Personal blog of Yzmir Ramirez

Managed by Q, the office management platform based out of New York, has today been acquired by The We Company, formerly known as WeWork.

Financial terms were not disclosed. The WSJ reports that it was a cash and stock deal. Managed by Q, which has 500 employees, will remain as a wholly owned separate entity and CEO Dan Teran will remain following the acquisition to join WeWork leadership.

Upon its latest financing in January, Managed by Q was valued at $249 million, according to PitchBook.

Here’s what Teran had to say in a prepared statement:

We are excited for this incredible opportunity to deepen our commitment to realizing our ambitious vision of building an operating system for the built world. WeWork is uniquely positioned to invest in workplace technology and services, and I look forward to partnering with their team to build more robust products for our clients and create a global platform to help companies push the bounds on our collective potential.

Managed by Q was founded in 2014 with a plan to change the way that offices run. The platform allowed office managers and other decision-makers to handle supply stocking, cleaning, IT support and other non-work related tasks in the office by simply using the Managed by Q dashboard. Managed by Q serves the demand through a combination of in-house operators and third-party vendors and service providers.

Notably, Managed by Q took a different tack than most other logistics companies, employing their operators as W2 workers instead of 1099 contractors. Moreover, Managed by Q offered a stock option plan to operators that gives 5 percent of the company back to those employees.

The company has raised a total of $128.25 million since launch from investors such as GV, RRE and Kapor Capital. Managed by Q currently serves the markets of New York, San Francisco, Los Angeles, Chicago, Boston and Silicon Valley, with plans to aggressively expand following the acquisition, according to the WSJ.

Not only has Managed by Q swiftly matured into a big player in the NY tech scene and Future of Work space, but it has also fostered interesting competition and consolidation within the space. Managed by Q has itself made several acquisitions, including the purchase of NVS (an office space planning and project management service) and Hivy (an internal comms tool to let employees tell office managers what they need).

Deep learning involves a highly iterative process where data scientists build models and test them on GPU-powered systems until they get something they can work with. It can be expensive and time-consuming, often taking weeks to fashion the right model. New startup Determined AI wants to change that by making the process faster, cheaper and more efficient. It emerged from stealth today with $11 million in Series A funding.

The round was led by GV (formerly Google Ventures) with help from Amplify Partners, Haystack and SV Angel. The company also announced an earlier $2.6 million seed round from 2017, for a total $13.6 million raised to date.

Evan Sparks, co-founder and CEO at Determined AI, says that up until now, only the largest companies like Facebook, Google, Apple and Microsoft could set up the infrastructure and systems to produce sophisticated AI like self-driving cars and voice recognition technologies. “Our view is that a big reason why [these big companies] can do that is that they all have internal software infrastructure that enables their teams of machine learning engineers and data scientists to be effective and produce applications quickly,” Sparks told TechCrunch.

Determined’s idea is to create software to handle everything from managing cluster compute resources to automating workflows, thereby putting some of that big-company technology within reach of any organization. “What we exist to do is to build that software for everyone else,” he said. The target market is Fortune 500 and Global 2000 companies.

The company’s solution is based on research conducted over the last several years at AmpLab at the University of California, Berkeley (which is probably best known for developing Apache Spark). It used the knowledge generated in the lab to build sophisticated solutions that help make better use of a customer’s GPU resources.

“We are offering kind of a base layer that is scheduling and resource sharing for these highly expensive resources, and then on top of that we’ve layered some services around workflow automation.” Sparks said the team has generated state of the art results that are somewhere between five and 50 times faster than the results from tools that are available to most companies today.

For now, the startup is trying to help customers move away from generic kinds of solutions currently available to more customized approaches, using Determined AI tools to help speed up the AI production process. The money from today’s round should help fuel growth, add engineers and continue building the solution.

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