Oct
15
2018
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Celonis brings intelligent process automation software to cloud

Celonis has been helping companies analyze and improve their internal processes using machine learning. Today the company announced it was providing that same solution as a cloud service with a few nifty improvements you won’t find on prem.

The new approach, called Celonis Intelligent Business Cloud, allows customers to analyze a workflow, find inefficiencies and offer improvements very quickly. Companies typically follow a workflow that has developed over time and very rarely think about why it developed the way it did, or how to fix it. If they do, it usually involves bringing in consultants to help. Celonis puts software and machine learning to bear on the problem.

Co-founder and CEO Alexander Rinke says that his company deals with massive volumes of data and moving all of that to the cloud makes sense. “With Intelligent Business Cloud, we will unlock that [on prem data], bring it to the cloud in a very efficient infrastructure and provide much more value on top of it,” he told TechCrunch.

The idea is to speed up the whole ingestion process, allowing a company to see the inefficiencies in their business processes very quickly. Rinke says it starts with ingesting data from sources such as Salesforce or SAP and then creating a visual view of the process flow. There may be hundreds of variants from the main process workflow, but you can see which ones would give you the most value to change, based on the number of times the variation occurs.

Screenshot: Celonis

By packaging the Celonis tools as a cloud service, they are reducing the complexity of running and managing it. They are also introducing an app store with over 300 pre-packaged options for popular products like Salesforce and ServiceNow and popular process like order to cash. This should also help get customers up and running much more quickly.

New Celonis App Store. Screenshot: Celonis

The cloud service also includes an Action Engine, which Rinke describes as a big step toward moving Celonis from being purely analytical to operational. “Action Engine focuses on changing and improving processes. It gives workers concrete info on what to do next. For example in process analysis, it would notice on time delivery isn’t great because order to cash is to slow. It helps accelerate changes in system configuration,” he explained.

Celonis Action Engine. Screenshot: Celonis

The new cloud service is available today. Celonis was founded in 2011. It has raised over $77 million. The most recent round was a $50 million Series B on a valuation over $1 billion.

Oct
11
2018
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Zuora partners with Amazon Pay to expand subscription billing options

Zuora, the SaaS company helping organizations manage payments for subscription businesses, announced today that it had been selected as a Premier Partner in the Amazon Pay Global Partner Program. 

The “Premier Partner” distinction means businesses using Zuora’s billing platform can now easily integrate Amazon’s digital payment system as an option during checkout or recurring payment processes. 

The strategic rationale for Zuora is clear, as the partnership expands the company’s product offering to prospective and existing customers.  The ability to support a wide array of payment methodologies is a key value proposition for subscription businesses that enables them to service a larger customer base and provide a more seamless customer experience.

It also doesn’t hurt to have a deep-pocketed ally like Amazon in a fairly early-stage industry.  With omnipotent tech titans waging war over digital payment dominance, Amazon has reportedly doubled down on efforts to spread Amazon Pay usage, cutting into its own margins and offering incentives to retailers.

As adoption of Amazon Pay spreads, subscription businesses will be compelled to offer the service as an available payment option and Zuora should benefit from supporting early billing integration.

For Amazon Pay, teaming up with Zuora provides direct access to Zuora’s customer base, which caters to tens of millions of subscribers. 

With Zuora minimizing the complexity of adding additional payment options, which can often disrupt an otherwise unobtrusive subscription purchase experience, the partnership with Zuora should help spur Amazon Pay adoption and reduce potential friction.

“By extending the trust and convenience of the Amazon experience to Zuora, merchants around the world can now streamline the subscription checkout experience for their customers,” said Vice President of Amazon Pay, Patrick Gauthier.  “We are excited to be working with Zuora to accelerate the Amazon Pay integration process for their merchants and provide a fast, simple and secure payment solution that helps grow their business.”

The world subscribed

The collaboration with Amazon Pay represents another milestone for Zuora, which completed its IPO in April of this year and is now looking to further differentiate its offering from competing in-house systems or large incumbents in the Enterprise Resource Planning (ERP) space, such as Oracle or SAP.   

Going forward, Zuora hopes to play a central role in ushering a broader shift towards a subscription-based economy. 

Tien Tzuo, founder and CEO of Zuora, told TechCrunch he wants the company to help businesses first realize they should be in the subscription economy and then provide them with the resources necessary to flourish within it.

“Our vision is the world subscribed.”  said Tzuo. “We want to be the leading company that has the right technology platform to get companies to be successful in the subscription economy.”

The partnership will launch with publishers “The Seattle Times” and “The Telegraph”, with both now offering Amazon Pay as a payment method while running on the Zuora platform.

Oct
10
2018
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Shared inbox startup Front launches a complete redesign

Front is launching a major revamp today. And it starts with a brand new design. Front is now powered by React for the web and desktop app, which should make it easier to add new features down the road.

Front hasn’t pivoted to become something else. At heart, it remains a multiplayer email client. You can share generic email addresses with your coworkers, such as sales@yourcompany or jobs@yourcompany. You can then assign emails, comment before replying and integrate your CRM with your email threads.

But the company is also adding a bunch of new features. The most interesting one is the ability to start a thread with your team without having to send an email first. If a client sends you an email, you can comment on the thread and mention your coworkers just like on a Facebook post.

Many companies already use emails for internal communications. So they started using Front to talk to their coworkers. Before today, you had to send an original email and then people could comment on it. Now, you can just create a post by giving it a title and jumping to the comment section. It’s much more straightforward.

“We aren’t planning for all internal conversations to move to Front, but a lot of them very well could. A tool like Slack is often used for questions that don’t require the immediate response that Slack demands,” co-founder and CEO Mathilde Collin told me. “By bringing these messages into Front, we aim to reduce disruptions and help people stay focused.”

In other words, a Slack message feels like a virtual tap on the shoulder. You have to interrupt what you’re doing to take a minute and answer. Front can be used for asynchronous conversations and things that don’t need an immediate response. That’s why you can now also send Slack messages to Front so that you can deal with them in Front.

With this update, Front is making sharing more granular. Front isn’t just about shared addresses. You can assign your personal emails to a coworker — this is much more efficient than forwarding an email. Now, you can easily see who can read and interact with an email thread at the top of the email view.

If somebody sends an email to Sarah and Sam, they’ll both have a copy of this email in their personal inboxes. If Sarah and Sam start commenting and @-mentioning people, Front will now merge the threads.

As a user, you get a unified inbox with all your personal emails, emails that were assigned to you and messages assigned to your team inbox.

Finally, Front has improved its smart filtering system. You can now create more flexible rules. For instance, if an email matches some or all criteria, Front can assign an email to a team or a person, send an automated reply, trigger another rule and more.

The new version of Front will be available later this month. Once again, Front remains focused on its core mission — making work conversations more efficient and more flexible. The company doesn’t try to reinvent the wheel and still relies heavily on emails.

Many people (myself included) say that email is too often a waste of time. Dealing with emails doesn’t necessarily mean getting work done. Front wants to remove all the pains of this messaging protocol so that you can focus on the content of the messages.

Oct
10
2018
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Zenefits’ Parker Conrad returns with Rippling to kill HR & IT busywork

Parker Conrad likes to save time, even though it’s gotten him in trouble. The former CEO of Zenefits was pushed out of the $4.5 billion human resources startup because he built a hack that let him and employees get faster insurance certifications. But 2.5 years later, he’s back to take the busy work out of staff onboarding as well as clumsy IT services like single sign-on to enterprise apps. Today his startup Rippling launches its combined employee management system, which Conrad calls a much larger endeavor than the minimum viable product it announced while in Y Combinator’s accelerator 18 months ago.

“It’s not an HR system. It’s a level below that,” Conrad tells me. “It’s this unholy, crazy mashup of three different things.” First, it handles payroll, benefits, taxes and PTO across all 50 states. “Except Syria and North Korea, you can pay anyone in the world with Rippling,” Conrad claims. That makes it a competitor with Gusto… and Zenefits.

Second, it’s a replacement for Okta, Duo and other enterprise single-sign on security apps that authenticate staffers across partnered apps. Rippling bookmarklets make it easy to auth into over 250 workplace apps, like Gmail, Slack, Dropbox, Asana, Trello, AWS, Salesforce, GitHub and more. When an employee is hired or changes teams, a single modification to their role in Rippling automatically changes all the permissions of what they can access.

And third, it handles computer endpoint security like Jamf. When an employee is hired, Rippling can instantly ship them a computer with all the right software installed and the hard drive encrypted, or have staffers add the Rippling agent that enforces the company’s security standards. The system is designed so there’s no need for an expert IT department to manage it.

“Distributed, fragmented systems of record for employee data are secretly the cause of almost all the annoying administrative work of running a company,” Conrad explains. “If you could build this system that ties all of it together, you could eliminate all this crap work.” That’s Rippling. It’s opening up to all potential clients today, charging them a combined subscription or à la carte fees for any of the three wings of the product.

Conrad refused to say how much Rippling has raised total, citing the enhanced scrutiny Zenefits’ raises drew. But he says a Wall Street Journal report that Rippling had raised $7 million was inaccurate. “We haven’t raised any priced VC rounds. Just a bunch of seed money. We raised from Initialized Capital, almost all the early seed investors at Zenefits and a lot of individuals.” He cited Y Combinator, YC Growth Fund, YC’s founder Jessica Livingston and president Sam Altman, other YC partners, as well as DFJ and SV Angel.

“Because we were able to raise a bunch of money and court great engineers . . . we were able to spend a lot of time building this fundamental technology,” Conrad tells me. Rippling has about 50 team members now, with about 40 of them being engineers, highlighting just how thoroughly Conrad wants to eradicate manual work about work, starting with his own startup.

The CEO refused to discuss details of exactly what went down at Zenefits and whether he thought his ejection was fair. He was accused of allowing Zenefits’ insurance brokers to sell in states where they weren’t licensed, and giving some employees a macro that let them more quickly pass the online insurance certification exam. Conrad ended up paying about $534,000 in SEC fines. Zenefits laid off 430 employees, or 45 percent of its staff, and moved to selling software to small-to-medium sized businesses through a network of insurance brokers.

But when asked what he’d learned from Zenefits, Conrad looked past those troubles and instead recalled that “one of the mistakes that we made was that we did a lot stuff manually behind the scenes. When you scale up, there are these manual processes, and it’s really hard to come back later when it’s a big hard complicated thing and replace it with technology. You get upside down on margins. If you start at the beginning and never let the manual processes creep in . . . it sort of works.”

Perhaps it was trying to cut corners that got Conrad into the Zenefits mess, but now that same intention has inspired Rippling’s goal of eliminating HR and IT drudgery with an all-in-one tool.

“I think I’m someone who feels the pain of that kind of stuff particularly strongly. So that’s always been a real irritant to me, and I saw this problem. The conventional wisdom is ‘don’t build something like this, start with something much smaller,’ ” Conrad concludes. “But I knew if I didn’t do this, that no one else was gong to do it and I really wanted this system to exist. This is a company that’s all about annoying stuff and making that fucking annoying stuff go away.”

Sep
19
2018
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IBM launches cloud tool to detect AI bias and explain automated decisions

IBM has launched a software service that scans AI systems as they work in order to detect bias and provide explanations for the automated decisions being made — a degree of transparency that may be necessary for compliance purposes not just a company’s own due diligence.

The new trust and transparency system runs on the IBM cloud and works with models built from what IBM bills as a wide variety of popular machine learning frameworks and AI-build environments — including its own Watson tech, as well as Tensorflow, SparkML, AWS SageMaker, and AzureML.

It says the service can be customized to specific organizational needs via programming to take account of the “unique decision factors of any business workflow”.

The fully automated SaaS explains decision-making and detects bias in AI models at runtime — so as decisions are being made — which means it’s capturing “potentially unfair outcomes as they occur”, as IBM puts it.

It will also automatically recommend data to add to the model to help mitigate any bias that has been detected.

Explanations of AI decisions include showing which factors weighted the decision in one direction vs another; the confidence in the recommendation; and the factors behind that confidence.

IBM also says the software keeps records of the AI model’s accuracy, performance and fairness, along with the lineage of the AI systems — meaning they can be “easily traced and recalled for customer service, regulatory or compliance reasons”.

For one example on the compliance front, the EU’s GDPR privacy framework references automated decision making, and includes a right for people to be given detailed explanations of how algorithms work in certain scenarios — meaning businesses may need to be able to audit their AIs.

The IBM AI scanner tool provides a breakdown of automated decisions via visual dashboards — an approach it bills as reducing dependency on “specialized AI skills”.

However it is also intending its own professional services staff to work with businesses to use the new software service. So it will be both selling AI, ‘a fix’ for AI’s imperfections, and experts to help smooth any wrinkles when enterprises are trying to fix their AIs… Which suggests that while AI will indeed remove some jobs, automation will be busy creating other types of work.

Nor is IBM the first professional services firm to spot a business opportunity around AI bias. A few months ago Accenture outed a fairness tool for identifying and fixing unfair AIs.

So with a major push towards automation across multiple industries there also looks to be a pretty sizeable scramble to set up and sell services to patch any problems that arise as a result of increasing use of AI.

And, indeed, to encourage more businesses to feel confident about jumping in and automating more. (On that front IBM cites research it conducted which found that while 82% of enterprises are considering AI deployments, 60% fear liability issues and 63% lack the in-house talent to confidently manage the technology.)

In additional to launching its own (paid for) AI auditing tool, IBM says its research division will be open sourcing an AI bias detection and mitigation toolkit — with the aim of encouraging “global collaboration around addressing bias in AI”.

“IBM led the industry in establishing trust and transparency principles for the development of new AI technologies. It’s time to translate principles into practice,” said David Kenny, SVP of cognitive solutions at IBM, commenting in a statement. “We are giving new transparency and control to the businesses who use AI and face the most potential risk from any flawed decision making.”

Sep
10
2018
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New Relic shifts with changing monitoring landscape

New Relic CEO Lew Cirne was feeling a bit nostalgic last week when he called to discuss the announcements for the company’s FutureStack conference taking place tomorrow in San Francisco. It had been 10 years since he first spoke to TechCrunch about his monitoring tool. A lot has changed in a decade including what his company is monitoring these days.

Cirne certainly recognizes that his company has come a long way since those first days. The monitoring world is going through a seismic shift as the ways we develop apps changes. His company needs to change with it to remain relevant in today’s market.

In the early days, they monitored Ruby on Rails applications, but gone are the days of only monitoring a fixed virtual machine. Today companies are using containers and Kubernetes, and beyond that, serverless architecture. Each of these approaches brings challenges to a monitoring company like New Relic, particularly the ephemeral nature and the sheer volume associated with these newer ways of working.

‘We think those changes have actually been an opportunity for us to further differentiate and further strengthen our thesis that the New Relic way is really the most logical way to address this.” He believes that his company has always been centered on the code, as opposed to the infrastructure where it’s delivered, and that has helped it make adjustments as the delivery mechanisms have changed.

Today, the company introduced a slew of new features and capabilities designed to keep the company oriented toward the changing needs of its customer base. One of the ways they are doing that is with a new feature called Outlier Detection, which has been designed to address changes in key metrics wherever your code happens to be deployed.

Further, Incident Context lets you see exactly where the incident occurred in the code so you don’t have to go hunting and pecking to find it in the sea of data.

Outlier Detection in action. Gif: New Relic

The company also introduced developer.newrelic.com, a site that extends the base APIs to provide a central place to build on top of the New Relic platform and give customers a way to extend the platform’s functionality. Cirne said each company has its own monitoring requirements, and they want to give them ability to build for any scenario.

In addition, they announced New Relic Query Language (NRQL) data, which leverages the New Relic GraphQL API to help deliver new kinds of customized, programmed capabilities to customers that aren’t available out of the box.”What if I could program New Relic to take action when a certain thing happens. When an application has a problem, it could post a notice to the status page or restart the service. You could automate something that has been historically done manually,” he explained.

Whatever the company is doing it appears to be working It went public in 2014 with an IPO share price of $30.14 and a market cap of $1.4 billion. Today, the share price was $103.65 with a market cap of $5.86 billion (as of publishing).

Sep
05
2018
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Elastic’s IPO filing is here

Elastic, the provider of subscription-based data search software used by Dell, Netflix, The New York Times and others, has unveiled its IPO filing after confidentially submitting paperwork to the SEC in June. The company will be the latest in a line of enterprise SaaS businesses to hit the public markets in 2018.

Headquartered in Mountain View, Elastic plans to raise $100 million in its NYSE listing, though that’s likely a placeholder amount. The timing of the filing suggests the company will transition to the public markets this fall; we’ve reached out to the company for more details. 

Elastic will trade under the symbol ESTC.

The business is known for its core product, an open-source search tool called ElasticSearch. It also offers a range of analytics and visualization tools meant to help businesses organize large data sets, competing directly with companies like Splunk and even Amazon — a name it mentions 14 times in the filing.

Amazon offers some of our open source features as part of its Amazon Web Services offering. As such, Amazon competes with us for potential customers, and while Amazon cannot provide our proprietary software, the pricing of Amazon’s offerings may limit our ability to adjust,” the company wrote in the filing, which also lists Endeca, FAST, Autonomy and several others as key competitors.

This is our first look at Elastic’s financials. The company brought in $159.9 million in revenue in the 12 months ended July 30, 2018, up roughly 100 percent from $88.1 million the year prior. Losses are growing at about the same rate. Elastic reported a net loss of $18.5 million in the second quarter of 2018. That’s an increase from $9.9 million in the same period in 2017.

Founded in 2012, the company has raised about $100 million in venture capital funding, garnering a $700 million valuation the last time it raised VC, which was all the way back in 2014. Its investors include Benchmark, NEA and Future Fund, which each retain a 17.8 percent, 10.2 percent and 8.2 percent pre-IPO stake, respectively.

A flurry of business software companies have opted to go public this year. Domo, a business analytics company based in Utah, went public in June raising $193 million in the process. On top of that, subscription biller Zuora had a positive debut in April in what was a “clear sign post on the road to SaaS maturation,” according to TechCrunch’s Ron Miller. DocuSign and Smartsheet are also recent examples of both high-profile and successful SaaS IPOs.

Aug
26
2018
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Rebuilding employee philanthropy from the bottom up

In tech circles, it would be easy to assume that the world of high-impact charitable giving is a rich man’s game where deals are inked at exclusive black tie galas over fancy hors d’oeuvre. Both Mark Zuckerberg and Marc Benioff have donated to SF hospitals that now bear their names. Gordon Moore has given away $5B – including $600M to Caltech – which was the largest donation to a university at the time. And of course, Bill Gates has already donated $27B to every cause imaginable (and co-founded The Giving Pledge, a consortium of billionaires pledging to donate most of their net worth to charity by the end of their lifetime.)

For Bill, that means he has about $90B left to give.

For the average working American, this world of concierge giving is out of reach, both in check size, and the army of consultants, lawyers and PR strategists that come with it. It seems that in order to do good, you must first do well. Very well.

Bright Funds is looking to change that. Founded in 2012, this SF-based startup is looking to democratize concierge giving to every individual so they “can give with the same effectiveness as Bill and Melinda Gates.” They are doing to philanthropy what Vanguard and Wealthfront have done for asset management for retail investors.

In particular, they are looking to unlock dollars from the underutilized corporate benefit of matching funds for donations, which according to Bright Funds is offered by over 60% of medium to large enterprises, but only used by 13% of employees at these companies. The need for such a service is clear — these programs are cumbersome, transactional, and often offline. Make a donation, submit a receipt, and wait for it to churn through the bureaucratic machine of accounting and finance before matching funds show up weeks later.

Bright Funds is looking to make your company’s matching funds benefit as accessible and important to you as your free lunches or massages. Plus, Bright Funds charges companies per seat, along with a transaction fee to cover the cost of payment processing, sparing employees any expense.

It’s a model that is working. According to Bright Fund’s CEO Ty Walrod, Bright Funds customers see on average a 40% year-over-year increase in funds donated through the platform. More importantly, Bright Funds not only transforms an employee’s relationship to personal philanthropy, but also to the company they work for.

Grassroots Giving

This model of bottoms-up giving is a welcome change from the big foundation model which has recently been rocked by scandal. The Silicon Valley Community Foundation was the go-to foundation for The Who’s Who of Silicon Valley elite. It rode the latest tech boom to become the largest community foundation in eleven short years with generous stock donations from donors like Mark Zuckerberg ($1.8 billion), GoPro’s Nicholas Woodman ($500 million), and WhatsApp co-founder Jan Koum ($566 million). Today, at $13.5 billion, it surpasses the 80+ year old Ford Foundation in endowment size.

However, earlier this year, their star fundraiser Mari Ellen Loijens (credited with raising $8.3B of the $13.5B) was accused of repeatedly bullying and sexually harassing coworkers, allegations that the Foundation had “known about for years” but failed to act upon. In 2017, a similar case occurred when USC’s star fundraiser David Carrera  stepped down on charges of sexual harassment after leading the university’s historic $6 billion fundraising campaign.

While large foundations and endowments do important work, their structure relies too much on whale hunting for big checks, giving an inordinate amount of power to the hands of a small group of talented fund raisers.

This stands in contrast to Bright Funds’ ethos — to lead a grassroots movement in empowering individual employees to make their dollar of giving count.

Rebuilding charitable giving for the platform age

Bright Funds is the latest iteration of a lineup of workplace giving platforms. MicroEdge and Cybergrants paved the way in the 80s and 90s by digitizing the giving experience, but was mainly on-premise, and lacked a focus on user experience. Benevity and YourCause arrived in 2007 to bring workplace giving to the cloud, but they were still not turnkey solutions that could be easily implemented.

Bright Funds started as a consumer platform, and has retained that heritage in its approach to product design, aiming to reduce friction for both employee and company adoption. This is why many of their first customers were midsized tech startups with limited resources and looking for a turnkey solution, including Eventbrite, Box, Github, and Contently . They are now finding their way upmarket into larger, more established enterprises like Cisco, VMWare, Campbell’s Soup Company, and Sunpower.

Bright Funds approach to product has brought a number of innovations to this space.

The first is the concept of a cause-focused “fund.” Similar to a mutual fund or ETF, these funds are portfolios of nonprofits curated by subject-matter experts tailored to a specific cause area (e.g. conservation, education, poverty, etc.). This solves one of the chief concerns of any donor — is my dollar being put to good use towards the causes I care about? Passionate about conservation? Invest with Jim Leape from the Stanford Woods Institute for the Environment, who brings over three decades of conservation experience in choosing the six nonprofits in Bright Fund’s conservation portfolio. This same expertise is available across a number of cause areas.

Additionally, funds can also be created by companies or employees. This has proven to be an important rallying point for emergency relief during natural disasters, where employees at companies can collectively assemble a list of nonprofits to donate to. In 2017, Cisco employees donated $1.8 million (including company matching) through Bright Funds to Hurricanes Harvey, Maria, and Irma as well as the central Mexico earthquakes, the current flooding in India and many more.

The second key feature of their product is the impact timeline, a central news feed to understand where your dollars are going across all your cause areas. This transforms giving from a black box transaction to an ongoing dialogue between you and your charities.

Lastly, Bright Funds wants to take away all the administrative burden that might come with giving and volunteering — everything from tracking your volunteer opportunities and hours, to one-click tax reporting across all your charitable donations. In short, no more shoeboxes of receipts to process through in April.

Doing good & doing well

Although Bright Funds is focused on transforming the individual giving experience, it’s paying customer at the end of the day is the enterprise.

And although it is philanthropic in nature, Bright Funds is not exempt from the procurement gauntlet that every enterprise software startup faces — what’s in it for the customer? What impact does workplace giving and volunteering have on culture and the bottom line?

To this end, there is evidence to show that corporate social responsibility has a an impact on recruiting the next generation of workers. A study by Horizon Media found that 81% of millennials expect their companies to be good corporate citizens. A separate 2015 study found that 62% of millennials said they’d take a pay cut to work for a company that’s socially responsible.

Box, one of Bright Fund’s early customers, has seen this impact on recruiting firsthand (disclosure: Box is one of my former employers). Like most tech companies competing for talent in the Valley, Box used to give out lucrative bonuses for candidate referrals. They recently switched to giving out $500 in Bright Funds gift credit. Instead of seeing employee referrals dip, Box saw referrals “skyrocket,” according to Box.org Executive Director Bryan Breckenridge. This program has now become “one of the most cherished cultural traditions at Box,” he said.

Additionally, like any corporate benefit, there should be metrics tied to employee retention. Benevity released a study of 2 million employees across 118 companies on their platform that showed a 57% reduction in turnover for employees engaged in corporate giving or volunteering efforts. VMware, one of Bright Fund’s customers, has seen an astonishing 82% of their 22,000 employees participate in their Citizen Philanthropy program of giving and volunteering, according to VMware Foundation Director Jessa Chin. Their full-time voluntary turnover rate (8%) is well below the software industry average of 13.2%.

Towards a Brighter Future

Bright Funds still has a lot of work to do. CEO Walrod says that one of his top priorities is to expand the platform beyond US charities, finding ways to evaluate and incorporate international nonprofits.

They have also not given up their dream of becoming a truly consumer platform, perhaps one day competing in the world of donor-advised funds, which today is largely dominated by big names like Fidelity and Schwab who house over $85B of assets. In the short term, Walrod wants to make every Bright Funds account similar to a 401K account. It goes wherever you work, and is a lasting record of the causes you care about, and the time and resources you’ve invested in them.

Whether the impetus is altruism around giving or something more utilitarian like retention, companies are increasingly realizing that their employees represent a charitable force that can be harnessed for the greater good. Bright Funds has more work to do like any startup, but it is empowering the next set of donors who can give with the same effectiveness as Gates, and one day, at the same scale as him as well.

Aug
09
2018
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Blissfully grabs $3.5 million seed investment to help companies get their SaaS in gear

Blissfully, a New York City startup that helps companies understand their SaaS usage inside their organizations, announced it has received a $3.5 million seed round.

The investment was led by Hummer Winblad Venture Partners. Hubspot, Founder Collective, and several unnamed pre-seed investors also participated. They got a $1.5 million pre-seed investment, bringing the total so far to $5 million, according the company.

Company co-founder and CEO Ariel Diaz says Blissfully actually helped him and his co-founder solve a problem they were having tracking the SaaS usage at their previous startups. Like many companies, they were using spreadsheets to track this information and they found it was untenable as the company grew beyond 30 or 40 people. They figured there had to be a better way, so they built one.

Their product is much more than simply a database of the SaaS products in use inside an organization. It can integrate with existing company systems like single sign-on tools such as Okta and OneLogIn, financial reporting systems and G Suite login information. “We are trying to automate as much of the data collection as possible to discover what you’re using, who’s using it and how much you are spending,” he said.

Blissfully SaaS report. Screenshot: Blissfully

Their scans often turn up products customers thought they had canceled or those that IT had asked employees to stop using. More than finding Shadow IT, the product also gives insight to overall SaaS spend, which many companies have trouble getting a grip on. They can find most usage with a scan. Some data such as customized contract information may have to be manually entered into the system, he says.

Hubspot CEO Brian Halligan, whose company is one of the investors in this round, sees a growing need for this kind of tool. “The widespread growth of SaaS across companies of all sizes is a leading indicator of the market need for Blissfully. As business’ investments in SaaS increase, they lose visibility into issues ranging from spending to security,” Halligan said in a statement.

The company offers a freemium and pay model and is available in the G Suite Marketplace. If you go for the free version, you can scan your systems for SaaS usage, but if you want to do more complex integrations with company systems, you have to pay. They currently have 10 employees and 500 customers with a mix of paying and free.

One interesting aspect of the Blissfully tool is that it is built entirely using Serverless architecture on AWS Lambda.

Jul
30
2018
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A pickaxe for the AI gold rush, Labelbox sells training data software

Every artificial intelligence startup or corporate R&D lab has to reinvent the wheel when it comes to how humans annotate training data to teach algorithms what to look for. Whether it’s doctors assessing the size of cancer from a scan or drivers circling street signs in self-driving car footage, all this labeling has to happen somewhere. Often that means wasting six months and as much as a million dollars just developing a training data system. With nearly every type of business racing to adopt AI, that spend in cash and time adds up.

Labelbox builds artificial intelligence training data labeling software so nobody else has to. What Salesforce is to a sales team, Labelbox is to an AI engineering team. The software-as-a-service acts as the interface for human experts or crowdsourced labor to instruct computers how to spot relevant signals in data by themselves and continuously improve their algorithms’ accuracy.

Today, Labelbox is emerging from six months in stealth with a $3.9 million seed round led by Kleiner Perkins and joined by First Round and Google’s Gradient Ventures.

“There haven’t been seamless tools to allow AI teams to transfer institutional knowledge from their brains to software,” says co-founder Manu Sharma. “Now we have over 5,000 customers, and many big companies have replaced their own internal tools with Labelbox.”

Kleiner’s Ilya Fushman explains that “If you have these tools, you can ramp up to the AI curve much faster, allowing companies to realize the dream of AI.”

Inventing the best wheel

Sharma knew how annoying it was to try to forge training data systems from scratch because he’d seen it done before at Planet Labs, a satellite imaging startup. “One of the things that I observed was that Planet Labs has a superb AI team, but that team had been for over six months building labeling and training tools. Is this really how teams around the world are approaching building AI?,” he wondered.

Before that, he’d worked at DroneDeploy alongside Labelbox co-founder and CTO Daniel Rasmuson, who was leading the aerial data startup’s developer platform. “Many drone analytics companies that were also building AI were going through the same pain point,” Sharma tells me. In September, the two began to explore the idea and found that 20 other companies big and small were also burning talent and capital on the problem. “We thought we could make that much smarter so AI teams can focus on algorithms,” Sharma decided.

Labelbox’s team, with co-founders Ysiad Ferreiras (third from left), Manu Sharma (fourth from left), Brian Rieger (sixth from left) Daniel Rasmuson (seventh from left)

Labelbox launched its early alpha in January and saw swift pickup from the AI community that immediately asked for additional features. With time, the tool expanded with more and more ways to manually annotate data, from gradation levels like how sick a cow is for judging its milk production to matching systems like whether a dress fits a fashion brand’s aesthetic. Rigorous data science is applied to weed out discrepancies between reviewers’ decisions and identify edge cases that don’t fit the models.

“There are all these research studies about how to make training data” that Labelbox analyzes and applies, says co-founder and COO Ysiad Ferreiras, who’d led all of sales and revenue at fast-rising grassroots campaign texting startup Hustle. “We can let people tweak different settings so they can run their own machine learning program the way they want to, instead of being limited by what they can build really quickly.” When Norway mandated all citizens get colon cancer screenings, it had to build AI for recognizing polyps. Instead of spending half a year creating the training tool, they just signed up all the doctors on Labelbox.

Any organization can try Labelbox for free, and Ferreiras claims hundreds have. Once they hit a usage threshold, the startup works with them on appropriate SaaS pricing related to the revenue the client’s AI will generate. One called Lytx makes DriveCam, a system installed on half a million trucks with cameras that use AI to detect unsafe driver behavior so they can be coached to improve. Conde Nast is using Labelbox to match runway fashion to related items in their archive of content.

Eliminating redundancy, and jobs?

The big challenge is convincing companies that they’re better off leaving the training software to the experts instead of building it in-house where they’re intimately, though perhaps inefficiently, involved in every step of development. Some turn to crowdsourcing agencies like CrowdFlower, which has their own training data interface, but they only work with generalist labor, not the experts required for many fields. Labelbox wants to cooperate rather than compete here, serving as the management software that treats outsourcers as just another data input.

Long-term, the risk for Labelbox is that it’s arrived too early for the AI revolution. Most potential corporate customers are still in the R&D phase around AI, not at scaled deployment into real-world products. The big business isn’t selling the labeling software. That’s just the start. Labelbox wants to continuously manage the fine-tuning data to help optimize an algorithm through its entire life cycle. That requires AI being part of the actual engineering process. Right now it’s often stuck as an experiment in the lab. “We’re not concerned about our ability to build the tool to do that. Our concern is ‘will the industry get there fast enough?’” Ferreiras declares.

Their investor agrees. Last year’s big joke in venture capital was that suddenly you couldn’t hear a startup pitch without “AI” being referenced. “There was a big wave where everything was AI. I think at this point it’s almost a bit implied,” says Fushman. But it’s corporations that already have plenty of data, and plenty of human jobs to obfuscate, that are Labelbox’s opportunity. “The bigger question is ‘when does that [AI] reality reach consumers, not just from the Googles and Amazons of the world, but the mainstream corporations?’”

Labelbox is willing to wait it out, or better yet, accelerate that arrival — even if it means eliminating jobs. That’s because the team believes the benefits to humanity will outweigh the transition troubles.

“For a colonoscopy or mammogram, you only have a certain number of people in the world who can do that. That limits how many of those can be performed. In the future, that could only be limited by the computational power provided so it could be exponentially cheaper” says co-founder Brian Rieger. With Labelbox, tens of thousands of radiology exams can be quickly ingested to produce cancer-spotting algorithms that he says studies show can become more accurate than humans. Employment might get tougher to find, but hopefully life will get easier and cheaper too. Meanwhile, improving underwater pipeline inspections could protect the environment from its biggest threat: us.

“AI can solve such important problems in our society,” Sharma concludes. “We want to accelerate that by helping companies tell AI what to learn.”

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