About mabb0tt

helping engineers engineer their companies, helping designers design their companies

the bigger story behind ClearStory’s Data Intelligence

i know what you’re thinking — “another big data startup.” yes, it’s true, but beyond the cliche, there is truth and opportunity, and when it comes to larger enterprise businesses, small decisions can have tremendous effects — good and not so good — on the trajectory of a business. that’s where a company like ClearStory Data comes in. as i wrote about earlier at the time of our investment, larger amounts of data will undoubtedly lead to more noise, so businesses may place a premium on harnessing deep machine learning technologies to not only help with data sifting and analysis, but to also facilitate discovery of insights that the human eye may be incapable of observing.

ClearStory’s approach, announced today, is novel. by combining the power of its platform with various data sources and collaboration, Data Intelligence is enabled via a simple and intuitive user experience. up to this point, while decisions in the enterprise were often in consultation with the data, the data itself may not have been so good or as good as it could be – let alone collaboration around the data. here, there’s a larger trend afoot in the market for data intelligence and relative implications for how this data can inform decisions which directly tie to real returns on investment decisions within the enterprise.

the discovery from harnessing big data in the enterprise will spawn many new opportunities. as an investor, i’m obviously excited to meet founders who are thinking about using data to architect new systems and solutions, as well as new business models. it’s the deep learning from the data which excites me most — as the saying goes, “in God i trust, all others must bring data.” well, i’d put a spin on that — others may also want to bring data analysis tools and systems that can answer questions about the data in a collaborative manner in real time. in other words, the data is great, but not good enough anymore. it’s this “anymore” which creates the opportunity for the next set of founders to build something new, backed by hard data, which couldn’t have been known before.

proud to partner with Nivi, Naval, and the AngelList crew.

angellist-logo2

well, summer vacation in technology is certainly over. it’s already been an exciting month with news from apple, news from twitter, and as i’m writing this post about our investment in angellist — blackberry is being taken private. and it’s only monday!

back to angellist. as you may have seen, nivi and naval announced a new funding round for angellist, and i’m proud to be leading the investment in nivi, naval, and their colleagues on behalf of kleiner perkins. i’ve known naval for a number of years (back to when he was  starting vast an early investor in composite software jim armstrong introduced us) and we have always wanted to work together. so, when this opportunity developed, there was no way we were going to miss out on partnering.

everyone by now knows that a platform like angellist democratizes financing for startups. it also saves founders time. it enables investors outside of the valley to get access to early-stage deals and helps companies outside the valley echo chamber gain visibility. at kleiner, (like many other firms i imagine) we watch the angellist newsfeed and network with other peers.

on a personal level, as a former seed investor (before joining kleiner), i find the concept of syndicates to be incredibly compelling, both as a follower or the lead on an opportunity. if this existed years ago, maybe i would’ve started my own fund for syndicates!

again, i am very excited to work with nivi, naval, and the angellist crew!

data and the virtualized datacenter

logohello folks. it’s been a while since my last blog post about an investment, but there’s a good reason for that. and, yes, this is about another “big data” startup, but allow to me explain why i’m so excited to announce our latest investment: cloud physics


“big data, again?” you ask. it’s a fair question. big data exists everywhere, really…on twitter, on instagram, or inside AWS and other places you may not think of right away. well, what about the the data sitting inside data centers at the systems level? what if a group of highly experienced hardcore technologists left their cushy jobs to form a voltron-like team of exceptional engineers tackling hard problems around data and simulation?


it’s my job now as an investor to help identify, back, and in a small way, help guide the people and technologies that can breakthrough enterprise technology, and with cloud physics, i feel on the right track. led by john blumenthal (ex-VMware) along with irfan ahmad, jim kleckner, xiaojun liu, the leadership has built a team that can focus on making their customers’ virtualized data centers more efficient not only through software, but by finding patterns inside the collective data of across large numbers of virtualized environments. as new technology companies emerge and scale, virtual data center operations become significant costs, but necessary — therefore, finding improvements in those operations directly effect the bottom-line, and john and his colleagues from VMware had a great view into this opportunity given their experience.



i am very fortunate to partner with a team like cloud physics along side exceptional investors like (diane green, peter wagner and robin vasan from mayfield fund) makes my job easy and fun! what investor wouldn’t jump at the chance to help out the team who helped build the hypervisor and had the depth of operational experience to identify a big whole and market around managing virtualized environments? people want to simulate changes in an virtualized environment before deployment and/or capital expenditures, and set against the backdrop of a world where hybrid cloud management systems need continuous operational maintenance, a team like cloud physics is the type of team i want to back. you can read more about john and his team here.


if you have a deep insight into a market (with a novel technical approach) please drop me a line (regardless if its consumer or enterprise-oriented) . i can guarantee a quick response!