Personal blog of Yzmir Ramirez

APIs are the grease turning the gears and wheels for many organizations’ IT systems today, but as APIs grow in number and use, tracking how they work (or don’t work) together can become complex and potentially critical if something goes awry. Now, a startup that has built an innovative way to help with this is announcing some funding after getting traction with big enterprises adopting its approach.

Tyk, which has built a way for users to access and manage multiple internal enterprise APIs through a universal interface by way of GraphQL, has picked up $35 million, an investment that it will be using both for hiring and to continue enhancing and expanding the tools that it provides to users. Tyk has coined a term describing its approach to managing APIs and the data they produce — “universal data graph” — and today its tools are being used to manage APIs by some 10,000 businesses, including large enterprises like Starbucks, Societe Generale and Domino’s.

Scottish Equity Partners led the round, with participation also from MMC Ventures — its sole previous investor from a round in 2019 after boostrapping for its first five years. The startup is based out of London but works in a very distributed way — one of the co-founders is living in New Zealand currently — and it will be hiring and growing based on that principle, too. It has raised just over $40 million to date.

Tyk (pronounced like “tyke”, meaning small/lively child) got its start as an open source side project first for co-founder Martin Buhr, who is now the company’s CEO, while he was working elsewhere, as a “load testing thing,” in his words.

The shifts in IT toward service-oriented architectures, and building and using APIs to connect internal apps, led him to rethink the code and consider how it could be used to control APIs. Added to that was the fact that as far as Buhr could see, the API management platforms that were in the market at the time — some of the big names today include Kong, Apigee (now a part of Google), 3scale (now a part of RedHat and thus IBM), MuleSoft (now a part of Salesforce) — were not as flexible as his needs were. “So I built my own,” he said.

It was built as an open source tool, and some engineers at other companies started to use it. As it got more attention, some of the bigger companies interested in using it started to ask why he wasn’t charging for anything — a sure sign as any that there was probably a business to be built here, and more credibility to come if he charged for it.

“So we made the gateway open source, and the management part went into a licensing model,” he said. And Tyk was born as a startup co-founded with James Hirst, who is now the COO, who worked with Buhr at a digital agency some years before.

The key motivation behind building Tyk has stayed as its unique selling point for customers working in increasingly complex environments.

“What sparked interest in Tyk was that companies were unhappy with API management as it exists today,” Buhr noted, citing architectures using multiple clouds and multiple containers, creating more complexity that needed better management. “It was just the right time when containerization, Kubernetes and microservices were on the rise… The way we approach the multi-data and multi-vendor cloud model is super flexible and resilient to partitions, in a way that others have not been able to do.”

“You engage developers and deliver real value and it’s up to them to make the choice,” added Hirst. “We are responding to a clear shift in the market.”

One of the next frontiers that Tyk will tackle will be what happens within the management layer, specifically when there are potential conflicts with APIs.

“When a team using a microservice makes a breaking change, we want to bring that up and report that to the system,” Buhr said. “The plan is to flag the issue and test against it, and be able to say that a schema won’t work, and to identify why.”

Even before that is rolled out, though, Tyk’s customer list and its growth speak to a business on the cusp of a lot more.

“Martin and James have built a world-class team and the addition of this new capital will enable Tyk to accelerate the growth of its API management platform, particularly around the GraphQL focused Universal Data Graph product that launched earlier this year,” said Martin Brennan, a director at SEP, in a statement. “We are pleased to be supporting the team to achieve their global ambitions.”

Keith Davidson, a partner at SEP, is joining the Tyk board as a non-executive director with this round.

In less than a year after raising $25 million in Series B funding, technical assessment company CodeSignal announced a $50 million in Series C funding to offer new features for its platform that helps companies make data-driven hiring decisions to find and test engineering talent.

Similar to attracting a big investor lead for its B round — Menlo Ventures — it has partnered with Index Ventures to lead the C round. Menlo participated again and was joined by Headline and A Capital. This round brings CodeSignal’s total fundraising to $87.5 million.

Co-founder and CEO Tigran Sloyan got the idea for the company from an experience his co-founder and friend Aram Shatakhtsyan had while trying to find an engineering job. Both from Armenia, the two went in different paths for college, with Shatakhtsyan staying in Armenia and Sloyan coming to the U.S. to study at MIT. He then went on to work at Google.

“As companies were recruiting myself and my classmates, Aram was trying to get his resume picked up, but wasn’t getting attention because of where he went to college, even though he was the greatest programmer I had ever known,” Sloyan told TechCrunch. “Hiring talent is the No. 1 problem companies say they have, but here was the best engineer, and no one would bring him in.”

They, along with Sophia Baik, started CodeSignal in 2015 to act as a self-driving interview platform that directly measures skills regardless of a person’s background. Like people needing to take a driver’s test in order to get a license, Sloyan calls the company’s technical assessment technology a “flight simulator for developers,” that gives candidates a simulated evaluation of their skills and comes back with a score and highlighted strengths.

The need by companies to hire engineers has led to CodeSignal growing 3.5 times in revenue year over year and to gather a customer list that includes Brex, Databricks, Facebook, Instacart, Robinhood, Upwork and Zoom.

Sloyan said the company has not yet touched the money it received in its Series B, but wanted to jump at the opportunity to work with Nina Achadjian, partner at Index Ventures, whom he had known for many years since their time together at Google. To work together and for Achadjian to join the company’s board was something “I couldn’t pass up,” Sloyan said.

When Achadjian moved over to venture capital, she helped Sloyan connect to mentors and angel investors while keeping an eye on the company. Hiring engineers is “mission critical” for technology companies, but what became more obvious to her was that engineering functions have become necessary for all companies, Achadjian explained.

While performing due diligence on the space, she saw traditional engineering cultures utilizing CodeSignal, but then would also see nontraditional companies like banks and insurance companies.

“Their traction was undeniable, and many of our portfolio companies were using CodeSignal,” she added. “It is rare to see a company accelerate growth at the stage they are at.”

U.S. Department of Labor statistics estimate there is already a global talent labor shortage of 40 million workers, and that number will grow to over 85 million by 2030. Achadjian says engineering jobs are also expected to increase during that time, and with all of those roles and applicants, vetting candidates will be more important than ever, as will the ability for candidates to apply from wherever they are.

The new funding enabled the company to launch its Integrated Development Environment for candidates to interact with relevant assessment experiences like codes, files and a terminal on a machine that is familiar with them, so that they can showcase their skills, while also being able to preview their application. At the same time, employers are able to assign each candidate the same coding task based on the open position.

In addition, Sloyan intends to triple the company’s headcount over the next couple of months and expand into other use cases for skills assessment.

Employee location has become a bit more complicated as some return to the office, while others work remotely. To embrace those hybrid working conditions, Google is making more changes to its Google Workspace offering by going live with spaces in Google Chat for all users.

Spaces integrates with Workspace tools, like the calendar, Drive and documents, to provide a more hybrid work experience where users can see the full history, content and context of conversations, regardless of their location.

Google’s senior director of product management, Sanaz Ahari, wrote in a blog post Wednesday that customers wanted spaces to be more like a “central hub for collaboration, both in real time and asynchronously. Instead of starting an email chain or scheduling a video meeting, teams can come together directly in a space to move projects and topics along.”

Here are some new features users can see in spaces:

• One interface for everything — inbox, chats, spaces and meetings.
• Spaces, and content therein, can be made discoverable for people to find and join in the conversation.
• Better search ability within a team’s knowledge base.
• Ability to reply to any message within a space.
• Enhanced security and admin tools to monitor communication.

Employees can now indicate if they will be virtual or in-person on certain days in Calendar for collaboration expectations. As a complement, users can call colleagues on both mobile and desktop devices in Google Meet.

Calendar work location. Image Credits: Google

In November, all customers will be able to use Google Meet’s Companion Mode to join a meeting from a personal device while tapping into in-room audio and video. Also later this year, live-translated captions will be available in English to French, German, Portuguese and Spanish, with more languages being added in the future.

In addition, Google is also expanding its Google Meet hardware portfolio to include two new all-in-one video conferencing devices, third-party devices — Logitech’s video bar and Appcessori’s mobile device speaker dock — and interoperability with Webex by Cisco.

Google is tying everything together with a handbook for navigating hybrid work, which includes best practice blueprints for five common hybrid meetings.

UiPath came seemingly out of nowhere in the last several years, going public last year in a successful IPO during which it raised more than $527 million. It raised $2 billion in private money prior to that with its final private valuation coming in at an amazing $35 billion. UiPath CEO Daniel Dines will be joining us on a panel to discuss automation at TC Sessions: SaaS on October 27th.

The company has been able to capture all this investor attention doing something called robotic process automation (RPA), which provides a way to automate a series of highly mundane tasks. It has become quite popular, especially to help bring a level of automation to legacy systems that might not be able to handle more modern approaches to automation involving artificial intelligence and machine learning. In 2019 Gartner found that RPA was the fastest growing category in enterprise software.

In point of fact, UiPath didn’t actually come out of nowhere. It was founded in 2005 as a consulting company and transitioned to software over the years. The company took its first VC funding, a modest $1.5 million seed round, in 2015, according to Crunchbase data.

As RPA found its market, the startup began to take off, raising gobs of money, including a $568 million round in April 2019 and $750 million in its final private raise in February 2021.

Dines will be appearing on a panel discussing the role of automation in the enterprise. Certainly, the pandemic drove home the need for increased automation as masses of office workers moved to work from home, a trend that is likely to continue even after the pandemic slows.

As the RPA market leader, he is uniquely positioned to discuss how this software and other similar types will evolve in the coming years and how it could combine with related trends like no-code and process mapping. Dines will be joined on the panel by investor Laela Sturdy from CapitalG and ServiceNow’s Dave Wright, where they will discuss the state of the automation market, why it’s so hot and where the next opportunities could be.

In addition to our discussion with Dines, the conference will also include Databricks’ Ali Ghodsi, Salesforce’s Kathy Baxter and Puppet’s Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope you’ll join us. It’s going to be a stimulating day.

Buy your pass now to save up to $100. We can’t wait to see you in October!

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Seattle-based Edge Delta, a startup that is building a modern distributed monitoring stack that is competing directly with industry heavyweights like Splunk, New Relic and Datadog, today announced that it has raised a $15 million Series A funding round led by Menlo Ventures and Tim Tully, the former CTO of Splunk. Previous investors MaC Venture Capital and Amity Ventures also participated in this round, which brings the company’s total funding to date to $18 million.

“Our thesis is that there’s no way that enterprises today can continue to analyze all their data in real time,” said Edge Delta co-founder and CEO Ozan Unlu, who has worked in the observability space for about 15 years already (including at Microsoft and Sumo Logic). “The way that it was traditionally done with these primitive, centralized models — there’s just too much data. It worked 10 years ago, but gigabytes turned into terabytes and now terabytes are turning into petabytes. That whole model is breaking down.”

Image Credits: Edge Delta

He acknowledges that traditional big data warehousing works quite well for business intelligence and analytics use cases. But that’s not real-time and also involves moving a lot of data from where it’s generated to a centralized warehouse. The promise of Edge Delta is that it can offer all of the capabilities of this centralized model by allowing enterprises to start to analyze their logs, metrics, traces and other telemetry right at the source. This, in turn, also allows them to get visibility into all of the data that’s generated there, instead of many of today’s systems, which only provide insights into a small slice of this information.

While competing services tend to have agents that run on a customer’s machine, but typically only compress the data, encrypt it and then send it on to its final destination, Edge Delta’s agent starts analyzing the data right at the local level. With that, if you want to, for example, graph error rates from your Kubernetes cluster, you wouldn’t have to gather all of this data and send it off to your data warehouse where it has to be indexed before it can be analyzed and graphed.

With Edge Delta, you could instead have every single node draw its own graph, which Edge Delta can then combine later on. With this, Edge Delta argues, its agent is able to offer significant performance benefits, often by orders of magnitude. This also allows businesses to run their machine learning models at the edge, as well.

Image Credits: Edge Delta

“What I saw before I was leaving Splunk was that people were sort of being choosy about where they put workloads for a variety of reasons, including cost control,” said Menlo Ventures’ Tim Tully, who joined the firm only a couple of months ago. “So this idea that you can move some of the compute down to the edge and lower latency and do machine learning at the edge in a distributed way was incredibly fascinating to me.”

Edge Delta is able to offer a significantly cheaper service, in large part because it doesn’t have to run a lot of compute and manage huge storage pools itself since a lot of that is handled at the edge. And while the customers obviously still incur some overhead to provision this compute power, it’s still significantly less than what they would be paying for a comparable service. The company argues that it typically sees about a 90 percent improvement in total cost of ownership compared to traditional centralized services.

Image Credits: Edge Delta

Edge Delta charges based on volume and it is not shy to compare its prices with Splunk’s and does so right on its pricing calculator. Indeed, in talking to Tully and Unlu, Splunk was clearly on everybody’s mind.

“There’s kind of this concept of unbundling of Splunk,” Unlu said. “You have Snowflake and the data warehouse solutions coming in from one side, and they’re saying, ‘hey, if you don’t care about real time, go use us.’ And then we’re the other half of the equation, which is: actually there’s a lot of real-time operational use cases and this model is actually better for those massive stream processing datasets that you required to analyze in real time.”

But despite this competition, Edge Delta can still integrate with Splunk and similar services. Users can still take their data, ingest it through Edge Delta and then pass it on to the likes of Sumo Logic, Splunk, AWS’s S3 and other solutions.

Image Credits: Edge Delta

“If you follow the trajectory of Splunk, we had this whole idea of building this business around IoT and Splunk at the Edge — and we never really quite got there,” Tully said. “I think what we’re winding up seeing collectively is the edge actually means something a little bit different. […] The advances in distributed computing and sophistication of hardware at the edge allows these types of problems to be solved at a lower cost and lower latency.”

The Edge Delta team plans to use the new funding to expand its team and support all of the new customers that have shown interest in the product. For that, it is building out its go-to-market and marketing teams, as well as its customer success and support teams.

Vantage, a service that helps businesses analyze and reduce their AWS costs, today announced that it has raised a $4 million seed round led by Andreessen Horowitz. A number of angel investors, including Brianne Kimmel, Julia Lipton, Stephanie Friedman, Calvin French Owen, Ben and Moisey Uretsky, Mitch Wainer and Justin Gage, also participated in this round.

Vantage started out with a focus on making the AWS console a bit easier to use — and helping businesses figure out what they are spending their cloud infrastructure budgets on in the process. But as Vantage co-founder and CEO Ben Schaechter told me, it was the cost transparency features that really caught on with users.

“We were advertising ourselves as being an alternative AWS console with a focus on developer experience and cost transparency,” he said. “What was interesting is — even in the early days of early access before the formal GA launch in January — I would say more than 95% of the feedback that we were getting from customers was entirely around the cost features that we had in Vantage.”

Image Credits: Vantage

Like any good startup, the Vantage team looked at this and decided to double down on these features and highlight them in its marketing, though it kept the existing AWS Console-related tools as well. The reason the other tools didn’t quite take off, Schaechter believes, is because more and more, AWS users have become accustomed to infrastructure-as-code to do their own automatic provisioning. And with that, they spend a lot less time in the AWS Console anyway.

“But one consistent thing — across the board — was that people were having a really, really hard time 12 times a year, where they would get a shocking AWS bill and had to figure out what happened. What Vantage is doing today is providing a lot of value on the transparency front there,” he said.

Over the course of the last few months, the team added a number of new features to its cost transparency tools, including machine learning-driven predictions (both on the overall account level and service level) and the ability to share reports across teams.

Image Credits: Vantage

While Vantage expects to add support for other clouds in the future, likely starting with Azure and then GCP, that’s actually not what the team is focused on right now. Instead, Schaechter noted, the team plans to add support for bringing in data from third-party cloud services instead.

“The number one line item for companies tends to be AWS, GCP, Azure,” he said. “But then, after that, it’s Datadog, Cloudflare, Sumo Logic, things along those lines. Right now, there’s no way to see, P&L or an ROI from a cloud usage-based perspective. Vantage can be the tool where that’s showing you essentially, all of your cloud costs in one space.”

That is likely the vision the investors bought into, as well, and even though Vantage is now going up against enterprise tools like Apptio’s Cloudability and VMware’s CloudHealth, Schaechter doesn’t seem to be all that worried about the competition. He argues that these are tools that were born in a time when AWS had only a handful of services and only a few ways of interacting with those. He believes that Vantage, as a modern self-service platform, will have quite a few advantages over these older services.

“You can get up and running in a few clicks. You don’t have to talk to a sales team. We’re helping a large number of startups at this stage all the way up to the enterprise, whereas Cloudability and CloudHealth are, in my mind, kind of antiquated enterprise offerings. No startup is choosing to use those at this point, as far as I know,” he said.

The team, which until now mostly consisted of Schaechter and his co-founder and CTO Brooke McKim, bootstrapped the company up to this point. Now they plan to use the new capital to build out its team (and the company is actively hiring right now), both on the development and go-to-market side.

The company offers a free starter plan for businesses that track up to $2,500 in monthly AWS cost, with paid plans starting at $30 per month for those who need to track larger accounts.

Honeywell, which only recently announced its entry into the quantum computing race, and Cambridge Quantum Computing (CQ), which focuses on building software for quantum computers, today announced that they are combining Honeywell’s Quantum Solutions (HQS) business with Cambridge Quantum in the form of a new joint venture.

Honeywell has long partnered with CQ and invested in the company last year, too. The idea here is to combine Honeywell’s hardware expertise with CQ’s software focus to build what the two companies call “the world’s highest-performing quantum computer and a full suite of quantum software, including the first and most advanced quantum operating system.”

The merged companies (or ‘combination,’ as the companies’ press releases calls it) expect the deal to be completed in the third quarter of 2021. Honeywell Chairman and CEO Darius Adamczyk will become the chairman of the new company. CQ founder and CEO Ilyas Khan will become the CEO and current Honeywell Quantum Solutions President Tony Uttley will remain in this role at the new company.

The idea here is for Honeywell to spin off HQS and combine it with CQC to form a new company, while still playing a role in its leadership and finances. Honeywell will own a majority stake in the new company and invest between $270 and $300 million. It will also have a long-term agreement with the new company to build the ion traps at the core of its quantum hardware. CQ’s shareholders will own 45% of the new company.

Image Credits: Honeywell

“The new company will have the best talent in the industry, the world’s highest-performing quantum computer, the first and most advanced quantum operating system, and comprehensive, hardware-agnostic software that will drive the future of the quantum computing industry,” said Adamczyk. “The new company will be extremely well positioned to create value in the near-term within the quantum computing industry by offering the critical global infrastructure needed to support the sector’s explosive growth.”

The companies argue that a successful quantum business will need to be supported by large-scale investments and offer a one-stop shop for customers that combines hardware and software. By combining the two companies now, they note, they’ll be able to build on their respective leadership positions in their areas of expertise and scale their businesses while also accelerate their R&D and product roadmaps.

“Since we first announced Honeywell’s quantum business in 2018, we have heard from many investors who have been eager to invest directly in our leading technologies at the forefront of this exciting and dynamic industry – now, they will be able to do so,” Adamczyk said. “The new company will provide the best avenue for us to onboard new, diverse sources of capital at scale that will help drive rapid growth.”

CQ launched in 2014 and now has about 150 employees. The company raised a total of $72.8 million, including a $45 million round, which it announced last December. Honeywell, IBM Ventures, JSR Corporation, Serendipity Capital, Alvarium Investments and Talipot Holdings invested in this last round — which also means that IBM, which uses a different technology but, in many ways, directly competes with the new company, now owns a (small) part of it.

At its (virtual) Build conference today, Microsoft launched a number of new features, tools and services for developers who want to integrate their services with Teams, the company’s Slack competitor. It’s no secret that Microsoft basically looks at Teams, which now has about 145 million daily active users, as the new hub for employees to get work done, so it’s no surprise that it wants third-party developers to bring their services right to Teams as well. And to do so, it’s now offering a set of new tools that will make this easier and enable developers to build new user experiences in Teams.

There’s a lot going on here, but maybe the most important news is the launch of the enhanced Microsoft Teams Toolkit for Visual Studio and Visual Studio Code.

“This essentially enables developers to build apps easier and faster — and to build very powerful apps tapping into the rich Microsoft stack,” Microsoft group program manager Archana Saseetharan explained. “With the updated toolkit […], we enable flexibility for developers. We want to meet developers where they are.”

Image Credits: Microsoft

The toolkit offers support for tools and frameworks like React, SharePoint and .NET. Some of the updates the team enabled with this release are integration with Aure Functions, the SharePoint Framework integration and a single-line integration with the Microsoft Graph. Microsoft is also making it easier for developers to integrate an authorization workflow into their Teams apps. “Login is the first kind of experience of any user with an app — and most of the drop-offs happen there,” Saseetharan said. “So [single-sign on] is something we completely are pushing hard on.”

The team also launched a new Developer Portal for Microsoft Teams that makes it easier for developers to register and configure their apps from a single tool. ISVs will also be able to use the new portal to offer their apps for in-Teams purchases.

Other new Teams features for developers include ways for developers to build real-time multi-user experiences like whiteboards and project boards, for example, as well as a new meeting event API to build meeting-related workflows for when a meeting starts and ends, for example, as well as new features for the Teams Together mode that will let developers design their own Together experiences.

There are a few other new features here as well, but what it all comes down to is that Microsoft wants developers to consider Teams as a viable platform for their services — and with 145 million daily active users, that’s potentially a lucrative way for software firms to get their services in front of a new audience.

“Teams is enabling a new class of apps called collaborative apps,” said Karan Nigam, Microsoft’s director of product marketing for Teams. “We are uniquely positioned to bring the richness to the collaboration space — a ton of innovation to the extensibility side to make apps richer, making it easier with the toolkit update, and then have a single-stop shop with the developer portal where the entire lifecycle can be managed. Ultimately, for a developer, they don’t have to go to multiple places, it’s one single flow from the business perspective for them as well.”

There may be billions of IoT devices in use today, but the tooling around building (and updating) the software for them still leaves a lot to be desired. Esper, which today announced that it has raised a $30 million Series B round, builds the tools to enable developers and engineers to deploy and manage fleets of Android-based edge devices. The round was led by Scale Venture Partners, with participation from Madrona Venture Group, Root Ventures, Ubiquity Ventures and Haystack.

The company argues that there are thousands of device manufacturers who are building these kinds of devices on Android alone, but that scaling and managing these deployments comes with a lot of challenges. The core idea here is that Esper brings to device development the DevOps experience that software developers now expect. The company argues that its tools allow companies to forgo building their own internal DevOps teams and instead use its tooling to scale their Android-based IoT fleets for use cases that range from digital signage and kiosks to custom solutions in healthcare, retail, logistics and more.

“The pandemic has transformed industries like connected fitness, digital health, hospitality, and food delivery, further accelerating the adoption of intelligent edge devices. But with each new use case, better software automation is required,” said Yadhu Gopalan, CEO and co-founder at Esper. “Esper’s mature cloud infrastructure incorporates the functionality cloud developers have come to expect, re-imagined for devices.”

Image Credits: Esper

Mobile device management (MDM) isn’t exactly a new thing, but the Esper team argues that these tools weren’t created for this kind of use case. “MDMs are the solution now in the market. They are made for devices being brought into an environment,” Gopalan said. “The DNA of these solutions is rooted in protecting the enterprise and to deploy applications to them in the network. Our customers are sending devices out into the wild. It’s an entirely different use case and model.”

To address these challenges, Esper offers a range of tools and services that includes a full development stack for developers, cloud-based services for device management and hardware emulators to get started with building custom devices.

“Esper helped us launch our Fusion-connected fitness offering on three different types of hardware in less than six months,” said Chris Merli, founder at Inspire Fitness. “Their full stack connected fitness Android platform helped us test our application on different hardware platforms, configure all our devices over the cloud, and manage our fleet exactly to our specifications. They gave us speed, Android expertise, and trust that our application would provide a delightful experience for our customers.”

The company also offers solutions for running Android on older x86 Windows devices to extend the life of this hardware, too.

“We spent about a year and a half on building out the infrastructure,” said Gopalan. “Definitely. That’s the hard part and that’s really creating a reliable, robust mechanism where customers can trust that the bits will flow to the devices. And you can also roll back if you need to.”

Esper is working with hardware partners to launch devices that come with built-in Esper-support from the get-go.

Esper says it saw 70x revenue growth in the last year, an 8x growth in paying customers and a 15x growth in devices running Esper. Since we don’t know the baseline, those numbers are meaningless, but the investors clearly believe that Esper is on to something. Current customers include the likes of CloudKitchens, Spire Health, Intelity, Ordermark, Inspire Fitness, RomTech and Uber.

At Google I/O today Google Cloud announced Vertex AI, a new managed machine learning platform that is meant to make it easier for developers to deploy and maintain their AI models. It’s a bit of an odd announcement at I/O, which tends to focus on mobile and web developers and doesn’t traditionally feature a lot of Google Cloud news, but the fact that Google decided to announce Vertex today goes to show how important it thinks this new service is for a wide range of developers.

The launch of Vertex is the result of quite a bit of introspection by the Google Cloud team. “Machine learning in the enterprise is in crisis, in my view,” Craig Wiley, the director of product management for Google Cloud’s AI Platform, told me. “As someone who has worked in that space for a number of years, if you look at the Harvard Business Review or analyst reviews, or what have you — every single one of them comes out saying that the vast majority of companies are either investing or are interested in investing in machine learning and are not getting value from it. That has to change. It has to change.”

Image Credits: Google

Wiley, who was also the general manager of AWS’s SageMaker AI service from 2016 to 2018 before coming to Google in 2019, noted that Google and others who were able to make machine learning work for themselves saw how it can have a transformational impact, but he also noted that the way the big clouds started offering these services was by launching dozens of services, “many of which were dead ends,” according to him (including some of Google’s own). “Ultimately, our goal with Vertex is to reduce the time to ROI for these enterprises, to make sure that they can not just build a model but get real value from the models they’re building.”

Vertex then is meant to be a very flexible platform that allows developers and data scientist across skill levels to quickly train models. Google says it takes about 80% fewer lines of code to train a model versus some of its competitors, for example, and then help them manage the entire lifecycle of these models.

Image Credits: Google

The service is also integrated with Vizier, Google’s AI optimizer that can automatically tune hyperparameters in machine learning models. This greatly reduces the time it takes to tune a model and allows engineers to run more experiments and do so faster.

Vertex also offers a “Feature Store” that helps its users serve, share and reuse the machine learning features and Vertex Experiments to help them accelerate the deployment of their models into producing with faster model selection.

Deployment is backed by a continuous monitoring service and Vertex Pipelines, a rebrand of Google Cloud’s AI Platform Pipelines that helps teams manage the workflows involved in preparing and analyzing data for the models, train them, evaluate them and deploy them to production.

To give a wide variety of developers the right entry points, the service provides three interfaces: a drag-and-drop tool, notebooks for advanced users and — and this may be a bit of a surprise — BigQuery ML, Google’s tool for using standard SQL queries to create and execute machine learning models in its BigQuery data warehouse.

“We had two guiding lights while building Vertex AI: get data scientists and engineers out of the orchestration weeds, and create an industry-wide shift that would make everyone get serious about moving AI out of pilot purgatory and into full-scale production,” said Andrew Moore, vice president and general manager of Cloud AI and Industry Solutions at Google Cloud. “We are very proud of what we came up with in this platform, as it enables serious deployments for a new generation of AI that will empower data scientists and engineers to do fulfilling and creative work.”