We produce huge amounts of data — not just in aggregate on networks synonymous with big data like Google or Facebook — but as siloed users as well. Just have a look at your inbox: Hundreds of messages a day, sent and received, deliverables requested or completed. A goldmine of potentially useful information.
Tools such as Google’s Inbox and Notion are already emerging as smarter mailboxes that can make sense of your email network. They can help answer questions like:
Which emails really need my attention? How long have I been waiting for a response from Sarah on that market data? How long does it usually take me to respond to Tom?
There are two limitations to this approach:
First, everyone uses email differently and every organisation has different requirements and data needs. A solution to our data mess must be open, accessible and modular in order to solve the deluge of small pain points we encounter at home, at work and in between.
Second, email does not exist in a vacuum and it is increasingly just one among a mix of channels we use for our work communication. Slack, Facebook Messenger, WhatsApp are all increasingly home to the same valuable exchanges that were once the exclusive realm of email. To get a full and truly actionable picture, the approach must be able to cover all of these channels at arms-length, and plug-in other complementary data streams from IoT.
For years we have each been accumulating ever more data from these sources, but the tools available to us users to make sense of this data have not changed at all.
Then we met Red Sift.
Or more specifically we caught up with Rahul Powar and Randal Pinto, who Tom had previously crossed paths with at Shazam and Apsmart.
Rahul was part of the founding team at Shazam where he held the role of Chief Technical Architect among others. He left to found Apsmart where Randal was one of the first hires — it was acquired by Reuters in 2012.
In our meeting room in London they introduced us to what they were building – PaaS for your data.
They conjured up a picture of a platform that would bring the power of machine learning tools already making sense of the world’s data to bear on our own personal data sets.
At first this would be email, everyone’s biggest data dump, but the platform would quickly expand to Slack, Facebook Messenger, other communication services and IoT streams.
The platform would be home to data apps called “Sifts”, open-source micro services, that can be built or forked by any developer to run secure computations on your data and deliver them back in-situ or on a dashboard.
One of my favourite Sifts demonstrates this quite nicely (and simply): It is trained to monitor my emails for taxi receipts and aggregates that data to provide a running tally of my spending split between Hailo, Uber, etc.
To build the platform, Rahul and Randal had put together crack team of developer talent with expertise across the stack and an eye for design and interfaces. They keep things agile and lean while continuing to attract the best.
Around the board table, we are pleased to have co-lead this investment with Christian from White Star Capital, with his expertise in scaling software platforms as an operator as well as an investor and a foot on each side of the Atlantic.
At Oxford Capital, we are thrilled to join Red Sift for the ride as they build a platform that could change the way we all work with our data, a home for a new kind of data app that will help businesses and people do more of what they do best while wasting less time sifting through their data mess.
Red Sift is now in open beta. Developers can give it a try here and start by forking an existing Sift or go straight to building new ones.