IDC: Asia-Pacific spending on AI systems will reach $5.5 billion this year, up 80 percent from 2018

Spending on artificial intelligence systems in the Asia-Pacific region is expected to reach $5.5 billion this year, an almost 80 percent increase over 2018, driven by businesses in China and the retail industry, according to IDC. In a new report, the research firm also said it expects AI spending to climb at a compound annual growth rate of 50 percent from 2018 to 2022, reaching a total of $15.06 billion in 2022.

This means AI spending growth in the Asia-Pacific region is expected to outpace the rest of the world over the next three years. In March, IDC forecast that worldwide spending on AI systems is expected to grow at a CAGR of 38 percent between 2018 to 2022.

Most of the growth will happen in China, which IDC says will account for nearly two-thirds of AI spending in the region, excluding Japan, in all forecast years. Spending on AI systems will be driven by retail, professional services and government industries.

Retail demand for AI-based tools will also lead growth in the rest of the region, as companies begin to rely on it more for merchandising, product recommendations, automated customer service and supply and logistics. While the banking industry’s AI spending trails behind retail, it will also begin adopting the tech for fraud analysis, program advisors, recommendations and customer service. IDC forecasts that this year, companies will invest almost $700 million in automated service agents. The next largest area for investment is sales process recommendations and automation, with $450 million expected, and intelligent process automation at more than $350 million.

The fastest-growing industries for AI spending are expected to be healthcare (growing at 60.2 percent CAGR) and process manufacturing (60.1 percent CAGR). In terms of infrastructure, IDC says spending on hardware, including servers and storage, will reach almost $7 billion in 2019, while spending on software is expected to grow at a five-year CAGR of 80 percent.


By Catherine Shu

Under the hood on Zoom’s IPO, with founder and CEO Eric Yuan

Extra Crunch offers members the opportunity to tune into conference calls led and moderated by the TechCrunch writers you read every day. This week, TechCrunch’s Kate Clark sat down with Eric Yuan, the founder and CEO of video communications startup Zoom, to go behind the curtain on the company’s recent IPO process and its path to the public markets.

Since hitting the trading desks just a few weeks ago, Zoom stock is up over 30%. But the Zoom’s path to becoming a Silicon Valley and Wall Street darling was anything but easy. Eric tells Kate how the company’s early focus on profitability, which is now helping drive the stock’s strong performance out of the gate, actually made it difficult to get VC money early on, and the company’s consistent focus on user experience led to organic growth across different customer bases.

Eric: I experienced the year 2000 dot com crash and the 2008 financial crisis, and it almost wiped out the company. I only got seed money from my friends, and also one or two VCs like AME Cloud Ventures and Qualcomm Ventures.

nd all other institutional VCs had no interest to invest in us. I was very paranoid and always thought “wow, we are not going to survive next week because we cannot raise the capital. And on the way, I thought we have to look into our own destiny. We wanted to be cash flow positive. We wanted to be profitable.

nd so by doing that, people thought I wasn’t as wise, because we’d probably be sacrificing growth, right? And a lot of other companies, they did very well and were not profitable because they focused on growth. And in the future they could be very, very profitable.

Eric and Kate also dive deeper into Zoom’s founding and Eric’s initial decision to leave WebEx to work on a better video communication solution. Eric also offers his take on what the future of video conferencing may look like in the next five to 10 years and gives advice to founders looking to build the next great company.

For access to the full transcription and the call audio, and for the opportunity to participate in future conference calls, become a member of Extra Crunch. Learn more and try it for free. 

Kate Clark: Well thanks for joining us Eric.

Eric Yuan: No problem, no problem.

Kate: Super excited to chat about Zoom’s historic IPO. Before we jump into questions, I’m just going to review some of the key events leading up to the IPO, just to give some context to any of the listeners on the call.


By Arman Tabatabai

Health[at]Scale lands $16M Series A to bring machine learning to healthcare

Health[at]Scale, a startup with founders who have both medical and engineering expertise, wants to bring machine learning to bear on healthcare treatment options to produce outcomes with better results and less aftercare. Today the company announced a $16 million Series A. Optum, which is part of the UnitedHealth Group, was the sole investor .

Today, when people looks at treatment options, they may look at a particular surgeon or hospital, or simply what the insurance company will cover, but they typically lack the data to make truly informed decisions. This is true across every part of the healthcare system, particularly in the U.S. The company believes using machine learning, it can produce better results.

“We are a machine learning shop, and we focus on what I would describe as precision delivery. So in other words, we look at this question of how do we match patients to the right treatments, by the right providers, at the right time,” Zeeshan Syed, Health at Scale CEO told TechCrunch.

The founders see the current system as fundamentally flawed, and while they see their customers as insurance companies, hospital systems and self-insured employers; they say the tools they are putting into the system should help everyone in the loop get a better outcome.

The idea is to make treatment decisions more data driven. While they aren’t sharing their data sources, they say they have information from patients with a given condition, to doctors who treat that condition, to facilities where the treatment happens. By looking at a patient’s individual treatment needs and medical history, they believe they can do a better job of matching that person to the best doctor and hospital for the job. They say this will result in the fewest post-operative treatment requirements, whether that involves trips to the emergency room or time in a skilled nursing facility, all of which would end up adding significant additional cost.

If you’re thinking this is strictly about cost savings for these large institutions, Mohammed Saeed, who is the company’s chief medical officer and has and MD from Harvard and a PhD in electrical engineering from MIT, insists that isn’t the case. “From our perspective, it’s a win-win situation since we provide the best recommendations that have the patient interest at heart, but from a payer or provider perspective, when you have lower complication rates you have better outcomes and you lower your total cost of care long term,” he said.

The company says the solution is being used by large hospital systems and insurer customers, although it couldn’t share any. The founders also said, it has studied the outcomes after using its software and the machine learning models have produced better outcomes, although it couldn’t provide the data to back that up at that point at this time.

The company was founded in 2015 and currently has 11 employees. It plans to use today’s funding to build out sales and marketing to bring the solution to a wider customer set.


By Ron Miller

Unveiling its latest cohort, Alchemist announces $4 million in funding for its enterprise accelerator

The enterprise software and services-focused accelerator Alchemist has raised $4 million in fresh financing from investors BASF and the Qatar Development Bank, just in time for its latest demo day unveiling 20 new companies.

Qatar and BASF join previous investors, including the venture firms Mayfield, Khosla Ventures, Foundation Capital, DFJ and USVP, and corporate investors like Cisco, Siemens and Juniper Networks.

While the roster of successes from Alchemist’s fund isn’t as lengthy as Y Combinator, the accelerator program has launched the likes of the quantum computing upstart Rigetti, the soft-launch developer tool LaunchDarkly and drone startup Matternet .

Some (personal) highlights of the latest cohort include:

  • Bayware: Helmed by a former head of software-defined networking from Cisco, the company is pitching a tool that makes creating networks in multi-cloud environments as easy as copying and pasting.
  • MotorCortex.AI: Co-founded by a Stanford engineering professor and a Carnegie Mellon roboticist, the company is using computer vision, machine learning and robotics to create a fruit packer for packaging lines. Starting with avocados, the company is aiming to tackle the entire packaging side of pick and pack in logistics.
  • Resilio: With claims of a 96% effectiveness rate and $35,000 in annual recurring revenue with another $1 million in the pipeline, Resilio is already seeing companies embrace its mobile app that uses a phone’s camera to track stress levels and application-based prompts on how to lower it, according to Alchemist.
  • Operant Networks: It’s a long-held belief (of mine) that if computing networks are already irrevocably compromised, the best thing that companies and individuals can do is just encrypt the hell out of their data. Apparently Operant agrees with me. The company is claiming 50% time savings with this approach, and have booked $1.9 million in 2019 as proof, according to Alchemist.
  • HPC Hub: HPC Hub wants to democratize access to supercomputers by overlaying a virtualization layer and pre-installed software on underutilized super computers to give more companies and researchers easier access to machines… and they’ve booked $92,000 worth of annual recurring revenue.
  • DinoPlusAI: This chip developer is designing a low latency chip for artificial intelligence applications, reducing latency by 12 times over a competing Nvidia chip, according to the company. DinoPlusAI sees applications for its tech in things like real-time AI markets and autonomous driving. Its team is led by a designer from Cadence and Broadcom and the company already has $8 million in letters of intent signed, according to Alchemist.
  • Aero Systems West: Co-founders from the Air Force’s Research Labs and MIT are aiming to take humans out of drone operations and maintenance. The company contends that for every hour of flight time, drones require seven hours of maintenance and check ups. Aero Systems aims to reduce that by using remote analytics, self-inspection, autonomous deployment and automated maintenance to take humans out of the drone business.

Watch a live stream of Alchemist’s demo day pitches, starting at 3PM, here.

 


By Jonathan Shieber

Beyond costs, what else can we do to make housing affordable?

This week on Extra Crunch, I am exploring innovations in inclusive housing, looking at how 200+ companies are creating more access and affordability. Yesterday, I focused on startups trying to lower the costs of housing, from property acquisition to management and operations.

Today, I want to focus on innovations that improve housing inclusion more generally, such as efforts to pair housing with transit, small business creation, and mental rehabilitation. These include social impact-focused interventions, interventions that increase income and mobility, and ecosystem-builders in housing innovation.

Nonprofits and social enterprises lead many of these innovations. Yet because these areas are perceived to be not as lucrative, fewer technologists and other professionals have entered them. New business models and technologies have the opportunity to scale many of these alternative institutions — and create tremendous social value. Social impact is increasingly important to millennials, with brands like Patagonia having created loyal fan bases through purpose-driven leadership.

While each of these sections could be their own market map, this overall market map serves as an initial guide to each of these spaces.

Social impact innovations

These innovations address:


By Arman Tabatabai

Algorithmia raises $25M Series B for its AI automation platform

Algorithmia, a Seattle-based startup that offers a cloud-agnostic AI automation platform for enterprises, today announced a $25 million Series B funding round led by Norwest Partners. Madrona, Gradient Ventures, Work-Bench, Osage University Partners and Rakuten Ventures also participated in this round.

While the company started out five years ago as a marketplace for algorithms, it now mostly focuses on machine learning and helping enterprises take their models into production.

“It’s actually really hard to productionize machine learning models,” Algorithmia CEO Diego Oppenheimer told me. “It’s hard to help data scientists to not deal with data infrastructure but really being able to build out their machine learning and AI muscle.”

To help them, Algorithmia essentially built out a machine learning DevOps platform that allows data scientists to train their models on the platform and with the framework of their choice, bring it to Algorithmia — a platform that has already been blessed by their IT departments — and take it into production.

“Every Fortune 500 CIO has an AI initiative but they are bogged down by the difficulty of managing and deploying ML models,” said Rama Sekhar, a partner at Norwest Venture Partners, who has now joined the company’s board. “Algorithmia is the clear leader in building the tools to manage the complete machine learning lifecycle and helping customers unlock value from their R&D investments.”

With the new funding, the company will double down on this focus by investing in product development to solve these issues, but also by building out its team, with a plan to double its headcount over the next year. A year from now, Oppenheimer told me, he hopes that Algorithmia will be a household name for data scientists and, maybe more importantly, their platform of choice for putting their models into production.

“How does Algorithmia succeed? Algorithmia succeeds when our customers are able to deploy AI and ML applications,” Oppenheimer said. “And although there is a ton of excitement around doing this, the fact is that it’s really difficult for companies to do so.”

The company previously raised a $10.5 million Series A round led by Google’s AI fund. It’s customers now include the United Nations, a number of U.S. intelligence agencies and Fortune 500 companies. In total, over 90,000 engineers and data scientists are now on the platform.


By Frederic Lardinois

Announcing TechCrunch Sessions: Enterprise this September in San Francisco

Of the many categories in the tech world, none is more ferociously competitive than enterprise. For decades, SAP, Oracle, Adobe, Microsoft, IBM and Salesforce, to name a few of the giants, have battled to deliver the tools businesses want to become more productive and competitive. That market is closing in on $500 billion in sales per year, which explains why hundreds of new enterprise startups launch every year and dozens are acquired by the big incumbents trying to maintain their edge.

Last year alone, the top 10 enterprise acquisitions were worth $87 billion and included IBM’s acquiring Red Hat for $34 billion, SAP paying $8 billion for Qualtrics, Microsoft landing GitHub for $7.5 billion, Salesforce acquiring MuleSoft for $6.5 billion and Adobe grabbing Marketo for $4.75 billion. No startup category has made more VCs and founders wildly wealthy, and none has seen more mighty companies rise faster or fall harder. That technology and business thrill ride makes enterprise a category TechCrunch has long wanted to tackle head on.

TC Sessions: Enterprise (September 5 at San Francisco’s Yerba Buena Center) will take on the big challenges and promise facing enterprise companies today. TechCrunch’s editors, notably Frederic Lardinois, Ron Miller and Connie Loizos, will bring to the stage founders and leaders from established and emerging companies to address rising questions like the promised revolution from machine learning and AI, intelligent marketing automation and the inevitability of the cloud, as well as the outer reaches of technology, like quantum and blockchain.

We’ll enlist proven enterprise-focused VCs to reveal where they are directing their early, middle and late-stage investments. And we’ll ask the most proven serial entrepreneurs to tell us what it really took to build that company, and which company they would like to create next. All throughout the show, TechCrunch’s editors will zero in on emerging enterprise technologies to sort the hype from the reality. Whether you are a founder, an investor, enterprise-minded engineer or a corporate CTO / CIO, TC Sessions: Enterprise will provide a valuable day of new insights and great networking.

Tickets are now available for purchase on our website at the early-bird rate of $395. Want to bring a group of people from your company? Get an automatic 15% savings when you purchase four or more tickets at once. Are you an early-stage startup? We have a limited number of Startup Demo Packages available for $2,000, which includes four tickets to attend the event. Students are invited to apply for a reduced-price student ticket at just $245. Additionally, for each ticket purchased for TC Sessions: Enterprise, you will also be registered for a complimentary Expo Only pass to TechCrunch Disrupt SF on October 2-4.

Interested in sponsoring TC Sessions: Enterprise? Fill out this form and a member of our sales team will contact you.


By Alexandra Ames

Market map: the 200+ innovative startups transforming affordable housing

In this section of my exploration into innovation in inclusive housing, I am digging into the 200+ companies impacting the key phases of developing and managing housing.

Innovations have reduced costs in the most expensive phases of the housing development and management process. I explore innovations in each of these phases, including construction, land, regulatory, financing, and operational costs.

Reducing Construction Costs

This is one of the top three challenges developers face, exacerbated by rising building material costs and labor shortages.


By Arman Tabatabai

Innovations in inclusive housing

Housing is big money. The industry has trillions under management and hundreds of billions under development.

And investors have noticed the potential. Opendoor raised nearly $1.3 billion to help homeowners buy and sell houses more quickly. Katerra raised $1.2 billion to optimize building development and construction, and Compass raised the same amount to help brokers sell real estate better. Even Amazon and Airbnb have entered the fray with high-profile investments.

Amidst this frenetic growth is the seed of the next wave of innovation in the sector. The housing industry — and its affordability problem — is only likely to balloon. By 2030, 84% of the population of developed countries will live in cities.

Yet innovation in housing lags compared to those of other industries. In construction, a major aspect of housing development, players spend less than 1% of their revenues on research and development. Technology companies, like the Amazons of the world, spend nearly 10% on average.

Innovations in older, highly-regulated industries, like housing and real estate, are part of what Steve Case calls the “third wave” of technology. VCs like Case’s Revolution Fund and the SoftBank Vision Fund are investing billions into what they believe is the future.

These innovations are far from silver bullets, especially if they lack involvement from underrepresented communities, avoid policy, and ignore distributive questions about who gets to benefit from more housing.

Yet there are hundreds of interventions reworking housing that cannot be ignored. To help entrepreneurs, investors, and job seekers interested in creating better housing, I mapped these innovations in this package of articles.

To make sense of this broad field, I categorize innovations into two main groups, which I detail in two separate pieces on Extra Crunch. The first (Part 1) identifies the key phases of developing and managing housing. The second (Part 2) section identifies interventions that contribute to housing inclusion more generally, such as efforts to pair housing with transit, small business creation, and mental rehabilitation.

Unfortunately, many of these tools don’t guarantee more affordability. Lowering acquisition costs, for instance, doesn’t mean that renters or homeowners will necessarily benefit from those savings. As a result, some tools likely need to be paired with others to ensure cost savings that benefit end users — and promote long-term affordability. I detail efforts here so that mission-driven advocates as well as startup founders can adopt them for their own efforts.


Topics We Explore

Today:

Coming Tomorrow:

  • Part 2. Other contributions to housing affordability
    • Social Impact Innovations
    • Landlord-Tenant Tools
    • Innovations that Increase Income
    • Innovations that Increase Transit Accessibility and Reduce Parking
    • Innovations that Improve the Ability to Regulate Housing
    • Organizations that Support the Housing Innovation Ecosystem
  • This is Just the Beginning
  • I’m Personally Closely Watching the Following Initiatives.
  • The Limitations of Technology
  • Move Fast and Protect People


Please feel free to let me know what else is exciting by adding a note to your LinkedIn invite here.

If you’re excited about this topic, feel free to subscribe to my future of inclusive housing newsletter by viewing a past issue here.


By Arman Tabatabai

India’s Locus raises $22 million to expand its logistics management business

Locus, an Indian startup that uses AI to help businesses map out their logistics, has raised $22 million in Series B funding to expand its operations in international markets.

The financing round for the four-year-old startup was led by Falcon Edge Capital and Tiger Global Management . Existing investors Exfinity Venture Partners and Blume Ventures also participated in the round. The startup has raised $29 million to date, Nishith Rastogi, co-founder and CEO of Locus, told TechCrunch in an interview.

Locus works with companies that operate in FMCG, logistics, and e-commerce spaces. Some of its clients include Tata Group companies, Myntra, BigBasket, Lenskart, and Bluedart. It helps these clients automate their logistics workload — tasks such as planning, organizing, transporting and tracking of inventories, and finding the best path to reach a destination — that have traditionally required intensive human labor.

“Say a Lenskart representative is visiting a house or an office to offer an eye checkup, and suddenly two more people there are interested in getting their eyes checked. The representative could attend these two new potential clients, or wrap things up with the first client and take care of his or her next appointment,” said Rastogi.

Locus looks at a client’s past data, identifies patterns, and automates these kind of decisions on a large scale. In an example shared earlier with TechCrunch, Rastogi talked about how Locus had built a scanner for ecommerce companies for measuring products.

Rastogi said he will use the fresh capital to develop products and expand Locus in Southeast Asian and North American markets. The startup says half of its 110 people workforce is outside of India. Half of the IP it has built and the revenue it generates comes from its team outside of India.

He said the startup has spent the recent quarters studying these international markets, and has secured some anchor clients to expand the business. Locus is operationally profitable already and any additional capital goes into expanding its business, he added.

The logistics market in India has long been riddled with challenges. A growing number of startups, including BlackBuck — which raised $150 million last week — have emerged in recent years to tackle these problems.

The new funding also illustrates Tiger Global Management’s new strategy for the Indian market. The VC fund, which has invested in B2C businesses Flipkart and Ola in India, has made a number of investments in B2B startups in recent months. Last month, it invested $90 million in agri-tech supply chain startup Ninjacart, and weeks later, it gave cloud-based solutions provider Zenoti $50 million.


By Manish Singh

Cisco open sources MindMeld conversational AI platform

Cisco announced today that it was open sourcing the MindMeld conversation AI platform, making it available to anyone who wants to use it under the Apache 2.0 license.

MindMeld is the conversational AI company that Cisco bought in 2017. The company put the technology to use in Cisco Spark Assistant later that year to help bring voice commands to meeting hardware, which was just beginning to emerge at the time.

Today, there is a concerted effort to bring voice to enterprise use cases, and Cisco is offering the means for developers to do that with the MindMeld tool set. “Today, Cisco is taking a big step towards empowering developers with more comprehensive and practical tools for building conversational applications by open-sourcing the MindMeld Conversational AI Platform,” Cisco’s head of machine learning Karthik Raghunathanw wrote in a blog post.

The company also wants to make it easier for developers to get going with the platform, so it is releasing the Conversational AI Playbook, a step-by-step guide book to help developers get started with conversation-driven applications. Cisco says this is about empowering developers, and that’s probably a big part of the reason.

But it would also be in Cisco’s best interest to have developers outside of Cisco working with and on this set of tools. By open sourcing them, the hope is that a community of developers, whether Cisco customers or others, will begin using, testing and improving the tools; helping it to develop the platform faster and more broadly than it could, even inside an organization as large as Cisco.

Of course, just because they offer it doesn’t necessarily automatically mean the community of interested developers will emerge, but given the growing popularity of voice-enabled used cases, chances are some will give it a look. It will be up to Cisco to keep them engaged.

Cisco is making all of this available on its own DevNet platform starting today.


By Ron Miller

Microsoft wants you to work less

Microsoft today announced updates to its MyAnalytics platform and a new Outlook feature that are meant to help you work less, find more time to focus on the work that actually matters and, by extension, get more downtime.

Until now, for example, MyAnalytics, Microsoft’s tool for helping employees track their productivity, would provide you with a measure of how much time you spent working after hours. That’s not necessarily a healthy number to track. Going forward, MyAnalytics will track the number of days you managed to unplug after work and didn’t check your email or work on a document at 8pm (something Microsoft’s own PR department could learn from given that it has a tendency to provide essential press materials for next-day embargoes at 6:30pm). The idea here, obviously, is to get employees to focus on this number instead of how much they work when they are off the clock.

“Our customers often tell us they spend all day in meetings with little time to focus on pressing tasks and projects,” Microsoft communications chief Frank X. Shaw also noted in a press briefing ahead of today’s announcement.

To combat this, the company today launched a few new features that will let you set up regular ‘focus time.’ The first of this is a tool that lets you set up focus time each week, as well as a feature in Microsoft teams that will alert your fellow employees when you are trying to get things done.

Since your colleagues often don’t care about your flow, though, and are prone to scheduling yet another unnecessary meeting during those times, Microsoft is also launching a new AI-powered Outlook plugin that will help you rebook your focus time and find times for focusing on specific to-do items.

In the future, the company also plans to introduce well-being, networking and collaboration plans.

Focus plans will become available in preview in the next few months for Microsoft 365 and Office 365 users, with E5 customers getting them first.


By Frederic Lardinois

Microsoft launches a drag-and-drop machine learning tool

Microsoft today announced three new services that all aim to simplify the process of machine learning. These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users.

Getting started with machine learning is hard. Even to run the most basic of experiments take a good amount of expertise. All of these new tools great simplify this process by hiding away the code or giving those who want to write their own code a pre-configured platform for doing so.

The new interface for Azure’s automated machine learning tool makes creating a model as easy importing a data set and then telling the service which value to predict. Users don’t need to write a single line of code, while in the backend, this updated version now supports a number of new algorithms and optimizations that should result in more accurate models. While most of this is automated, Microsoft stresses that the service provides “complete transparency into algorithms, so developers and data scientists can manually override and control the process.”

For those who want a bit more control from the get-go, Microsoft also today launched a visual interface for its Azure Machine Learning service into preview that will allow developers to build, train and deploy machine learning models without having to touch any code.

This tool, the Azure Machine Learning visual interface looks suspiciously like the existing Azure ML Studio, Microsoft’s first stab at building a visual machine learning tool. Indeed, the two services look identical. The company never really pushed this service, though, and almost seemed to have forgotten about it despite that fact that it always seemed like a really useful tool for getting started with machine learning.

Microsoft says that this new version combines the best of Azure ML Studio with the Azure Machine Learning service. In practice, this means that while the interface is almost identical, the Azure Machine Learning visual interface extends what was possible with ML Studio by running on top of the Azure Machine Learning service and adding that services’ security, deployment and lifecycle management capabilities.

The service provides an easy interface for cleaning up your data, training models with the help of different algorithms, evaluating them and, finally, putting them into production.

While these first two services clearly target novices, the new hosted notebooks in Azure Machine Learning are clearly geared toward the more experiences machine learning practitioner. The notebooks come pre-packaged with support for the Azure Machine Learning Python SDK and run in what the company describes as a “secure, enterprise-ready environment.” While using these notebooks isn’t trivial either, this new feature allows developers to quickly get started without the hassle of setting up a new development environment with all the necessary cloud resources.


By Frederic Lardinois

Takeaways from F8 and Facebook’s next phase

Extra Crunch offers members the opportunity to tune into conference calls led and moderated by the TechCrunch writers you read every day. This week, TechCrunch’s Josh Constine and Frederic Lardinois discuss major announcements that came out of Facebook’s F8 conference and dig into how Facebook is trying to redefine itself for the future.

Though touted as a developer-focused conference, Facebook spent much of F8 discussing privacy upgrades, how the company is improving its social impact, and a series of new initiatives on the consumer and enterprise side. Josh and Frederic discuss which announcements seem to make the most strategic sense, and which may create attractive (or unattractive) opportunities for new startups and investment.

“This F8 was aspirational for Facebook. Instead of being about what Facebook is, and accelerating the growth of it, this F8 was about Facebook, and what Facebook wants to be in the future.

That’s not the newsfeed, that’s not pages, that’s not profiles. That’s marketplace, that’s Watch, that’s Groups. With that change, Facebook is finally going to start to decouple itself from the products that have dragged down its brand over the last few years through a series of nonstop scandals.”

(Photo by Justin Sullivan/Getty Images)

Josh and Frederic dive deeper into Facebook’s plans around its redesign, Messenger, Dating, Marketplace, WhatsApp, VR, smart home hardware and more. The two also dig into the biggest news, or lack thereof, on the developer side, including Facebook’s Ax and BoTorch initiatives.

For access to the full transcription and the call audio, and for the opportunity to participate in future conference calls, become a member of Extra Crunch. Learn more and try it for free. 


By Arman Tabatabai

SalesLoft nabs $70M at $500M valuation for its sales engagement platform

Artificial intelligence and other tech for automating some of the more repetitive aspects of human jobs continues to be a growing category of software, and today a company that builds tools to address this need for salespeople has raised a tidy sum to grow its business.

SalesLoft, an Atlanta-based startup that has built a platform for salespeople to help them engage with their clients — providing communications tools, supporting data, and finally analytics to ‘coach’ salespeople to improve their processes — has raised $70 million in a Series D round of funding led by Insight Venture Partners with participation from HarbourVest.

Kyle Porter, SalesLoft’s co-founder and CEO, would not disclose the amount of funding in an interview but he did confirm that it is double its valuation from the previous round, a $50 million Series C that included LinkedIn among the investors (more on that below). That round was just over a year ago and would have valued the firm at $250 million. That would put SalesLoft’s current valuation at about $500 million.

While there are a number of CRM and sales tools out in the market today, Porter believes that many of the big ones might better be described as “dumb databases or repositories” of information rather than natively aimed at helping source and utilise data more effectively.

“They are not focused on improving how to connect buyers to sales teams in sincere ways,” he said. “And anytime a company like Salesforce has moved into tangential areas like these, they haven’t built from the ground up, but through acquisitions. It’s just hard to move giant aircraft carriers.”

SalesLoft is not the only one that has spotted this opportunity, of course. There are dozens of others that are either competing on single or all aspects of the same services that SalesLoft provides, including the likes of Clari, Chorus.ai, Gong, Conversica, Afiniti and not least Outreach — which is seen as a direct competitor on sales engagement and itself raised $114 million on a $1.1 billion valuation earlier this month.

One of the notable distinctions for SalesLoft is that one of its strategic investors is LinkedIn, which participated in its Series C. Before Microsoft acquired it, LinkedIn was seen as a potential competitor to SalesForce, and many thought that Microsoft’s acquisition was made squarely to help it compete against the CRM giant.

These days, Porter said that his company and LinkedIn have a tight integration by way of LinkedIn’s Sales Navigator product, which SalesLoft users can access and utilise directly within SalesLoft, and they have a hotline to be apprised of and help shape LinkedIn’s API developments. SalesLoft is also increasingly building links into Microsoft Dynamics, the company’s CRM business.

“We are seeing the highest usage in our LinkedIn integration among all the other integrations we provide,” Porter told me. “Our customers find that it’s the third most important behind email and phone calls.” Email, for all its cons, remains the first.

The fact that this is a crowded area of the market does speak to the opportunity and need for something effective, however, and the fact that SalesLoft has grown revenues 100 percent in each of the last two years, according to Porter, makes it a particularly attractive horse to bet on.

“So many software companies build a product to meet a market need and then focus purely on selling. SalesLoft is different. This team is continually innovating, pushing the boundaries, and changing the face of sales,” said Jeff Horing, co-founder and MD of Insight Venture Partners, in a statement. “This is one reason the company’s customers are so devoted to them. We are privileged to partner with this innovative company on their mission to improve selling experiences all over the world.”

Going forward, Porter said that in addition to expanding its footprint globally — recent openings include a new office in London — the company is going to go big on more AI and “intelligence” tools. The company already offers something it calls its “coaching network” which is not human but AI-based and analyses calls as they happen to provide pointers and feedback after the fact (similar to others like Gong and Chorus, I should note).

“We want to give people a better way to deliver an authentic but ultimately human way to sell,” he said.


By Ingrid Lunden