Jul
23
2019
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Google updates its speech tech for contact centers

Last July, Google announced its Contact Center AI product for helping businesses get more value out of their contact centers. Contact Center AI uses a mix of Google’s machine learning-powered tools to help build virtual agents and help human agents as they do their job. Today, the company is launching several updates to this product that will, among other things, bring improved speech recognition features to the product.

As Google notes, its automated speech recognition service gets to very high accuracy rates, even on the kind of noisy phone lines that many customers use to complain about their latest unplanned online purchase. To improve these numbers, Google is now launching a feature called “Auto Speech Adaptation in Dialogflow,” (with Dialogflow being Google’s tool for building conversational experiences). With this, the speech recognition tools are able to take into account the context of the conversation and hence improve their accuracy by about 40%, according to Google.

Speech Recognition Accuracy

In addition, Google is launching a new phone model for understanding short utterances, which is now about 15% more accurate for U.S. English, as well as a number of other updates that improve transcription accuracy, make the training process easier and allow for endless audio streaming to the Cloud Speech-to-Text API, which previously had a five-minute limit.

If you want to, you also can now natively download MP3s of the audio (and then burn them to CDs, I guess).

dialogflow virtual agent.max 1100x1100

Jul
23
2019
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CircleCI closes $56M Series D investment as market for continuous delivery expands

CircleCI launched way back in 2011 when the notion of continuous delivery was just a twinkle in most developers’ eyes, but over the years with the rise of agile, containerization and DevOps, we’ve seen the idea of continuous integration and continuous delivery (CI/CD) really begin to mainstream with developers. Today, CircleCI was rewarded with a $56 million Series D investment.

The round was led by Owl Rock Capital Partners and Next Equity. Existing investors Scale Venture Partners, Top Tier Capital, Threshold Ventures (formerly DFJ), Baseline Ventures, Industry Ventures, Heavybit and Harrison Metal Capital also participated in the round. CircleCI’s most recent funding prior to this round was a $31 million Series C last January. Today’s investment brings the total raised to $115.5 million, according to the company.

CircleCI CEO Jim Rose sees a market that’s increasingly ready for the product his company is offering. “As we’re putting more money to work, there are just more folks that are now moving away from aspiring about doing continuous delivery and really leaning into the idea of, ‘We’re a software company, we need to know how to do this well, and we need to be able to automate all the steps between the time our developers are making changes to the code until that application gets in front of the customer,’ ” Rose told TechCrunch.

Rose sees a market that’s getting ready to explode and he wants to use the runway this money provides his company to take advantage of that growth. “Now, what we’re finding is that fintech companies, insurance companies, retailers — all of the more traditional brands — are now realizing they’re in a software business as well. And they’re really trying to build out the tool sets and the expertise to be effective at that. And so the real growth in our market is still right in front of us,” he said.

As CircleCI matures and the market follows suit, a natural question following a Series D investment is when the company might go public, but Rose was not ready to commit to anything yet. “We come at it from the perspective of keeping our heads down trying to build the best business and doing right by our customers. I’m sure at some point along the journey our investors will be itching for liquidity, but as it stands right now, everyone is really [focused]. I think what we have found is that the bulk of the market is just starting to arrive,” he said.

Jul
22
2019
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Google Cloud makes it easier to set up continuous delivery with Spinnaker

Google Cloud today announced Spinnaker for Google Cloud Platform, a new solution that makes it easier to install and run the Spinnaker continuous delivery (CD) service on Google’s cloud.

Spinnaker was created inside Netflix and is now jointly developed by Netflix and Google. Netflix open-sourced it back in 2015 and over the course of the last few years, it became the open-source CD platform of choice for many enterprises. Today, companies like Adobe, Box, Cisco, Daimler, Samsung and others use it to speed up their development process.

With Spinnaker for Google Cloud Platform, which runs on the Google Kubernetes Engine, Google is making the install process for the service as easy as a few clicks. Once up and running, the Spinnaker install includes all of the core tools, as well as Deck, the user interface for the service. Users pay for the resources used by the Google Kubernetes Engine, as well as Cloud Memorystore for Redis, Google Cloud Load Balancing and potentially other resources they use in the Google Cloud.

could spinnker.max 1100x1100

The company has pre-configured Spinnaker for testing and deploying code on Google Kubernetes Engine, Compute Engine and App Engine, though it also will work with any other public or on-prem cloud. It’s also integrated with Cloud Build, Google’s recently launched continuous integration service, and features support for automatic backups and integrated auditing and monitoring with Google’s Stackdriver.

“We want to make sure that the solution is great both for developers and DevOps or SRE teams,” says Matt Duftler, tech lead for Google’s Spinnaker effort, in today’s announcement. “Developers want to get moving fast with the minimum of overhead. Platform teams can allow them to do that safely by encoding their recommended practice into Spinnaker, using Spinnaker for GCP to get up and running quickly and start onboard development teams.”

 

Jul
22
2019
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Serverless, Inc. expands free Framework to include monitoring and security

Serverless development has largely been a lonely pursuit until recently, but Serverless, Inc. has been offering a free framework for intrepid programmers since 2015. At first, that involved development, deployment and testing, but today the company announced it is expanding into monitoring and security to make it an end-to-end tool — and it’s available for free.

Serverless computing isn’t actually server-free, but it’s a form of computing that provides a way to use only the computing resources you need to carry out a given function — and no more. When the process is complete, the resources effectively go away. That has the potential to be more cost-effective than having a server that’s always on, regardless of whether you’re using it or not. That requires a new way of thinking about how developers write code.

While serverless offers a compelling value proposition, up until Serverless, Inc. came along with some developer tooling, early adherents were pretty much stuck building their own tooling to develop, deploy and test their programs. Today’s announcement expands the earlier free Serverless, Inc. Framework to provide a more complete set of serverless developer tools.

Company founder and CEO Austen Collins says that he has been thinking a lot about what developers need to develop and deploy serverless programs, and talking to customers. He says that they really craved a more integrated approach to serverless development than has been available until now.

“What we’re trying to do is build this perfectly integrated solution for developers and developer teams because we want to enable them to innovate as much as possible and be as autonomous as possible,” Collins told TechCrunch. He says at the same time, he recognizes that operations need to connect to other tools, and the Serverless Framework provides hooks into other systems, as well.

Screenshot 2019 07 22 09.27.24

The new tooling includes an integrated environment, so that once you deploy, you can simply click an error or security event and drill down to a dashboard for more information about the issue. You can click for further detail to see the exact spot in the code where the issue occurred, which should make it easier to resolve more quickly.

While no tool is 100% comprehensive, and most large organizations, and even individual developers, will have a set of tools they prefer to use, this is an attempt to build a one-stop solution for serverless developers for the first time. That in itself is significant, as serverless moves beyond early adopters and begins to become more of a mainstream kind of programming and deployment option. People starting now probably won’t want to cobble together their own toolkits, and the Serverless, Inc. Framerwork gives them a good starting point.

Serverless, Inc. was founded by Collins in 2015 out of a need for serverless computing tooling. He has raised more than $13.5 million since inception.

Jul
22
2019
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Slack speeds up its web and desktop client

Slack is launching a major update to its web and desktop today that doesn’t introduce any new features or a new user interface. Instead, it’s almost a complete rebuild of the underlying technology that makes these two experiences work. Over the course of the last year or so, Slack worked on shifting the web and desktop clients (which essentially use the same codebase) to a modern stack and away from jQuery and other technologies it used when it first introduced these tools in 2012.

“We want people to be able to run Slack alongside anything else they’re using to get their job done and have that be easy, uncumbersome, delightful even. So we took a look at the environment we’re in,” Jaime DeLanghe, director of Product Management at Slack, told me. “I think the other thing to note is that the ecosystem for client-side development has just changed a lot in the past five years. There have been some major updates to JavaScript and new technologies like React and Redux to make it easier to build dynamic web applications. We also wanted to update our stack to fit in with the modern paradigm.”

02 Speed Slack desktop side by side

Over the course of the last few months, the team actually quietly rolled out a lot of the prep work for this move, though the full extent of the work is only going to become apparent once you update the client to the latest version, as it’s the new Electron app that will bring it all together.

Slack promises that this new version will use up to 50% less memory than before and that Slack will load 33% faster. Joining an incoming call will also be 10 times faster now.

A lot of these changes will be especially apparent to users who are part of multiple workspaces. That’s because, as DeLanghe stressed, the team designed the new architecture with the assumption that many users are now part of multiple workspaces. Those used to take up a lot of memory and CPU cycles when you switched between them, as each workspace used to get its own Electron process in the old app. 2019 07 21 1907

In the updated app, Slack went with React to build all of the UI components, and instead of waiting for all the data to load before displaying the UI, the new app now lazily loads data as it becomes available.

The result of this is an experience that also now allows you to at least read previously opened channels and conversations when you are offline.

04 Low connectivity Slack desktop side by side

What’s maybe even more important, though, is that Slack now has a modern client to build on, which should speed up feature development going forward. “I’m not going to over-promise,” DeLanghe said. “This removes one of the barriers that any company that’s scaling and building features at the same time has to think about. […] This makes that trade-off a little bit easier.”

The update will roll out to all users over the course of the next few weeks. That’s because this is a two-part change. You’ll need both the new desktop application and become eligible for the new version. Some of this is out of Slack’s hands, as your IT department may decide how it rolls out updates, for example.

03 Memory Slack desktop side by side

Jul
02
2019
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Software development analytics platform Sourced launches an enterprise edition

Sourced, or source{d}, as the company styles its name, provides developers and IT departments with deeper analytics into their software development life cycle. It analyzes codebases, offers data about which APIs are being used and provides general information about developer productivity and other metrics. Today, Sourced is officially launching its Enterprise Edition, which gives IT departments and executives a number of advanced tools for managing their software portfolios and the processes they use to create them.

“Sourced enables large engineering organizations to better monitor, measure and manage their IT initiatives by providing a platform that empowers IT leaders with actionable data,” said the company’s CEO Eiso Kant. “The release of Sourced Enterprise is a major milestone towards proper engineering observability of the entire software development life cycle in enterprises.”

Engineering Effectiveness Efficiency

Because it’s one of the hallmarks of every good enterprise tools, it’s no surprise that Sourced Enterprise also offers features like role-based access control and other security features, as well as dedicated support and SLAs. IT departments also can run the service on-premise, or use it as a SaaS product.

The company also tells me that the enterprise version can handle larger codebases so that even complex queries over a large data set only takes a few seconds (or minutes if it’s a really large codebase). To create these complex queries, the enterprise edition includes a number of add-ons to allow users to create these advanced queries. “These are available upon request and tailored to help enterprises overcome specific challenges that often rely on machine learning capabilities, such as identity matching or code duplication analysis,” the company says.

Cloud Migration

The service integrates with most commonly used project management and business intelligence tools, but it also ships with Apache Superset, an open-source business intelligence application that offers built-in data visualization capabilities.

These visualization capabilities are also now part of the Sourced Community Edition, which is now available in private beta.

“Sourced Enterprise gave us valuable insights into the Cloud Foundry codebase evolution, development patterns, trends and dependencies, all presented in easy-to-digest dashboards,” said Chip Childers, the CTO of the open-source Cloud Foundry Foundation, which tested the Enterprise Edition ahead of its launch. “If you really want to understand what’s going on in your codebase and engineering department, Sourced is the way to go.”

To date, the company has raised $10 million from First VC, Heartcore Capital, Xavier Niel and others.

Talent Assessment Managment

Jul
01
2019
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Tara.ai, which uses machine learning to spec out and manage engineering projects, nabs $10M

Artificial intelligence has become an increasingly important component of how a lot of technology works; now it’s also being applied to how technologists themselves work. Today, one of the startups building such a tool has raised some capital, Tara.ai, a platform that uses machine learning to help an organization get engineering projects done — from identifying and predicting the work that will need to be tackled, to sourcing talent to execute that, and then monitoring the project of that project — has raised a Series A of $10 million to continue building out its platform.

The funding for the company cofounded by Iba Masood (she is the CEO) and Syed Ahmed comes from an interesting group of investors that point to Tara’s origins, as well as how it sees its product developing over time.

The round was led by Aspect Ventures (the female-led firm that puts a notable but not exclusive emphasis on female-founded startups) with participation also from Slack, by way of its Slack Fund. Previous investors Y Combinator and Moment Ventures also participated in the round. (Y Combinator provides an avenue to companies from its cohorts to help them source their Series A rounds, and Tara.ai went through this process.)

Tara.ai was originally founded as Gradberry out of Y Combinator, with its initial focus on using an AI platform for organizations to evaluate and help source engineering talent: Tara.ai was originally that name of its AI engine.

(The origin of how Masood and Ahmed identified this problem was through their own direct experience: both were grads (she in finance, he in engineering) from the American University of Sharjah in the U.A.E. that had problems getting hired because no one had ever heard of their university. Even so, they had won an MIT-affiliated startup competition in Morocco and relocated to Boston. The idea with Gradberry was to cut through the big names and focus just on what people could do.)

Masood and Syed (who eventually got married) eventually realised that using that engine to evaluate the wider challenges of executing engineering projects came as a natural progression once the team started digging into the challenges and identifying what actually needed to be solved.

A study that McKinsey (where Masood once worked) conducted across some 5,000 projects found that $66 billion dollars were identified as “lost” due to projects running past the expected completion time, lack of adequate talent and just overall poor planning.

“We realised that recruiting was actually the final decision you make, not the first, and we wanted to be involved earlier in the decision-making process,” Masood said in an interview. “We saw a much bigger opportunity looking not at the people, but the whole project.”

In action, that means that Tara.ai is used not just to scope out the nature of the problem that needed to be solved, or the goal that an organization wanted to achieve; it is also used to suggest which frameworks will need to be used to execute on that goal, and then suggest a timeline to follow.

Then, it starts to evaluate a company’s own staff expertise, along with that from other recruiting platforms, to figure out which people to source from within the company. Eventually, that will also be complemented with sourcing information from outside the organization — either contractors or new hires.

Masood noted that a large proportion of users in the tech world today use Jira and platforms like it to manage projects. While there are some tools in Jira to help plan out projects better, Tara is proposing its platform as a kind of virtual project manager, or an assistant to an existing project manager, to conceive of the whole project, not just help with the admin of getting it done.

Notably, right now she says that some 75% of Tara.ai’s users — customers include Cisco, Orange Silicon Valley and Mower Digital — are “not technical,” meaning they themselves do not ship or use code. “This helps them understand what could be considered and the dependencies that can be expected out of a project,” she notes.

Lauren Kolodny, the partner at Aspect who led the investment, said that one of the things that stood out for her, in fact, with Tara.ai, was precisely how it could be applied exactly in those kinds of scenarios.

Today, tech is such a fundamental part of how a lot of businesses operate, but that doesn’t mean that every business is natively a technology one (think here of food and beverage companies as an example, or government agencies). In those cases, these companies would have traditionally had to turn to outside consultants to identify opportunities, and then build and potentially long-term operate whatever the solutions become. Now there is an opportunity to rethink how technology is used in these kinds of organizations.

“Projects have been hacked together from multiple systems, not really built in combination,” Kolodny said of how much development happens at these traditional businesses. “We are really excited about the machine learning scoping and mapping of internal and external talent, which is looking to be particularly important as traditional enterprises are required to get level with newer businesses, and the amount of talent they need to execute on these projects becomes challenging.”

Tara.ai’s next steps will involve essentially taking the building blocks of what you can think of as a very powerful talent and engineering project search engine, and making it more powerful. That will include integrating databases of external consultants and figuring out how best to have these in tandem with internal teams while keeping them working well together. And soon to come also will be bug prediction: how to identify these before they arise in a project. The company is releasing an updated AI engine to coincide with the funding.

Tara AI launch

The Slack investment is also a notable nod to what direction Tara.ai will take. Masood said that Slack was one of three “big tech” companies interested in investing in this round, and she and Syed chose Slack because from what they could see of its existing and target customers, many were already using it and some have already started requesting closer collaboration so that events in one could come up as updates in the other.

“Our largest customers are heavy Slack users and they are already having conversations in Slack related to projects in Tara.ai,” she said. “We are tackling the scoping element and now seeing how to link up even command line interfaces between the two.”

She noted that this does not rule out closer integrations with communications and other platforms that people use on a daily basis to get their work done: the idea is to become a tool to work better overall.

Jun
19
2019
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Postman raises $50 million to grow its API development platform

Postman, a five-year-old startup that is attempting to simplify development, tests and management of APIs through its platform, has raised $50 million in a new round to scale its business.

The Series B for the startup, which began its journey in India, was led by CRV and included participation from existing investor Nexus Venture Partners . The startup, with offices in India and San Francisco, closed its Series A financing round four years ago and has raised $58 million to date.

Postman offers a development environment which a developer or a firm could use to build, publish, document, design, monitor, test and debug their APIs. Postman, like some other startups such as RapidAPI, also maintains a marketplace to offer APIs for quick integration with other popular services.

The startup was co-founded by Abhinav Asthana, a former intern at Yahoo . Asthana was frustrated with how APIs were an afterthought for many developers, as they usually got around to building them in the eleventh hour. Additionally, developers were relying on their own workflows and there was no organized platform that could be used by many, he explained in an interview with TechCrunch.

Even big software firms have not looked into this space yet, and many have instead become a customer of Postman. “We are solving a fundamental problem for the technology landscape. Big companies tend to be slower as they have many other things on their plate,” said Asthana.

Five years later, Postman has grown significantly. More than 7 million users and 300,000 companies, including Microsoft, Twitter, Best Buy, AMC Theaters, PayPal, Shopify, BigCommerce and DocuSign today use Postman’s platform.

The modern software development relies heavily on APIs as more businesses begin to talk with one another. According to research firm Gartner, more than 65% of global infrastructure service providers’ revenue will be generated through services enabled by APIs by 2023, up from 15% in 2018.

Asthana said Postman intends to use the fresh capital to scale its startup, products and grow its team. “We are scaling rapidly across all dimensions. There are many use cases that we still want to address over the coming months. We will also experiment with sales and invest in improving user experience,” he added.

Postman offers some of its services in limited capacity for free to users. For the rest, it charges between $8 to $18 per user to its customers. That’s how the company generates revenue. Asthana declined to share the financial performance of the startup, but said its customer base was “growing phenomenally.”

Postman said CRV general partner Devdutt Yellurkar has joined its board of directors.

Jun
12
2019
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RealityEngines.AI raises $5.25M seed round to make ML easier for enterprises

RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.

The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier data sets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.

As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me, the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller data sets, already have some available solutions like generative adversarial networks that can augment existing data sets and that RealityEngines expects to innovate on.

Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.

Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.

Jun
12
2019
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Apollo raises $22M for its GraphQL platform

Apollo, a San Francisco-based startup that provides a number of developer and operator tools and services around the GraphQL query language, today announced that it has raised a $22 million growth funding round co-led by Andreessen Horowitz and Matrix Partners. Existing investors Trinity Ventures and Webb Investment Network also participated in this round.

Today, Apollo is probably the biggest player in the GraphQL ecosystem. At its core, the company’s services allow businesses to use the Facebook -incubated GraphQL technology to shield their developers from the patchwork of legacy APIs and databases as they look to modernize their technology stacks. The team argues that while REST APIs that talked directly to other services and databases still made sense a few years ago, it doesn’t anymore now that the number of API endpoints keeps increasing rapidly.

Apollo replaces this with what it calls the Data Graph. “There is basically a missing piece where we think about how people build apps today, which is the piece that connects the billions of devices out there,” Apollo co-founder and CEO Geoff Schmidt told me. “You probably don’t just have one app anymore, you probably have three, for the web, iOS and Android . Or maybe six. And if you’re a two-sided marketplace you’ve got one for buyers, one for sellers and another for your ops team.”

Managing the interfaces between all of these apps quickly becomes complicated and means you have to write a lot of custom code for every new feature. The promise of the Data Graph is that developers can use GraphQL to query the data in the graph and move on, all without having to write the boilerplate code that typically slows them down. At the same time, the ops teams can use the Graph to enforce access policies and implement other security features.

“If you think about it, there’s a lot of analogies to what happened with relational databases in the ’80s,” Schmidt said. “There is a need for a new layer in the stack. Previously, your query planner was a human being, not a piece of software, and a relational database is a piece of software that would just give you a database. And you needed a way to query that database, and that syntax was called SQL.”

Geoff Schmidt, Apollo CEO, and Matt DeBergalis, CTO

GraphQL itself, of course, is open source. Apollo is now building a lot of the proprietary tools around this idea of the Data Graph that make it useful for businesses. There’s a cloud-hosted graph manager, for example, that lets you track your schema, as well as a dashboard to track performance, as well as integrations with continuous integration services. “It’s basically a set of services that keep track of the metadata about your graph and help you manage the configuration of your graph and all the workflows and processes around it,” Schmidt said.

The development of Apollo didn’t come out of nowhere. The founders previously launched Meteor, a framework and set of hosted services that allowed developers to write their apps in JavaScript, both on the front-end and back-end. Meteor was tightly coupled to MongoDB, though, which worked well for some use cases but also held the platform back in the long run. With Apollo, the team decided to go in the opposite direction and instead build a platform that makes being database agnostic the core of its value proposition.

The company also recently launched Apollo Federation, which makes it easier for businesses to work with a distributed graph. Sometimes, after all, your data lives in lots of different places. Federation allows for a distributed architecture that combines all of the different data sources into a single schema that developers can then query.

Schmidt tells me the company started to get some serious traction last year and by December, it was getting calls from VCs that heard from their portfolio companies that they were using Apollo.

The company plans to use the new funding to build out its technology to scale its field team to support the enterprises that bet on its technology, including the open-source technologies that power both the services.

“I see the Data Graph as a core new layer of the stack, just like we as an industry invested in the relational database for decades, making it better and better,” Schmidt said. “We’re still finding new uses for SQL and that relational database model. I think the Data Graph is going to be the same way.”

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