Lightyear, a New York City startup that wants to make it easier for large companies to procure networking infrastructure like internet and SD-WAN, announced a $3.7 million seed round today.

Amplo led the round with help from Susa Ventures, Ludlow Ventures, Mark Cuban, David Adelman and Operator Partners. While it was at it, the company announced that it was emerging from stealth and offering its solution in public beta.

Company CEO and co-founder Dennis Thankachan says that while so much technology buying has moved online, networking technology procurement still involves phone calls for price quotes that could sometimes take weeks to get. Thankachan says that when he was working at a hedge fund specializing in telecommunications he witnessed this first hand and saw an opportunity for a startup to fill the void.

“Our objective is to make the process of buying telecom infrastructure, kind of like buying socks on Amazon, providing a real consumer-like experience to the enterprise and empowering buyers with data because information asymmetry and a lack of transparent data on what things should cost, where providers are available, and even what’s existing already in your network is really at the core of the problem for why this is frustrating for enterprise buyers,” Thankachan explained.

The company offers the ability to simply select a service and find providers in your area with costs and contract terms if it’s a simple purchase, but he recognizes that not all enterprise purchases will be that simple and the startup is working to digitize the corporate buying process into the Lightyear platform.

To provide the data that he spoke of, the company has already formed relationships with over 400 networking providers worldwide. The pricing model is in flux, but could involve a monthly subscription or a percentage of the sale. That is something they are working out, but they are using the latter during beta testing to keep the product free for now.

The company already has 10 employees and flush with the new investment, it plans to double that in the next year. Thankachan says as he builds the company, particularly as a person of color himself, he takes diversity and inclusion extremely seriously and sees it as part of the company’s core values.

“Trying to enable people from non-traditional backgrounds to succeed will be really important to us, and I think providing economic opportunity to people that traditionally would not have been afforded several aspects of economic opportunity is the biggest ways to fix the opportunity gap in this country,” he said.

The company, which launched a year ago has basically grown up during the pandemic. That means he has yet to meet any of his customers or investors in person, but he says he has learned to adapt to that approach. While he is based in NYC, his investors are are in the Bay Area and so that remote approach will remain in place for the time being.

As he makes his way from seed to a Series A, he says that it’s up to him to stay focused and execute with the goal of showing product-market fit across a variety of company types. He believes if the startup can do this, it will have the data to take to investors when it’s time to take the next step.

We’ve seen our fair share of business intelligence (BI) platforms that aim to make data analysis accessible to everybody in a company. Most of them are still fairly complicated, no matter what their marketing copy says. MachEye, which is launching its AI-powered BI platform today, is offering a new twist on this genre. In addition to its official launch, the company also today announced a previously unreported $4.6 seed funding round led by Canaan Partners with participation from WestWave Capital.

MachEye is not just what its founder and CEO Ramesh Panuganty calls a “low-prep, no-prep” BI platform, but it uses natural language processing to allow anybody to query data using natural language — and it can then automatically generate interactive data stories on the fly that put the answer into context. That’s quite a different approach from its more dashboard-centric competition.

“I have seen the business intelligence problems in the past,” Panuganty said. “And I saw that Traditional BI, even though it has existed for 30 or 40 years, had this paradigm of ‘what you ask is what you get.’ So the business user asks for something, either in an email, on the phone or in person, and then he gets an answer to that question back. That essentially has these challenges of being dependent on the experts and there is a time that is lost to get the answers — and then there’s a lack of exploratory capabilities for the business user. and the bigger problem is that they don’t know what they don’t know.”

Panuganty’s background includes time at Sun Microsystems and Bell Labs, working on their operating systems before becoming an entrepreneur. He build three companies over the last 12 years or so. The first was a cloud management platform, Cloud365, which was acquired by Cognizant. The second was analytics company Drastin, which got acquired by Splunk in 2017, and the third was the AI-driven educational platform SelectQ, which Thinker acquired this April. He also holds 15 patents related to machine learning, analytics and natural language processing.

Given that track record, it’s probably no surprise why VCs wanted to invest in his new startup, too. Panuganty tells me that when he met with Canaan Partners, he wasn’t really looking for an investment. He had already talked to the team while building SelectQ, but Canaan never got to make an investment because the company got acquired before it needed to raise more funding. But after an informal meeting that ended up lasting most of the day, he received an offer the next morning.

Image Credits: MachEye

MachEye’s approach is definitely unique. “Generating audio-visuals on enterprise data, we are probably the only company that does it,” Panuganty said. But it’s important to note that it also offers all of the usual trappings of a BI service. If you really want dashboards, you can build those, and developers can use the company’s APIs to use their data elsewhere, too. The service can pull in data from most of the standard databases and data warehousing services, including AWS Redshift, Azure Synapse, Google BigQuery, Snowflake and Oracle. The company promises that it only takes 30 minutes from connecting a data source to being able to ask questions about that data.

Interestingly, MachEye’s pricing plan is per seat and doesn’t limit how much data you can query. There’s a free plan, but without the natural search and query capabilities, an $18/month/user plan that adds those capabilities and additional search features, but it takes the enterprise plan to get the audio narrations and other advanced features. The team is able to use this pricing model because it is able to quickly spin up the container infrastructure to answer a query and then immediately shut it down again — all within about two minutes.

Kandji, a mobile device management (MDM) startup, launched last October. That means it was trying to build the early stage company just as the pandemic hit earlier this year. But a company that helps manage devices remotely has been in demand in this environment, and today it announced a $21 million Series A.

Greycroft led the round with participation from new investors Okta Ventures and B Capital Group, and existing investor First Round Capital. Today’s investment brings the total raised to $28.4 million, according to the company.

What Kandji is building is a sophisticated zero-touch device management solution to help larger companies manage their fleet of Apple devices, including keeping them in compliance with a particular set of rules. As CEO and co-founder Adam Pettit told TechCrunch at the time of his seed investment last year:

“We’re the only product that has almost 200 of these one-click policy frameworks we call parameters. So an organization can go in and browse by compliance framework, or we have pre-built templates for companies that don’t necessarily have a specific compliance mandate in mind,” he said.

Monty Gray, SVP of corporate development at Okta, says Okta Ventures is investing because it sees this approach as a valuable extension of the company’s mission.

“Kandji’s device management streamlines the most common and complex tasks for Apple IT administrators and enables distributed workforces to get up and running quickly and securely,” he said in a statement.

It seems to be working. Since the company’s launch last year it reports it has gained hundreds of new paying customers and grown from 10 employees at launch to 40 today. Pettit says that he has plans to triple that number in the next 12 months. As he builds the company, he says finding and hiring a diverse pool of candidates is an important goal.

“There are ways to extend out into different candidate pools so that you’re not just looking at the same old candidates that you normally would. There are certain ways to reduce bias in the hiring process. So again, I think we look at this as absolutely critical, and we’re excited to build a really diverse company over the next several years,” he said.

Image Credits: Kandji

He notes that the investment will not only enable him to build the employee base, but also expand the product too, and in the past year, it has already taken it from basic MDM into compliance and there are new features coming as they continue to grow the product.

“If someone saw our product a year ago, it’s a very different product today, and it’s allowed us to move up market into the enterprise, which has been very exciting for us,” he said.

In the distant past, there was a proverbial “digital divide” that bifurcated workers into those who knew how to use computers and those who didn’t.[1] Young Gen Xers and their later millennial companions grew up with Power Macs and Wintel boxes, and that experience made them native users on how to make these technologies do productive work. Older generations were going to be wiped out by younger workers who were more adaptable to the needs of the modern digital economy, upending our routine notion that professional experience equals value.

Of course, that was just a narrative. Facility with using computers was determined by the ability to turn it on and log in, a bar so low that it can be shocking to the modern reader to think that a “divide” existed at all. Software engineering, computer science and statistics remained quite unpopular compared to other academic programs, even in universities, let alone in primary through secondary schools. Most Gen Xers and millennials never learned to code, or frankly, even to make a pivot table or calculate basic statistical averages.

There’s a sociological change underway though, and it’s going to make the first divide look quaint in hindsight.

Over the past two or so years, we have seen the rise of a whole class of software that has been broadly (and quite inaccurately) dubbed “no-code platforms.” These tools are designed to make it much easier for users to harness the power of computing in their daily work. That could be everything from calculating the most successful digital ad campaigns given some sort of objective function, or perhaps integrating a computer vision library into a workflow that calculates the number of people entering or exiting a building.

The success and notoriety of these tools comes from the feeling that they grant superpowers to their users. Projects that once took a team of engineers some hours to build can now be stitched together in a couple of clicks through a user interface. That’s why young startups like Retool can raise at nearly a $1 billion valuation and Airtable at $2.6 billion, while others like Bildr, Shogun, Bubble, Stacker and dozens more are getting traction among users.

Of course, no-code tools often require code, or at least, the sort of deductive logic that is intrinsic to coding. You have to know how to design a pivot table, or understand what machine learning capability is and what it might be useful for. You have to think in terms of data, and about inputs, transformations and outputs.

The key here is that no-code tools aren’t successful just because they are easier to use — they are successful because they are connecting with a new generation that understands precisely the sort of logic required by these platforms to function. Today’s students don’t just see their computers and mobile devices as consumption screens and have the ability to turn them on. They are widely using them as tools of self-expression, research and analysis.

Take the popularity of platforms like Roblox and Minecraft. Easily derided as just a generation’s obsession with gaming, both platforms teach kids how to build entire worlds using their devices. Even better, as kids push the frontiers of the toolsets offered by these games, they are inspired to build their own tools. There has been a proliferation of guides and online communities to teach kids how to build their own games and plugins for these platforms (Lua has never been so popular).

These aren’t tiny changes; 150 million play Roblox games across 40 million user-created experiences, and the platform has nearly 350,000 developers. Minecraft for its part has more than 130 million active users. These are generation-defining experiences for young people today.

That excitement to harness computers is also showing up in educational data. Advanced Placement tests for computer science have grown from around 20,000 in 2010 to more than 70,000 this year according to the College Board, which administers the high school proficiency exams. That’s the largest increase among all of the organization’s dozens of tests. Meanwhile at top universities, computer science has emerged as the top or among the top majors, pulling in hundreds of new students per campus per year.

The specialized, almost arcane knowledge of data analysis and engineering is being widely democratized for this new generation, and that’s precisely where a new digital divide is emerging.

In business today, it’s not enough to just open a spreadsheet and make some casual observations anymore. Today’s new workers know how to dive into systems, pipe different programs together using no-code platforms and answer problems with much more comprehensive — and real-time — answers.

It’s honestly striking to see the difference. Whereas just a few years ago, a store manager might (and strong emphasis on might) put their sales data into Excel and then let it linger there for the occasional perusal, this new generation is prepared to connect multiple online tools to build an online storefront (through no-code tools like Shopify or Squarespace), calculate basic LTV scores using a no-code data platform and prioritize their best customers with marketing outreach through basic email delivery services. And it’s all reproducible, as it is in technology and code and not produced by hand.

There are two important points here. First is to note the degree of fluency these new workers have for these technologies, and just how many members of this generation seem prepared to use them. They just don’t have the fear to try new programs, and they know they can always use search engines to find answers to problems they are having.

Second, the productivity difference between basic computer literacy and a bit more advanced expertise is profound. Even basic but accurate data analysis on a business can raise performance substantially compared to gut instinct and expired spreadsheets.

This second digital divide is only going to get more intense. Consider students today in school, who are forced by circumstance to use digital technologies in order to get their education. How many more students are going to become even more capable of using these technologies? How much more adept are they going to be at remote work? While the current educational environment is a travesty and deeply unequal, the upshot is that ever more students are going to be forced to become deeply fluent in computers.[2]

Progress in many ways is about raising the bar. This generation is raising the bar on how data is used in the workplace, in business and in entrepreneurship. They are better than ever at bringing together various individual services and cohering them into effective experiences for their customers, readers and users. The No-Code Generation has the potential to finally fill that missing productivity gap in the global economy, making our lives better, while saving time for everyone.

[1] Probably worth pointing out that the other “digital divide” at the time was describing households that had internet access and households that did not. That’s a divide that unfortunately still plagues America and many other rich, industrialized countries.

[2] Important to note that access to computing is still an issue for many students and represents one of the most easily fixable inequalities today in America. Providing equal access to computing should be an absolute imperative.

Freshworks, the customer and employee engagement company that offers a range of products, from call center and customer support software to HR tools and marketing automation services, today announced the launch of its newest product: Freshworks CRM. The new service, which the company built on top of its new Freshworks Neo platform, is meant to give sales and marketing teams all of the tools they need to get a better view of their customers — with a bit of machine learning thrown in for better predictions.

Freshworks CRM is essentially a rebrand of the company’s Freshsales service, combined with the company’s capabilities of its Freshmarketer marketing automation tool.

“Freshworks CRM unites Freshsales and Freshmarketer capabilities into one solution, which leverages an embedded customer data platform for an unprecedented and 360-degree view of the customer throughout their entire journey,” a company spokesperson told me.

The promise here is that this improved CRM solution is able to provide teams with a more complete view of their (potential) customers thanks to the unified view — and aggregated data — that the company’s Neo platform provides.

The company argues that the majority of CRM users quickly become disillusioned with their CRM service of choice — and the reason for that is because the data is poor. That’s where Freshworks thinks it can make a difference.

“Freshworks CRM delivers upon the original promise of CRM: a single solution that combines AI-driven data, insights and intelligence and puts the customer front and center of business goals,” said Prakash Ramamurthy, the company’s chief product officer. “We built Freshworks CRM to harness the power of data and create immediate value, challenging legacy CRM solutions that have failed sales teams with clunky interfaces and incomplete data.”

The idea here is to provide teams with all of their marketing and sales data in a single dashboard and provide AI-assisted insights to them to help drive their decision making, which in turn should lead to a better customer experience — and more sales. The service offers predictive lead scoring and qualification, based on a host of signals users can customize to their needs, as well as Slack and Teams integrations, built-in telephony with call recording to reach out to prospects and more. A lot of these features were already available in Freshsales, too.

“The challenge for online education is the ‘completion rate’. To increase this, we need to understand the ‘Why’ aspect for a student to attend a course and design ‘What’ & ‘How’ to meet the personalized needs of our students so they can achieve their individual goals,” said Mamnoon Hadi Khan, the chief analytics officer at Shaw Academy. “With Freshworks CRM, Shaw Academy can track the entire student customer journey to better engage with them through our dedicated Student Success Managers and leverage AI to personalize their learning experience — meeting their objectives.”

Pricing for Freshworks CRM starts at $29 per user/month and goes up to $125 per user/month for the full enterprise plan with more advanced features.