By Ron Miller
October 11, 2020
By Ron Miller
October 9, 2020
By Ingrid Lunden
October 8, 2020
By Ron Miller
October 8, 2020
By Ingrid Lunden
October 8, 2020
Grid AI raises $18.6M Series A to help AI researchers and engineers bring their models to production
By Frederic Lardinois
October 8, 2020
By Ron Miller
October 7, 2020
By Anthony Ha
October 7, 2020
By Frederic Lardinois
October 7, 2020
By Ron Miller
October 7, 2020
We have heard from a couple of industry sources that the deal is in the works and could be announced as early as Monday.
Twilio and Segment are both API companies. That means they create an easy way for developers to tap into a specific type of functionality without writing a lot of code. As I wrote in a 2017 article on Segment, it provides a set of APIs to pull together customer data from a variety of sources:
Segment has made a name for itself by providing a set of APIs that enable it to gather data about a customer from a variety of sources like your CRM tool, customer service application and website and pull that all together into a single view of the customer, something that is the goal of every company in the customer information business.
While Twilio’s main focus since it launched in 2008 has been on making it easy to embed communications functionality into any app, it signaled a switch in direction when it released the Flex customer service API in March 2018. Later that same year, it bought SendGrid, an email marketing API company for $2 billion.
Twilio’s market cap as of Friday was an impressive $45 billion. You could see how it can afford to flex its financial muscles to combine Twilio’s core API mission, especially Flex, with the ability to pull customer data with Segment and create customized email or ads with SendGrid.
This could enable Twilio to expand beyond pure core communications capabilities and it could come at the cost of around $5 billion for the two companies, a good deal for what could turn out to be a substantial business as more and more companies look for ways to understand and communicate with their customers in more relevant ways across multiple channels.
As Semil Shah from early stage VC firm Haystack wrote in the company blog yesterday, Segment saw a different way to gather customer data, and Twilio was wise to swoop in and buy it.
Segment’s belief was that a traditional CRM wasn’t robust enough for the enterprise to properly manage its pipe. Segment entered to provide customer data infrastructure to offer a more unified experience. Now under the Twilio umbrella, Segment can continue to build key integrations (like they have for Twilio data), which is being used globally inside Fortune 500 companies already.
Segment was founded in 2011 and raised over $283 million, according to Crunchbase data. Its most recent raise was $175 million in April on a $1.5 billion valuation.
Twilio stock closed at $306.24 per share on Friday up $2.39%.
Segment declined to comment on this story. We also sent a request for comment to Twilio, but hadn’t heard back by the time we published. If that changes, we will update the story.
By Ron Miller
Picture yourself in the role of CIO at Roblox in 2017.
At that point, the gaming platform and publishing system that launched in 2005 was growing fast, but its underlying technology was aging, consisting of a single data center in Chicago and a bunch of third-party partners, including AWS, all running bare metal (nonvirtualized) servers. At a time when users have precious little patience for outages, your uptime was just two nines, or less than 99% (five nines is considered optimal).
Unbelievably, Roblox was popular in spite of this, but the company’s leadership knew it couldn’t continue with performance like that, especially as it was rapidly gaining in popularity. The company needed to call in the technology cavalry, which is essentially what it did when it hired Dan Williams in 2017.
Williams has a history of solving these kinds of intractable infrastructure issues, with a background that includes a gig at Facebook between 2007 and 2011, where he worked on the technology to help the young social network scale to millions of users. Later, he worked at Dropbox, where he helped build a new internal network, leading the company’s move away from AWS, a major undertaking involving moving more than 500 petabytes of data.
When Roblox approached him in mid-2017, he jumped at the chance to take on another major infrastructure challenge. While they are still in the midst of the transition to a new modern tech stack today, we sat down with Williams to learn how he put the company on the road to a cloud-native, microservices-focused system with its own network of worldwide edge data centers.
Scoping the problem
By Ron Miller
Videoconferencing has become a cornerstone of how many of us work these days — so much so that one leading service, Zoom, has graduated into verb status because of how much it’s getting used.
But does that mean videoconferencing works as well as it should? Today, a new startup called Headroom is coming out of stealth, tapping into a battery of AI tools — computer vision, natural language processing and more — on the belief that the answer to that question is a clear — no bad WiFi interruption here — “no.”
Headroom not only hosts videoconferences, but then provides transcripts, summaries with highlights, gesture recognition, optimised video quality, and more, and today it’s announcing that it has raised a seed round of $5 million as it gears up to launch its freemium service into the world.
You can sign up to the waitlist to pilot it, and get other updates here.
The funding is coming from Anna Patterson of Gradient Ventures (Google’s AI venture fund); Evan Nisselson of LDV Capital (a specialist VC backing companies buidling visual technologies); Yahoo founder Jerry Yang, now of AME Cloud Ventures; Ash Patel of Morado Ventures; Anthony Goldbloom, the cofounder and CEO of Kaggle.com; and Serge Belongie, Cornell Tech associate dean and Professor of Computer Vision and Machine Learning.
It’s an interesting group of backers, but that might be because the founders themselves have a pretty illustrious background with years of experience using some of the most cutting-edge visual technologies to build other consumer and enterprise services.
Julian Green — a British transplant — was most recently at Google, where he ran the company’s computer vision products, including the Cloud Vision API that was launched under his watch. He came to Google by way of its acquisition of his previous startup Jetpac, which used deep learning and other AI tools to analyze photos to make travel recommendations. In a previous life, he was one of the co-founders of Houzz, another kind of platform that hinges on visual interactivity.
Russian-born Andrew Rabinovich, meanwhile, spent the last five years at Magic Leap, where he was the head of AI, and before that, the director of deep learning and the head of engineering. Before that, he too was at Google, as a software engineer specializing in computer vision and machine learning.
You might think that leaving their jobs to build an improved videoconferencing service was an opportunistic move, given the huge surge of use that the medium has had this year. Green, however, tells me that they came up with the idea and started building it at the end of 2019, when the term “Covid-19” didn’t even exist.
“But it certainly has made this a more interesting area,” he quipped, adding that it did make raising money significantly easier, too. (The round closed in July, he said.)
Given that Magic Leap had long been in limbo — AR and VR have proven to be incredibly tough to build businesses around, especially in the short- to medium-term, even for a startup with hundreds of millions of dollars in VC backing — and could have probably used some more interesting ideas to pivot to; and that Google is Google, with everything tech having an endpoint in Mountain View, it’s also curious that the pair decided to strike out on their own to build Headroom rather than pitch building the tech at their respective previous employers.
Green said the reasons were two-fold. The first has to do with the efficiency of building something when you are small. “I enjoy moving at startup speed,” he said.
And the second has to do with the challenges of building things on legacy platforms versus fresh, from the ground up.
“Google can do anything it wants,” he replied when I asked why he didn’t think of bringing these ideas to the team working on Meet (or Hangouts if you’re a non-business user). “But to run real-time AI on video conferencing, you need to build for that from the start. We started with that assumption,” he said.
All the same, the reasons why Headroom are interesting are also likely going to be the ones that will pose big challenges for it. The new ubiquity (and our present lives working at home) might make us more open to using video calling, but for better or worse, we’re all also now pretty used to what we already use. And for many companies, they’ve now paid up as premium users to one service or another, so they may be reluctant to try out new and less-tested platforms.
But as we’ve seen in tech so many times, sometimes it pays to be a late mover, and the early movers are not always the winners.
The first iteration of Headroom will include features that will automatically take transcripts of the whole conversation, with the ability to use the video replay to edit the transcript if something has gone awry; offer a summary of the key points that are made during the call; and identify gestures to help shift the conversation.
And Green tells me that they are already also working on features that will be added into future iterations. When the videoconference uses supplementary presentation materials, those can also be processed by the engine for highlights and transcription too.
And another feature will optimize the pixels that you see for much better video quality, which should come in especially handy when you or the person/people you are talking to are on poor connections.
“You can understand where and what the pixels are in a video conference and send the right ones,” he explained. “Most of what you see of me and my background is not changing, so those don’t need to be sent all the time.”
All of this taps into some of the more interesting aspects of sophisticated computer vision and natural language algorithms. Creating a summary, for example, relies on technology that is able to suss out not just what you are saying, but what are the most important parts of what you or someone else is saying.
And if you’ve ever been on a videocall and found it hard to make it clear you’ve wanted to say something, without straight-out interrupting the speaker, you’ll understand why gestures might be very useful.
But they can also come in handy if a speaker wants to know if he or she is losing the attention of the audience: the same tech that Headroom is using to detect gestures for people keen to speak up can also be used to detect when they are getting bored or annoyed and pass that information on to the person doing the talking.
“It’s about helping with EQ,” he said, with what I’m sure was a little bit of his tongue in his cheek, but then again we were on a Google Meet, and I may have misread that.
And that brings us to why Headroom is tapping into an interesting opportunity. At their best, when they work, tools like these not only supercharge videoconferences, but they have the potential to solve some of the problems you may have come up against in face-to-face meetings, too. Building software that actually might be better than the “real thing” is one way of making sure that it can have staying power beyond the demands of our current circumstances (which hopefully won’t be permanent circumstances).
By Ingrid Lunden
When IBM announced this morning that it was spinning out its legacy infrastructure services business, it was a clear signal that new CEO Arvand Krishna, who took the reins in April, was ready to fully commit his company to the cloud.
The move was a continuation of the strategy the company began to put in place when it bought Red Hat in 2018 for the princely sum of $34 billion. That purchase signaled a shift to a hybrid-cloud vision, where some of your infrastructure lives on-premises and some in the cloud — with Red Hat helping to manage it all.
Even as IBM moved deeper into the hybrid cloud strategy, Krishna saw the financial results like everyone else and recognized the need to focus more keenly on that approach. In its most recent earnings report overall IBM revenue was $18.1 billion, down 5.4% compared to the year-ago period. But if you broke out just IBM’s cloud and Red Hat revenue, you saw some more promising results: cloud revenue was up 30 percent to $6.3 billion, while Red Hat-derived revenue was up 17%.
Even more, cloud revenue for the trailing 12 months was $23.5 billion, up 20%.
You don’t need to be a financial genius to see where the company is headed. Krishna clearly saw that it was time to start moving on from the legacy side of IBM’s business, even if there would be some short-term pain involved in doing so. So the executive put his resources into (as they say) where the puck is going. Today’s news is a continuation of that effort.
The managed infrastructure services segment of IBM is a substantial business in its own right, but Krishna was promoted to CEO to clean house, taking over from Ginni Rometti to make hard decisions like this.
While its cloud business is growing, Synergy Research data has IBM public cloud market share mired in single digits with perhaps 4 or 5%. In fact, Alibaba has passed its market share, though both are small compared to the market leaders Amazon, Microsoft and Google.
Like Oracle, another legacy company trying to shift more to the cloud infrastructure business, IBM has a ways to go in its cloud evolution.
As with Oracle, IBM has been chasing the market leaders — Google at 9%, Microsoft 18% and AWS with 33% share of public cloud revenue (according to Synergy) — for years now without much change in its market share. What’s more, IBM competes directly with Microsoft and Google, which are also going after that hybrid cloud business with more success.
While IBM’s cloud revenue is growing, its market share needle is stuck and Krishna understands the need to focus. So, rather than continue to pour resources into the legacy side of IBM’s business, he has decided to spin out that part of the company, allowing more attention for the favored child, the hybrid cloud business.
It’s a sound strategy on paper, but it remains to be seen if it will have a material impact on IBM’s growth profile in the long run. He is betting that it will, but then what choice does he have?
By Ron Miller
IBM, a company that originally made its name out of its leadership in building a myriad of enterprise hardware (quite literally: its name is an abbreviation for International Business Machines), is taking one more step away from that legacy and deeper into the world of cloud services. The company today announced that it plans to spin off its managed infrastructure services unit, a $19 billion business, to help it focus more squarely on newer opportunities in hybrid cloud applications and artificial intelligence.
Infrastrucuture services includes a range of services based around legacy infrastructure and digital transformation related to it. It includes things like testing and assembly, but also product engineering and lab services, among other things. A spokesperson confirmed to me that the deal will not include the company’s servers business, only infrastructure services.
IBM said it expects to complete the process — a tax-free spinoff for shareholders — by the end of 2021. It has not yet given a name to “NewCo” but it said that out of the gate the spun off company will have 90,000 employees, 4,600 big enterprise clients in 115 countries, a backlog of $60 billion in business, “and more than twice the scale of its nearest competitor” in the area of infrastructure services. Others that compete against it include the likes of BMC and Microsoft.
At the same time that IBM announced the news, it also gave some updated guidance for Q3, which it plans to report officially later this month. It said it expects revenues of $17.6 billion, with GAAP diluted earnings per share from continuing operations of $1.89, and operating (non-GAAP) earnings per share of $2.58. As a point of comparison, in Q3 2019 it reported higher revenues of $18 billion. Last quarter it had revenues of $18.1 billion. Tellingly, the divisions that contained infrastructure services saw declines last quarter.
The market seems to like the news: IBM shares are trading up almost 5% ahead of the market opening.
The move is a significant shift for the company and underscores a bigger sea change in how enterprise IT has evolved and looks to continue changing in the future.
IBM is betting that legacy infrastructure and the servicing of it, while continuing to net revenues, will not grow as it has in the past, and as companies continue with their modernization (or “digital transformation,” as consultants like to refer to it today), they will turn increasingly to outsourced infrastructure and using cloud services, both to run their businesses and to build the services that interface with consumers.
IBM, often referred to as “Big Blue”, is using the announcement as the start of an effort to streamline its business to spur growth (maybe we’ll have to rename it “Medium Blue.”).
“IBM is laser-focused on the $1 trillion hybrid cloud opportunity,” said Arvind Krishna, IBM CEO, in a statement. “Client buying needs for application and infrastructure services are diverging, while adoption of our hybrid cloud platform is accelerating. Now is the right time to create two market-leading companies focused on what they do best. IBM will focus on its open hybrid cloud platform and AI capabilities. NewCo will have greater agility to design, run and modernize the infrastructure of the world’s most important organizations. Both companies will be on an improved growth trajectory with greater ability to partner and capture new opportunities –creating value for clients and shareholders.”
Its purchase of Red Hat in 2019 is perhaps its most notable investment in recent times in IBM’s own transformation.
“We have positioned IBM for the new era of hybrid cloud,” said Ginni Rometty, IBM Executive Chairman in a statement. “Our multi-year transformation created the foundation for the open hybrid cloud platform, which we then accelerated with the acquisition of Red Hat. At the same time, our managed infrastructure services business has established itself as the industry leader, with unrivaled expertise in complex and mission-critical infrastructure work. As two independent companies, IBM and NewCo will capitalize on their respective strengths. IBM will accelerate clients’digital transformation journeys, and NewCo will accelerate clients’infrastructure modernization efforts. This focus will result in greater value, increased innovation, and faster execution for our clients.”
More to come.
By Ingrid Lunden
Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute.
Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.
The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.
“Now the industry has an unhealthy aversion to deep learning because of this,” Falcon noted. “Lightning and Grid embed all those tricks into the workflow so you no longer need to be a PhD in AI nor [have] the resources of the major AI companies to get these things to work. This makes the opportunity cost of putting a simple model against a sophisticated neural network a few hours’ worth of effort instead of the months it used to take. When you use Lightning and Grid it’s hard to make mistakes. It’s like if you take a bad photo with your phone but we are the phone and make that photo look super professional AND teach you how to get there on your own.”
As Falcon noted, Grid is meant to help data scientists and other ML professionals “scale to match the workloads required for enterprise use cases.” Lightning itself can get them partially there, but Grid is meant to provide all of the services its users need to scale up their models to solve real-world problems.
What exactly that looks like isn’t quite clear yet, though. “Imagine you can find any GitHub repository out there. You get a local copy on your laptop and without making any code changes you spin up 400 GPUs on AWS — all from your laptop using either a web app or command-line-interface. That’s the Lightning “magic” applied to training and building models at scale,” Falcon said. “It is what we are already known for and has proven to be such a successful paradigm shift that all the other frameworks like Keras or TensorFlow, and companies have taken notice and have started to modify what they do to try to match what we do.”
The service is now in private beta.
With this new funding, Grid, which currently has 25 employees, plans to expand its team and strengthen its corporate offering via both Grid AI and through the open-source project. Falcon tells me that he aims to build a diverse team, not in the least because he himself is an immigrant, born in Venezuela, and a U.S. military veteran.
“I have first-hand knowledge of the extent that unethical AI can have,” he said. “As a result, we have approached hiring our current 25 employees across many backgrounds and experiences. We might be the first AI company that is not all the same Silicon Valley prototype tech-bro.”
“Lightning’s open-source traction piqued my interest when I first learned about it a year ago,” Index Ventures’ Sarah Cannon told me. “So intrigued in fact I remember rushing into a closet in Helsinki while at a conference to have the privacy needed to hear exactly what Will and Luis had built. I promptly called my colleague Bryan Offutt who met Will and Luis in SF and was impressed by the ‘elegance’ of their code. We swiftly decided to participate in their seed round, days later. We feel very privileged to be part of Grid’s journey. After investing in seed, we spent a significant amount with the team, and the more time we spent with them the more conviction we developed. Less than a year later and pre-launch, we knew we wanted to lead their Series A.”
By Frederic Lardinois
Most startup founders have a tough road to their first round of funding, but the founders of Digital Brain had it a bit tougher than most. The two young founders survived by entering and winning hackathons to pay their rent and put on food on the table. One of the ideas they came up with at those hackathons was DigitalBrain, a layer that sits on top of customer service software like Zendesk to streamline tasks and ease the job of customer service agents.
They ended up in Y Combinator in the Summer 2020 class, and today the company announced a $3.4 million seed investment. This total includes $3 million raised this round, which closed in August, and previously unannounced investments of $250,000 in March from Unshackled Ventures and $150,000 from Y Combinator in May.
The round was led by Moxxie Ventures with help from Caffeinated Capital, Unshackled Ventures, Shrug Capital, Weekend Fund, Underscore VC and Scribble Ventures along with a slew of individual investors.
Company co-founder Kesava Kirupa Dinakaran says that after he and his partner Dmitry Dolgopolov met at hackathon in May 2019, they moved into a community house in San Francisco full of startup founders. They kept hearing from their housemates about the issues their companies faced with customer service as they began scaling. Like any good entrepreneur, they decided to build something to solve that problem.
“DigitalBrain is an external layer that sits on top of existing help desk software to actually help the support agents get through their tickets twice as fast, and we’re doing that by automating a lot of internal workflows, and giving them all the context and information they need to respond to each ticket making the experience of responding to these tickets significantly faster,” Dinakaran told TechCrunch.
What this means in practice is that customer service reps work in DigitalBrain to process their tickets, and as they come upon a problem such as canceling an order or reporting a bug, instead of traversing several systems to fix it, they chose the appropriate action in DigitalBrain, enter the required information, and the problem is resolved for them automatically. In the case of a bug, it would file a Jira ticket with engineering. In the case of canceling an order, it would take all of the actions and update all of the records required by this request.
As Dinakaran points out they aren’t typical Silicon Valley startup founders. They are 20 year old immigrants from India and Russia respectively, who came to the U.S. with coding skills and a dream of building a company. “We are both outsiders to Silicon Valley. We didn’t go to college. We don’t come from families of means. We wanted to come here and build our initial network from ground up,” he said.
Eventually they met some folks through their housemates, who suggested that they apply to Y Combinator. “As we started to meet people that we met through our community house here, some of them were YC founders and they kept saying I think you guys will love the YC community, not just in terms of your ethos, but also just purely from a perspective of meeting new people and where you are,” he said.
He said while he and his co-founder have trouble wrapping their arms around a number like the amount they have in the bank now, considering it wasn’t that long ago that they struggling to meet expenses every month, they recognize this money buys them an opportunity to help start building a more substantial company.
“What we’re trying to do is really accelerate the development and building of what we’re doing. And we think if we push the gas pedal with the resources we’ve gotten, we’ll be able to accelerate bringing on the next couple of customers, and start onboarding some of the larger companies we’re interested in,” he said.
By Ron Miller
There are four main products, starting with DashPass for Work, where employers can fund employee memberships to DashPass, a program that eliminates delivery fees on orders from thousands of restaurants. In fact, DoorDash says it already worked with Mt. Sinai to offer free DashPass subscriptions to 42,000 healthcare employees, and that other DashPass for Work customers include Charles Schwab, Hulu and Stanford Research Park.
DoorDash for Work also includes the ability for employers to provide credits for meal orders — there are options for day and time restrictions, so employers can be sure they’re paying for food while someone is working. For teams that are working in-person, there’s the ability to combine individual meal orders into a larger group orders. And the service also includes employee gift cards (Zoom, for example, is providing these on employee birthdays).
In a blog post, Broderick McClinton, the head of DoorDash for Work, noted that COVID-19 has had “a profound impact on our daily routines, including the way we eat.”
“Instead of meeting our favorite barista on the way into the office or socializing with our colleagues in the lunch room, we’re spending a lot more time in the kitchen and eating solo at home, missing out on those moments to engage with peers and support our favorite restaurants,” McClinton wrote. “In this new normal, companies are adapting and looking for ways to support their employees’ wellbeing and productivity through new work-from-home corporate wellness benefits, including food perks.
While free food might seem relatively low on the list of priorities during the pandemic (at least for those of us who have been fortunate enough to keep our jobs), DoorDash says it conducted a survey of 1,000 working Americans last month and found that 90% of them said they miss at least one food-related benefit from the office.
So DoorDash for Work is designed to help employers continue offering benefits in this area, and also it opens up a new source of revenue for DoorDash.
By Anthony Ha
At its (virtual) Kong Summit 2020, API platform Kong today announced the launch of Kong Konnect, its managed end-to-end cloud-native connectivity platform. The idea here is to give businesses a single service that allows them to manage the connectivity between their APIs and microservices and help developers and operators manage their workflows across Kong’s API Gateway, Kubernetes Ingress and King Service Mesh runtimes.
“It’s a universal control plane delivery cloud that’s consumption-based, where you can manage and orchestrate API gateway runtime, service mesh runtime, and Kubernetes Ingress controller runtime — and even Insomnia for design — all from one platform,” Kong CEO and co-founder Augusto ‘Aghi’ Marietti told me.
The new service is now in private beta and will become generally available in early 2021.
At the core of the platform is Kong’s new so-called ServiceHub, which provides that single pane of glass for managing a company’s services across the organization (and make them accessible across teams, too).
As Marietti noted, organizations can choose which runtime they want to use and purchase only those capabilities of the service that they currently need. The platform also includes built-in monitoring tools and supports any cloud, Kubernetes provider or on-premises environment, as long as they are Kubernetes-based.
The idea here, too, is to make all these tools accessible to developers and not just architects and operators. “I think that’s a key advantage, too,” Marietti said. “We are lowering the barrier by making a connectivity technology easier to be used by the 50 million developers — not just by the architects that were doing big grand plans at a large company.”
To do this, Konnect will be available as a self-service platform, reducing the friction of adopting the service.
This is also part of the company’s grander plan to go beyond its core API management services. Those services aren’t going away, but they are now part of the larger Kong platform. With its open-source Kong API Gateway, the company built the pathway to get to this point, but that’s a stable product now and it’s now clearly expanding beyond that with this cloud connectivity play that takes the company’s existing runtimes and combines them to provide a more comprehensive service.
“We have upgraded the vision of really becoming an end-to-end cloud connectivity company,” Marietti said. “Whether that’s API management or Kubernetes Ingress, […] or Kuma Service Mesh. It’s about connectivity problems. And so the company uplifted that solution to the enterprise.”
By Frederic Lardinois
It seems that no-code is the tech watchword of the year. It refers to the ability to create something that normally would require a developer to code, and replace it with dragging and dropping components instead, putting the task in reach of much less technical business users. Today Okta announced new no-code workflows that provide a way to use identity as a trigger to launch a customer-centric workflow.
Okta co-founder and CEO Todd McKinnon says that the company has created a series of connectors to make it easier to connect identity to a workflow that includes sales and marketing tooling. This comes on the heels of the identity lifecycle workflows, the company introduced at the Oktane customer conference in April.
“For this release we are introducing customer identity workflows which are focused on the connectors for all the customer-specific systems, things like Salesforce and Marketo and all the customer-centric [applications] that you’d want to do with your customer identities. And you can imagine over time that we’re going to expose this to more and more areas that will cover every kind of scenario a company would want to use,” McKinnon told TechCrunch.
McKinnon says that last year the company introduced Platform Services, which pulled apart the various pieces of the platform and exposed them as individual services, which bigger company customers could tap into as needed. He says that this is an extension of that idea, but instead of having to get engineering talent to write complex code to tie the Okta service into say Salesforce, you can simply drag the Salesforce connector to your workflow.
As McKinnon describes this using early adopter MLB as an example, say someone downloads the MLB app, creates a log-in and signs in. At that point, if MLB marketing personnel wanted to connect to any applications outside of Okta, it would normally require leveraging some programming help to make it happen.
But with the new workflow tools, a marketing person can set up a workflow that checks the log-in for fraud, then sends the person’s information automatically into Salesforce to create a customer record, and also triggers a welcome email in Marketo — and all of this could be done automatically triggered by the customer sign up.
This functionality was made possible by the $52.5 million acquisition of Azuqua last year. As COO and co-founder Frederic Kerrest wrote in a blog post at the time of the acquisition (and we quoted in the article):
“With Okta and Azuqua, IT teams will be able to use pre-built connectors and logic to create streamlined identity processes and increase operational speed. And, product teams will be able to embed this technology in their own applications alongside Okta’s core authentication and user management technology to build…integrated customer experiences.”
And that’s precisely the kind of approach the company is delivering this week. For now, it’s available as an early adopter program, but as Okta works out the kinks, you can expect them to build on this and add other enterprise workflow connectors to the mix as it expands this vision, giving the company a way to move beyond pure identity management and connect to other parts of the organization.
By Ron Miller