Author: Thomas Crown

Influential announced today that it has raised $12 million in Series B funding.

The funding came from existing investors Capital Zed, ECA Ventures, Paradigm Talent Agency, ROAR and Tech Coast Angels, as well as from Hollywood agency WME .

Just a couple weeks ago, Influential said it was working with (and had raised money from) WME. The agency is the first to try out a new Influential product called Talent Pro, which gives agents access to social data around a broader pool of talent.

Influential founder and CEO Ryan Detert said the product will allow WME — and, in the future, other agencies — to sweeten endorsement and promotional deals with more data and to “take an A-list celebrity… and now surround that person with 10 lookalike influencers who are not celebrities themselves.”

One of Influential’s big selling points is its use of artificial intelligence (it’s a developer partner with IBM Watson) to help brands and marketers find influencers who would be a good fit for their campaigns. However, Detert acknowledged that selling access to social media influencers is starting to feel overhyped — as he put it, “People think of influencer marketing sometimes as a four-letter word.”

But in Detert’s view, influencer marketing is just one “tactic” that Influential supports: “We consider ourselves more of social intelligence and activation company.”

And in fact, Influential already offers a social intelligence product that helps customers get a broader understanding of things like the broader competitive landscape.

Detert also said Influential is working to measure the impact of brands’ social media campaigns, so that when they pay an influencer to make a promotional post, they “can actually map back that not only [the consumer] saw it, but that they engaged with it to make a real-world decision — walking into a location, buying a product in a grocery store.”

The company has now raised a total of $26.5 million.

from TechCrunch

Email and a smarter notebook might be enough for handling communication for projects or experiments inside a team in a lab in some university basement. But when you have around 200 scientists working on discovering something new — say, a new drug — that communication process is going to quickly break down, and Sajith Wickramasekara that sits somewhere between science and software.

That’s the goal for Benchling, which Wickramasekara hopes will make life easier for researchers and help simplify and speed up the process of scientific discovery. Specializing in life sciences, Benchling aims to create a comprehensive suite of tools that help researchers thoroughly log their processes and collaborate among other scientists. Benchling looks to provide a rigorous platform that can take a lot of the work away from researchers, who instead might be documenting everything in email, Excel sheets, or just in a notebook somewhere. Benchling said it has raised a $14.5 million round of financing led by Benchmark Capital, with participation from F-Prime Capital and Thrive Capital. Benchmark’s Eric Vishria is joining the company’s board of directors.

“I was always planning to go to grad school to become a scientist,” Wickramasekara said. “Obviously since I’m working here I took a kind of left turn. As someone who was doing both science and software, on the software side of things I felt like i had really great tools for working with other people, and on the science side I felt like there were really great scientific tools but not great tools for working with other people.”

At its core, Benchling is a suite of applications and tools that include ways to design experiments as well as document them during that process. Researchers can track materials they are producing, manage their physical inventory — like even tubes or containers — and helps scientists standardize and easily query information from existing or previous runs. The service seeks to capture all of this in some unified platform that a company can deploy across a whole fleet of researchers and teams. Wickramasekara says more than 100,000 scientists are using the platform.

Benchling was initially born as a sort of smart notebook for scientists and academics. While that’s where it got started — and where a lot of the learning happened — eventually the team ended up creating something a little more formalized that it could sell as an actual product. That step proved a little more challenging as academics tend to be either alone or in small teams, so they don’t necessarily need the robust tools that a product like Benchling might have when commercialized.

“The freeform nature of a lab notebook is actually sufficient [for academia],” Wickramasekara said. “In the industry, that’s where all the structure comes in. We have a team as part of our customer success and implementation, we help customers come up with the right model and complexity and adjust their business processes. At the end fo the day, all these customers do something slightly differently. But we work with probably more than 80 customers and 25 do antibody research, so we figure out all the best practices over time. We help customers think about the tradeoffs vs one data model for another.”

Benchling also offers those same employees a suite of auditing tools, which Wickramasekara would be critical as it looked to move into larger companies that are dealing with more sensitive IP. For a company looking to discover new drugs, keeping that process under tight control is especially important — especially when they are working with organizations like the FDA. Benchling admins get a comprehensive view of who is doing what within the system, as well as guidelines around documentation.

Part of the challenge will be catering to all the niches and needs these individual companies might have throughout their own unique experimentation processes. Each lab is different, with its own quirks, and Benchling aims to be a unified platform that covers as many scenarios as possible, even with help tuning and adjustable models. So that means that there is room for other tools that could tap other niches and becomes the one-size-fits-all. But over time and with enough data, a tool like Benchling could figure out not only the best practices for specific labs, but also ones they should use — and then cover all those bases.

from TechCrunch

PatSnap, a Euro-Asian company that offers a patent and R&D platform and services, has pulled in a $38 million Series D funding round led by existing investors Sequoia and Shunwei Capital, the investment firm founded by Xiaomi co-founder and CEO Lei Jun. Southeast Asia’s Qualgro also took part.

All three backed the company in 2016 when it led an undisclosed Series C round. While PatSnap didn’t give a figure for that previous round, it is saying this time around that it has raised over $100 million to date. Doing some quick via math via figures on Crunchbase suggests that the Series C was something in the region of $50 million.

PatSnap was founded in 2007 and it is based out of the UK and Singapore, with locations in China and the U.S.. The company started out as essentially a directory for IP, helping companies — and particularly enterprises — pull in data for R&D and product development purposes.

The company claims 8,000 clients worldwide, with the U.S. its largest market for revenue. PatSnap said that in China, its second-largest market and a major focus for the firm, it said it has more than 4,500 clients. In addition to its core service, it is focused on going beyond a data repository to offer services for enterprises that help manage internal product development and other R&D initiatives.

“Patent data let us kick down the door and earn respect, but now we’re looking at completely different products,” Ray Chohan, SVP of corporate strategy at PatSnap told TechCrunch in an interview. “We are working on new products for R&D with a long-term view of becoming the software stack for R&D teams.”

That’s exactly how this new capital will be put to work, Tiong said. Related to that, the company plans to open an office in Toronto, Canada, for development. Already, the company has 700 staff across a range of offices that include London (commercial), China (product), Singapore (machine learning) and LA (go to market).

Series D is a fairly advanced stage for a startup in Southeast Asia (and London) and exits are something that the tech industry is giving more thought to given the growth of the ecosystem, and events such as Sea’s U.S. listing last year. Despite that, Chohan — who founded the company’s London-based office — said that he’s not thinking too hard about the future for now.

“Our obsession is our employees, customers and building great products, if we can do that then the byproduct of a liquidity event will happen by itself,” he explained.

Chohan added that PatSnap is “well funded” and on course to become profitable over the next two to three years.

from TechCrunch

Farmdrop, the farmer-friendly online grocery platform based in the U.K., has picked up £10 million in new funding. New investors in this Series B round include LGT Impact Ventures (described as a growth equity investor that invests in businesses making a positive contribution to society), and Belltown Ventures, a renewable energy investment specialist with an interest in agricultural technology. Previous backer Atomico also followed on.

Founded by ex-city broker Ben Pugh in 2014, Farmdrop originally launched as a ‘click and collect’ service that let you order groceries online from farmer-producers to pick up at a local collection point. However, the company has since pivoted to door-to-door delivery but with the same basic idea of a marketplace that bypasses the mass supermarkets. It claims to give consumers much fresher produce, and farmer-producers a more generous share of the retail price. Large supermarkets are known for squeezing suppliers in a bid to lower prices whilst maintaining their own profits, after all.

“The fundamental problem is that the supermarket’s dominance over the last fifty years has put huge amounts of downward pressure on farmgate prices,” Pugh told me when Farmdrop raised its Series A. “In this environment, the only option for producers has been to focus on yields and durability which has led to a big depreciation in the taste and nutritional quality of homegrown foods”.

To that end, Farmdrop says it now sells over 2,000 products ranging from high-welfare meat, dairy, fish, organic fruit and veg, plus household supplies and larder items. It says that 80 percent of its fresh produce is sourced directly from 208 “sustainable farmers and independent food makers” and that since 2014 the startup has generated over £5 million in revenue for small-scale British farmers.

The new capital will be used to fund further U.K. expansion after the successful launch of a second hub in Bristol and Bath in September 2017, in addition to London. “Over the next six months Farmdrop will double the total number of households it can deliver to, initially growing in the South East but with plans for a northern hub in Manchester by end of 2019,” says the company.

More broadly, Farmdrop is tapping the rise of online grocery — even if the offline to online switch is still happening quite slowly — coupled with a growing demand for high-quality produce that comes from a more ethical/sustainable supply chain (Farmdrop also uses electric vans for the last few miles of delivery). It seems to be working, too: the startup says it is now on track to achieve £10 million in annualised revenues before the end of 2018.

Adds Niklass Zennström, Skype founder and CEO of Atomico: “What we find so compelling about Farmdrop is the way they’re using technology for good. By creating a direct route to market for farmers, Farmdrop is helping to create a healthier and more efficient supply chain. We’re proud to invest in such a fantastic team and are excited about helping them scale their innovative e-grocery platform.”

from TechCrunch

Samsung is diving deeper into artificial intelligence after it announced a new fund focused on AI technologies and startups.

The Korean firm’s ‘Samsung NEXT Q Fund’ is targeted at seed and Series A deals for startups that are “solving AI problems, as well as those using AI to solve computer science problems.” In particular, the announcement revealing the new fund mentioned areas that include learning in simulation, scene understanding, problem learning programs and human computer interaction.

The fund itself doesn’t have a dedicated kitty, it instead invests from Samsung’s $150 million U.S. Next Fund, which was announced last year and is focused on early-stage companies in emerging tech verticals.

The Q fund has already cut checks, though. To date it has backed a number of companies, one of which is Covariant.AI — a startup that teaches skills to robots.

“For the past ten years, we’ve watched software eat the world. Now, it’s AI’s turn to eat software. We’re launching Q Fund to support the next generation of AI startups who look to scratch beyond the surface of what we know today,” said Samsung NEXT Ventures’ Vincent Tang in a statement.

from TechCrunch