, is part of what interested SoftBank. The investor has been long on AI for a while; but it also has been building out a section of its investment portfolio to provide strategic services to the kinds of businesses in which it invests.
Those include e-commerce and other consumer-facing businesses, which make up one of the main segments of Peak’s customer base.
Notably, one of its recent investments specifically in that space was made earlier this year, also in Manchester, when it took a $730 million stake (with potentially $1.6 billion more down the line) in The Hut Group, which builds software for and runs D2C businesses.
“In Peak we have a partner with a shared vision that the future enterprise will run on a centralized AI software platform capable of optimizing entire value chains,” Max Ohrstrand, senior investor for SoftBank Investment Advisers, said in a statement. “To realize this a new breed of platform is needed and we’re hugely impressed with what Richard and the excellent team have built at Peak. We’re delighted to be supporting them on their way to becoming the category-defining, global leader in Decision Intelligence.”
It’s not clear that SoftBank’s two Manchester interests will be working together, but it’s an interesting synergy if they do, and most of all highlights one of the firm’s areas of interest.
Longer term, it will be interesting to see how and if Peak evolves to extend its platform to a wider set of users at the organizations that are already its customers.
Potter said he believes that “those with technical predispositions” will be the most likely users of its products in the near and medium term. You might assume that would cut out, for example, marketing managers, although the general trend in a lot of software tools has precisely been to build versions of the same tools used by data scientists for these less technical people to engage in the process of building what it is that they want to use.
“I do think it’s important to democratize the ability to stream data pipelines, and to be able to optimize those to work in applications,” Potter added.
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Hibob raises $70M for its new take on human resources
Productivity software has been getting a major re-examination this year, and human resources platforms — used for hiring, firing, paying and managing employees — have been no exception. Today, one of the startups that’s built what it believes is the next generation of how HR should and will work is announcing a big fundraise, underscoring its own growth and the focus on the category.
Hibob, the startup behind the HR platform that goes by the name of “bob” (the company name is pronounced, “Hi, Bob!”), has picked up $70 million in funding at a valuation that reliable sources close to the company tell us is around $500 million.
“Our mission is to modernize HR technology,” said Ronni Zehavi, Hibob’s CEO, who co-founded the company with Israel David. “We are a people management platform for how people work today. Whether that’s remotely or physically collaborative, our customers face challenges with work. We believe that the HR platforms of the future will not be clunky systems, annoying, giant platforms. We believe it should be different. We are a system of engagement rather than record.”
The Series B is being led by SEEK and Israel Growth Partners, with participation also from Bessemer Venture Partners, Battery Ventures, Eight Roads Ventures, Arbor Ventures, Presidio Ventures, Entree Capital, Cerca Partners and Perpetual Partners, the same group that also backed Hibob in its last round (a Series A extension) in 2019. It has raised $124 million to date.
The company has its roots in Israel but these days describes its headquarters as London and New York, and the funding comes on the back of strong growth in multiple markets. In an interview, Zehavi said that Hibob specialises in the mid-market customers and says that it has more than 1,000 of them currently on its books across the U.S., Europe and Asia, including Monzo, Revolut, Happy Socks, ironSource, Receipt Bank, Fiverr, Gong and VaynerMedia. In the last year Hibob has had “triple-digit” year-on-year growth (it didn’t specify what those digits are).
Human resources has never been at the more glamorous end of how a company works, and it can sometimes even be looked on with some disdain. However, HR has found itself in a new spotlight in 2020, the year when every company — whether one based around people sitting at desks or in more interactive and active environments — had to change how it worked.
That might have involved sending everyone home to sign in from offices possibly made out of corners of bedrooms or kitchens, or that might have involved a vastly different set of practices in terms of when and where workers showed up and how they interacted with people once they did. But regardless of the implementations, they all involved a team of people who needed to be linked together, still feeling connected and managed; and sometimes hired, furloughed, or let go.
That focus has started to reveal the strains of how some legacy systems worked, with older systems built to consider little more than creating an employee identity number that could then be tracked for payroll and other purposes.
Hibob — Zehavi said they chose the name after the person who owned the bob.com domain wanted too much to sell it, but they liked “bob” for the actual product — takes an approach from the ground up that is in line with how many people work today, balancing different software and apps depending on what they are doing, and linking them up by way of integrations: its own includes Slack, Microsoft Teams and Mercer, and other packages that are popular with HR departments.
While it covers all of the necessary HR bases like payroll and further compensation, onboarding, managing time off and benefits, it further brings in a variety of other features that help build out bigger profiles of users, such as performance and culture, with the ability for peers, managers and workers themselves to provide feedback to enhance their own engagement with the company, and for the company to have a better idea of how they are fitting into the organization, and what might need more attention in the future.
That then links into a bigger organizational chart and conceptual charts that highlight strong performers, those who are possible flight risks, those who are leaders and so on. While there have been a number of others in the HR world that have built standalone apps that cover some of these features (for example, 15five was early to spot the value of a platform that made it much easier to set goals and provide feedback), what’s notable here is how they are all folded into one system together.
The end effect, as you can see here, looks less like word salad and more interactive, graphic interfaces that are presumably a lot more enjoyable and at least easier to use for HR people themselves.
The importance for investors has been that the product and the startup has identified the opportunity, but has delivered not just more engagement, but a strong piece of software that still provides the essentials.
“This is certainly not a Workday,” said Adam Fisher, a partner at Bessemer, in an interview. “Our overall thesis has been that HR is only growing in importance. And while engagement is super important, that opportunity is not enough to create the market.”
The end result is a platform that has a significant shot at building in even more over time. For example, another large area that has been seeing traction in the world of enterprise and B2B software is employee training. Specifically, enterprise learning systems are creating another way to help keep people not only up to speed on important aspects of how they work, but also engaged at a time when connections are under strain.
“Training, a SuccessFactors -style offering, is definitely in our road map,” said Zehavi, who noted they are adding new features all the time. The latest has been compensation, sometimes known as merit increase cycles. “That is a very complex issue and requires deeper integrations finance and the CFO’s office. We streamlined it and made it easy to use. We launched two months ago and it’s on fire. After learning and development there are other modules also down the road.”
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Fylamynt raises $6.5M for its cloud workflow automation platform
Fylamynt, a new service that helps businesses automate their cloud workflows, today announced both the official launch of its platform as well as a $6.5 million seed round. The funding round was led by Google’s AI-focused Gradient Ventures fund. Mango Capital and Point72 Ventures also participated.
At first glance, the idea behind Fylamynt may sound familiar. Workflow automation has become a pretty competitive space, after all, and the service helps developers connect their various cloud tools to create repeatable workflows. We’re not talking about your standard IFTTT- or Zapier -like integrations between SaaS products, though. The focus of Fylamynt is squarely on building infrastructure workflows. While that may sound familiar, too, with tools like Ansible and Terraform automating a lot of that already, Fylamynt sits on top of those and integrates with them.
Image Credits: Fylamynt
“Some time ago, we used to do Bash and scripting — and then [ … ] came Chef and Puppet in 2006, 2007. SaltStack, as well. Then Terraform and Ansible,” Fylamynt co-founder and CEO Pradeep Padala told me. “They have all done an extremely good job of making it easier to simplify infrastructure operations so you don’t have to write low-level code. You can write a slightly higher-level language. We are not replacing that. What we are doing is connecting that code.”
So if you have a Terraform template, an Ansible playbook and maybe a Python script, you can now use Fylamynt to connect those. In the end, Fylamynt becomes the orchestration engine to run all of your infrastructure code — and then allows you to connect all of that to the likes of DataDog, Splunk, PagerDuty Slack and ServiceNow.
Image Credits: Fylamynt
The service currently connects to Terraform, Ansible, Datadog, Jira, Slack, Instance, CloudWatch, CloudFormation and your Kubernetes clusters. The company notes that some of the standard use cases for its service are automated remediation, governance and compliance, as well as cost and performance management.
The company is already working with a number of design partners, including Snowflake.
Fylamynt CEO Padala has quite a bit of experience in the infrastructure space. He co-founded ContainerX, an early container-management platform, which later sold to Cisco. Before starting ContainerX, he was at VMWare and DOCOMO Labs. His co-founders, VP of Engineering Xiaoyun Zhu and CTO David Lee, also have deep expertise in building out cloud infrastructure and operating it.
“If you look at any company — any company building a product — let’s say a SaaS product, and they want to run their operations, infrastructure operations very efficiently,” Padala said. “But there are always challenges. You need a lot of people, it takes time. So what is the bottleneck? If you ask that question and dig deeper, you’ll find that there is one bottleneck for automation: that’s code. Someone has to write code to automate. Everything revolves around that.”
Fylamynt aims to take the effort out of that by allowing developers to either write Python and JSON to automate their workflows (think “infrastructure as code” but for workflows) or to use Fylamynt’s visual no-code drag-and-drop tool. As Padala noted, this gives developers a lot of flexibility in how they want to use the service. If you never want to see the Fylamynt UI, you can go about your merry coding ways, but chances are the UI will allow you to get everything done as well.
One area the team is currently focusing on — and will use the new funding for — is building out its analytics capabilities that can help developers debug their workflows. The service already provides log and audit trails, but the plan is to expand its AI capabilities to also recommend the right workflows based on the alerts you are getting.
“The eventual goal is to help people automate any service and connect any code. That’s the holy grail. And AI is an enabler in that,” Padala said.
Gradient Ventures partner Muzzammil “MZ” Zaveri echoed this. “Fylamynt is at the intersection of applied AI and workflow automation,” he said. “We’re excited to support the Fylamynt team in this uniquely positioned product with a deep bench of integrations and a nonprescriptive builder approach. The vision of automating every part of a cloud workflow is just the beginning.”
The team, which now includes about 20 employees, plans to use the new round of funding, which closed in September, to focus on its R&D, build out its product and expand its go-to-market team. On the product side, that specifically means building more connectors.
The company offers both a free plan as well as enterprise pricing and its platform is now generally available.
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Gatik’s self-driving box trucks to shuttle groceries for Loblaw in Canada
Gatik, the autonomous vehicle startup focused on the “middle mile,” is already using its self-driving box trucks to deliver customer online grocery orders for Walmart. Now, the company — freshly stocked with $25 million in Series A funding — is expanding up into Canada with a partnership with retail giant Loblaw.
Gatik said Monday that five autonomous box trucks in Toronto will be used to deliver goods for Loblaw starting in January 2021. The fleet will be used seven days a week on five routes along public roads. All vehicles will have a safety driver as a co-pilot. This deployment, which follows a 10-month pilot in the Toronto area, marks the first autonomous delivery fleet in Canada.
“As more Canadians turn to online grocery shopping, we’ve looked at ways to make our supply chain more efficient. Middle-mile autonomous delivery is a great example,” Loblaw Digital senior vice president Lauren Steinberg said in a statement. “With this initial rollout in Toronto, we are able to move goods from our automated picking facility multiple times a day to keep pace with PC Express online grocery orders in stores around the city.”
Unlike other autonomous delivery companies, Gatik isn’t targeting consumers. Instead, the startup is using its autonomous trucks to shuttle groceries and other goods from large distribution centers to retail locations. For Loblaw, the company will equip Ford Transit 350 box trucks with refrigeration units, lift gates and its autonomous self-driving software.
“Retailers know the biggest inefficiencies in their logistics operations often exist in the middle-mile, typically between automated picking facilities and retail locations,” Gatik CEO and co-founder Gautam Narang said in a statement. “This is where Gatik lives and succeeds, and is the reason we’re able to offer immediate value to our customers. We are delighted to partner with Loblaw in addressing this critical piece of their supply chain.”
Gatik’s “middle mile” B2B focus has attracted customers like Walmart, as well as investors, including Wittington Ventures and Innovation Endeavors, which co-led the company’s Series A round. FM Capital and Intact Ventures, along with existing investors Dynamo Ventures, Fontinalis Partners and AngelPad also participated in the round that was announced alongside the Loblaw partnership. Gatik has raised $29.5 million to date.
The company said it plans to use the funding to build out operations across North America and hire more employees at its Palo Alto, California and Toronto facilities. Narang said Gatik is also pushing to expand its retail partnerships and fleet deployments.
“Throughout the year we saw an increase of 30% to 35% in orders from our customer base, and we expect this trend to continue,” Narang said. “We will continue to bring autonomous delivery into the mainstream, driving substantial efficiencies in supply chain logistics for retailers across North America and beyond.”
Gatik said it has completed more than 30,000 revenue-generating autonomous orders for multiple customers across North America.
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AI-tool maker Seldon raises £7.1M Series A from AlbionVC and Cambridge Innovation Capital
Seldon is a U.K. startup that specializes in the rarified world of development tools to optimize machine learning. What does this mean? Well, dear reader, it means that the “AI” that companies are so fond of trumpeting does actually end up working.
It has now raised a £7.1 million Series A round co-led by AlbionVC and Cambridge Innovation Capital . The round also includes significant participation from existing investors Amadeus Capital Partners and Global Brain, with follow-on investment from other existing shareholders. The £7.1 million funding will be used to accelerate R&D and drive commercial expansion, take Seldon Deploy — a new enterprise solution — to market and double the size of the team over the next 18 months.
More accurately, Seldon is a cloud-agnostic machine learning (ML) deployment specialist which works in partnership with industry leaders such as Google, Red Hat, IBM and Amazon Web Services.
Key to its success is that its open-source project Seldon Core has more than 700,000 models deployed to date, drastically reducing friction for users deploying ML models. The startup says its customers are getting productivity gains of as much as 92% as a result of utilizing Seldon’s product portfolio.
Alex Housley, CEO and founder of Seldon speaking to TechCrunch explained that companies are using machine learning across thousands of use cases today, “but the model actually only generates real value when it’s actually running inside a real-world application.”
“So what we’ve seen emerge over these last few years are companies that specialize in specific parts of the machine learning pipeline, such as training version control features. And in our case we’re focusing on deployment. So what this means is that organizations can now build a fully bespoke AI platform that suits their needs, so they can gain a competitive advantage,” he said.
In addition, he said Seldon’s open-source model means that companies are not locked-in: “They want to avoid locking as well they want to use tools from various different vendors. So this kind of intersection between machine learning, DevOps and cloud-native tooling is really accelerating a lot of innovation across enterprise and also within startups and growth-stage companies.”
Nadine Torbey, an investor at AlbionVC, added: “Seldon is at the forefront of the next wave of tech innovation, and the leadership team are true visionaries. Seldon has been able to build an impressive open-source community and add immediate productivity value to some of the world’s leading companies.”
Vin Lingathoti, partner at Cambridge Innovation Capital, said: “Machine learning has rapidly shifted from a nice-to-have to a must-have for enterprises across all industries. Seldon’s open-source platform operationalizes ML model development and accelerates the time-to-market by eliminating the pain points involved in developing, deploying and monitoring machine learning models at scale.”
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App management startup AppFollow raises $5M Series A round led by Nauta Capital
AppFollow, an app management startup, has raised a $5 million Series A round led by Barcelona’s Nauta Capital, alongside existing investors Vendep Capital and RTP Global participating.
The Helsinki-headquartered company says it benefitted during the pandemic and even in April 2020 as the desire for automation and apps exploded. It says it now has 70,000 clients on its platform globally, including McDonald’s, Disney, Expedia, PicsArt, Flo, Jam City and Discord.
CEO Anatoly Sharifulin said in a statement: “AppFollow helps teams understand sentiment, both for your users and competitor’s, figure out how your potential customers search for apps and use this knowledge to make your app more visible and, of course, follow on your KPIs like downloads and revenues to be sure that all is under control.”
Eugene Kruglov of Nauta Capital said: “We are extremely delighted to partner with Nauta Capital on this round. And having both of current investors and as well some of our customers to participate in the round proves that we are on the right direction to become the market standard for effective app management.”
The company, which employs 65 people across nine countries, all working remotely, will use the investment to strengthen its presence in the U.S. and Europe, hire VP-level executives in sales and marketing, and diversify their platform.
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Shelf Engine has a plan to reduce food waste at grocery stores, and $12 million in new cash to do it
For the first few months it was operating, Shelf Engine, the Seattle-based company that optimizes the process of stocking store shelves for supermarkets and groceries, didn’t have a name.
Co-founders Stefan Kalb and Bede Jordan were on a ski trip outside of Salt Lake City about four years ago when they began discussing what, exactly, could be done about the problem of food waste in the U.S.
Kalb is a serial entrepreneur whose first business was a food distribution company called Molly’s, which was sold to a company called HomeGrown back in 2019.
A graduate of Western Washington University with a degree in actuarial science, Kalb says he started his food company to make a difference in the world. While Molly’s did, indeed, promote healthy eating, the problem that Kalb and Bede, a former Microsoft engineer, are tackling at Shelf Engine may have even more of an impact.
Food waste isn’t just bad for its inefficiency in the face of a massive problem in the U.S. with food insecurity for citizens, it’s also bad for the environment.
Shelf Engine proposes to tackle the problem by providing demand forecasting for perishable food items. The idea is to wring inefficiencies out of the ordering system. Typically about a third of food gets thrown out of the bakery section and other highly perishable goods stocked on store shelves. Shelf Engine guarantees sales for the store, and any items that remain unsold the company will pay for.
Image: OstapenkoOlena/iStock
Shelf Engine gets information about how much sales a store typically sees for particular items and can then predict how much demand for a particular product there will be. The company makes money off of the arbitrage between how much it pays for goods from vendors and how much it sells to grocers.
It allows groceries to lower the food waste and have a broader variety of products on shelves for customers.
Shelf Engine initially went to market with a product that it was hoping to sell to groceries, but found more traction by becoming a marketplace and perfecting its models on how much of a particular item needs to go on store shelves.
The next item on the agenda for Bede and Kalb is to get insights into secondary sources like imperfect produce resellers or other grocery stores that work as an outlet.
The business model is already showing results at around 400 stores in the Northwest, according to Kalb, and it now has another $12 million in financing to go to market.
The funds came from Garry Tan’s Initialized and GGV (and GGV managing director Hans Tung has a seat on the company’s board). Other investors in the company include Foundation Capital, Bain Capital, 1984 and Correlation Ventures .
Kalb said the money from the round will be used to scale up the engineering team and its sales and acquisition process.
The investment in Shelf Engine is part of a wave of new technology applications coming to the grocery store, as Sunny Dhillon, a partner at Signia Ventures, wrote in a piece for TechCrunch’s Extra Crunch (membership required).
“Grocery margins will always be razor thin, and the difference between a profitable and unprofitable grocer is often just cents on the dollar,” Dhillon wrote. “Thus, as the adoption of e-grocery becomes more commonplace, retailers must not only optimize their fulfillment operations (e.g. MFCs), but also the logistics of delivery to a customer’s doorstep to ensure speed and quality (e.g. darkstores).”
Beyond Dhillon’s version of a delivery-only grocery network with mobile fulfillment centers and dark stores, there’s a lot of room for chains with existing real estate and bespoke shopping options to increase their margins on perishable goods, as well.
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Data startup Axiom secures $4M from Crane Venture Partners, emerges from stealth
Axiom, a startup that helps companies deal with their internal data, has secured a new $4 million seed round led by U.K.-based Crane Venture Partners, with participation from LocalGlobe, Fly VC and Mango Capital. Notable angel investors include former Xamarin founder and current GitHub CEO Nat Friedman and Heroku co-founder Adam Wiggins. The company is also emerging from a relative stealth mode to reveal that is has now raised $7 million in funding since it was founded in 2017.
The company says it is also launching with an enterprise-grade solution to manage and analyze machine data “at any scale, across any type of infrastructure.” Axiom gives DevOps teams a cloud-native, enterprise-grade solution to store and query their data all the time in one interface — without the overhead of maintaining and scaling data infrastructure.
DevOps teams have spent a great deal of time and money managing their infrastructure, but often without being able to own and analyze their machine data. Despite all the tools at hand, managing and analyzing critical data has been difficult, slow and resource-intensive, taking up far too much money and time for organizations. This is what Axiom is addressing with its platform to manage machine data and surface insights, more cheaply, they say, than other solutions.
Co-founder and CEO Neil Jagdish Patel told TechCrunch: “DevOps teams are stuck under the pressure of that, because it’s up to them to deliver a solution to that problem. And the solutions that existed are quite, well, they’re very complex. They’re very expensive to run and time-consuming. So with Axiom, our goal is to try and reduce the time to solve data problems, but also allow businesses to store more data to query at whenever they want.”
Why did they work with Crane? “We needed to figure out how enterprise sales work and how to take this product to market in a way that makes sense for the people who need it. We spoke to different investors, but when I sat down with Crane they just understood where we were. They have this razor-sharp focus on how they get you to market and how you make sure your sales process and marketing is a success. It’s been beneficial to us as were three engineers, so you need that,” said Patel.
Commenting, Scott Sage, founder and partner at Crane Venture Partners added: “Neil, Seif and Gord are a proven team that have created successful products that millions of developers use. We are proud to invest in Axiom to allow them to build a business helping DevOps teams turn logging challenges from a resource-intense problem to a business advantage.”
Axiom co-founders Neil Jagdish Patel, Seif Lotfy and Gord Allott previously created Xamarin Insights that enabled developers to monitor and analyse mobile app performance in real time for Xamarin, the open-source cross-platform app development framework. Xamarin was acquired by Microsoft for between $400 and $500 million in 2016. Before working at Xamarin, the co-founders also worked together at Canonical, the private commercial company behind the Ubuntu Project.
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Directly, which taps experts to train chatbots, raises $11M, closes out Series B at $51M
Directly, a startup whose mission is to help build better customer service chatbots by using experts in specific areas to train them, has raised more funding as it opens up a new front to grow its business: APIs and a partner ecosystem that can now also tap into its expert network. Today Directly is announcing that it has added $11 million to close out its Series B at $51 million (it raised $20 million back in January of this year, and another $20 million as part of the Series B back in 2018).
The funding is coming from Triangle Peak Partners and Toba Capital, while its previous investors in the round included strategic backers Samsung NEXT and Microsoft’s M12 Ventures (who are both customers, alongside companies like Airbnb), as well as Industry Ventures, True Ventures, Costanoa Ventures and Northgate. (As we reported when covering the initial close, Directly’s valuation at that time was at $110 million post-money, and so this would likely put it at $120 million or higher, given how the business has expanded.)
While chatbots have now been around for years, a key focus in the tech world has been how to help them work better, after initial efforts saw so many disappointing results that it was fair to ask whether they were even worth the trouble.
Directly’s premise is that the most important part of getting a chatbot to work well is to make sure that it’s trained correctly, and its approach to that is very practical: find experts both to troubleshoot questions and provide answers.
As we’ve described before, its platform helps businesses identify and reach out to “experts” in the business or product in question, collect knowledge from them, and then fold that into a company’s AI to help train it and answer questions more accurately. It also looks at data input and output into those AI systems to figure out what is working, and what is not, and how to fix that, too.
The information is typically collected by way of question-and-answer sessions. Directly compensates experts both for submitting information as well as to pay out royalties when their knowledge has been put to use, “just as you would in traditional copyright licensing in music,” its co-founder Antony Brydon explained to me earlier this year.
It can take as little as 100 experts, but potentially many more, to train a system, depending on how much the information needs to be updated over time. (Directly’s work for Xbox, for example, used 1,000 experts but has to date answered millions of questions.)
Directly’s pitch to customers is that building a better chatbot can help deflect more questions from actual live agents (and subsequently cut operational costs for a business). It claims that customer contacts can be reduced by up to 80%, with customer satisfaction by up to 20%, as a result.
What’s interesting is that now Directly sees an opportunity in expanding that expert ecosystem to a wider group of partners, some of which might have previously been seen as competitors. (Not unlike Amazon’s AI powering a multitude of other businesses, some of which might also be in the market of selling the same services that Amazon does).
The partner ecosystem, as Directly calls it, use APIs to link into Directly’s platform. Meya, Percept.ai, and SmartAction — which themselves provide a range of customer service automation tools — are three of the first users.
“The team at Directly have quickly proven to be trusted and invaluable partners,” said Erik Kalviainen, CEO at Meya, in a statement. “As a result of our collaboration, Meya is now able to take advantage of a whole new set of capabilities that will enable us to deliver automated solutions both faster and with higher resolution rates, without customers needing to deploy significant internal resources. That’s a powerful advantage at a time when scale and efficiency are key to any successful customer support operation.”
The prospect of a bigger business funnel beyond even what Directly was pulling in itself is likely what attracted the most recent investment.
“Directly has established itself as a true leader in helping customers thrive during these turbulent economic times,” said Tyler Peterson, Partner at Triangle Peak Partners, in a statement. “There is little doubt that automation will play a tremendous role in the future of customer support, but Directly is realizing that potential today. Their platform enables businesses to strike just the right balance between automation and human support, helping them adopt AI-powered solutions in a way that is practical, accessible, and demonstrably effective.”
In January, Mike de la Cruz, who took over as CEO at the time of the funding announcement, said the company was gearing up for a larger Series C in 2021. It’s not clear how and if that will be impacted by the current state of the world. But in the meantime, as more organizations are looking for ways to connect with customers outside of channels that might require people to physically visit stores, or for employees to sit in call centres, it presents a huge opportunity for companies like this one.
“At its core, our business is about helping customer support leaders resolve customer issues with the right mix of automation and human support,” said de la Cruz in a statement. “It’s one thing to deliver a great product today, but we’re committed to ensuring that our customers have the solutions they need over the long term. That means constantly investing in our platform and expanding our capabilities, so that we can keep up with the rapid pace of technological change and an unpredictable economic landscape. These new partnerships and this latest expansion of our recent funding round have positioned us to do just that. We’re excited to be collaborating with our new partners, and very thankful to all of our investors for their support.”
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Identity management startup Truework raises $30M to help you verify your work history
As organizations look for safe and efficient ways of running their services in the new global paradigm of increased social distancing, a startup that has built a platform to help people verify their work details in a secure way is announcing a round of growth funding.
Truework, which provides a way for banks, apartment-rental agencies, and others to check the employment details of an applicant in a quick and secure manner online, has raised $30 million, money that CEO and co-founder Ryan Sandler said in an interview that it would use both grow its existing business, as well to explore adding more details — both via its own service and via third-party partnerships — to the identity information that it shares.
The Series B is being led by Activant Capital — a VC that focuses on B2B2C startups — with participation also from Sequoia Capital and Khosla Ventures, as well as a number of high profile execs and entrepreneurs — Jeff Weiner (LinkedIn); Tom Gonser (Docusign); William Hockey (Plaid); and Daniel Yanisse (Checkr) among them.
The LinkedIn connection is an interesting one. Both Sandler and co-founder Victor Kabdebon were engineers at LinkedIn working on profile and improving the kind of data that LinkedIn sources on its users (the third co-founder, Ethan Winchell, previously worked elsewhere), and while Sandler tells me that the idea for Truework came to them after both left the company, he sees LinkedIn “as a potential partner here,” so watch this space.
The problem that Truework is aiming to solve is the very clunky, and often insecure, nature of how organizations typically verify an individual’s employment information. Details about salary and where you work, and the job you do, are typically essential for larger financial transactions, whether it’s securing a mortgage or another financing loan, or renting an apartment, or for others who might need to verify that information for other purposes, such as staffing agencies.
Typically that kind of information gathering is time-consuming both to reach out to get and to confirm (Sandler cites statistics that say on average an HR person spends over 1,000 hours annually answering questions like these). And some of the systems that have been put in place to do that work — specifically consumer reporting agencies — have been proven not be as watertight in their security as you would hope.
“Your data is flowing around lots of third party platforms,” Sandler said. “You’re releasing a lot of information about yourself and you don’t know where the data is going and if it’s even accurate.”
Truework’s solution is based around a platform, and now an API, that a company buys into. In turn, it gives its employees the ability to consent to using it. If the employee agrees, Truework sources a worker’s place of employment and salary details. Then when a third party wants to verify that information for the person in question, it uses Truework to do so, rather than contacting the company directly.
Then, when those queries come in, Truework contacts the individual with an email or text about the inquiry, so that he/she can okay (or reject) the request. Truework’s Sandler said that it uses ISO27001, SOC2 Type 1 & 2 protections, but he also confirmed that it does store your data.
Currently the idea is that if you leave your job, your next employer would need to also be a Truework customer in order to update the information it has on you: the startup makes money by charging both larger enterprises to make the platform accessible to employees as well as those organizations that are querying for the information/verifications (small business employers using the platform can use it for free).
Over time, the plan will be to configure a way to update your profiles regardless of where you work.
So far, the concept has seen a lot of traction: there are 20,000 small businesses using the platform, as well as 100 enterprises, with the number of verifiers (its term for those requesting information) now at 40,000. Customers include The College Board, The Real Real, Oscar Health, The Motley Fool, and Tuft & Needle.
While all of this was built at a time before COVID-19, the global health pandemic has highlighted the importance of having more efficient and secure systems for doing work, especially at a time when many people are not in the office.
“Our biggest competitor is the fax machine and the phone call,” Sandler said, “but as companies move to more remote working, no one is manning the phones or fax machines. But these operations still need to happen.” Indeed, he points out that at the end of 2019, Truework had 25,000 verifiers. Nearly doubling its end-user customers speaks to the huge boost in business it has seen in the last five months.
That is part of the reason the company has attracted the investment it has.
“Truework’s platform sits at the center of consumers’ most important transactions and life events – from purchasing a home, to securing a new job,” said Steve Sarracino, founder and partner at Activant Capital, in a statement. “Up until now, the identity verification process has been painful, expensive, and opaque for all parties involved, something we’ve seen first-hand in the mortgage space. Starting with income and employment, Truework is setting the standard for consent-based verifications and unlocking the next wave of the digital economy. We’re thrilled to be partnering with this exceptional team as they continue to scale the platform.” Sarracino is joining the board with this round.
While a big focus in the world of tech right now may be on building more and better ways of connecting goods and services to people in as contact-free a way as possible, the bigger play around identity management has been around for years, and will continue to be a huge part of how the internet develops in the future.
The fax and phone may be the primary tools these days for verifying employment information, but on a more general level, there are companies like Facebook, Google and Apple already playing a big role in how we “log in” and use all kinds of services online. They, along with others focused squarely on the identity and verification space (and Truework works with some of them), and using a myriad of approaches that include biometrics, ‘wallet’-style passports that link to information elsewhere, and more, will all continue to try to make the case for why they might be the most trusted provider of that layer of information, at a time when we may want to share less and especially share less with multiple parties.
That is the bigger opportunity that investors are betting on here.
“The increasing momentum Truework has seen since its founding in 2017 demonstrates the critical need for transformation in this space,” said Alfred Lin, partner at Sequoia, in a statement. “Privacy, especially around identity data, is becoming increasingly top of mind for consumers and how they make transactions online.”
Truework has now raised close to $45 million, and it’s not disclosing its valuation.
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