One-of-a-kind app for the enterprise Confide takes you off the record, with confidential messages that self-destruct.

The startup just stepped up its efforts in providing off-the-record communication in the digital world, with their latest release last week. With the Confide 3.0 for iOS and Android, it brings in 3 major additions to the existing app :

1. The user can send end-to-end encrypted, disappearing and screenshot-proof documents. Documents can be attached from Dropbox, Box, Google Drive, OneDrive or any other document storage app while allowing sending Word, Excel, PowerPoint and PDF documents that can only be viewed once and can’t be saved, printed, forwarded or screenshot.
2. Photos can also be end-to-end encrypted, and screenshot-proof.
3. Allowing for better integration, the app is now included in the phone’s “Share” options.

Other tweaks and enhancements include a preview option to see how a recipient would see the message, improved message reading tweaks, saving an email address or phone number within a message to the address book and opening a website URL from within a message.

Confide’s patent-pending technology pre-processes a document on the sender’s phone and sends it using a proprietary format, ensuring the recipient can only view it once. The “wanding” technique protects against screenshots, ensuring that only a small portion of the photo can be viewed at a time.

Unlike other messaging services that offer such confidentiality, Confide has businesses and enterprises in its cross-hairs. The launch of “Confide for Business” last December, has initiated “hundreds of inbound inquiries,” said Jon Brod, Co-founder and President at Confide. “[The] Sony hacks made the need very acute,” he says, according to Silicon Angle.

He further added, “It is becoming more and more accepted that anything we communicate digitally—via email, IM, text, et cetera—will be exposed at some point in the future.”

Founded a year ago by Howard Lerman, current chairman, Brod, Rich Hong, the CTO and Jeff Grossman, the CPO, Confide has found investors in Google Ventures, WGI Group and First Round, among others.

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(Image credit: Confide)

MapD, a Big Data analytics and visualization platform, has secured $1.5 million from Nvidia, Google Ventures, and other participatory investors, with the aim to fund its product development and its first commercial release, later this year, reports Venture Beat.

“There aren’t really any other tools on the market that allow truly interactive visualization and analytics on big data,” explained Todd Mostak, co-founder of Map-D, in a statement. “Map-D can query data at a rate of terabytes per second per server, something only possible by building the fastest possible software on the fastest possible hardware, GPUs”

An MIT spinoff, founded in 2013, MapD (Massively Parallel Database) is an analytics database created by Mostak and Thomas Graham with help from Prof. Sam Madden at MIT that allows interactive querying of big datasets and does so quite quick by tapping Nvidia’s graphics processing units (GPUs). VB reports that it delivers real-time data processing with millisecond latencies across billions of rows of data, all within the memory of the GPUs.

Map-D had won $100,000 from Nvidia at the Emerging Companies Summit in March. “Nvidia quickly recognized Map-D as a leader in the burgeoning ecosystem of big data solutions powered by GPUs,” pointed out Nvidia vice president of business development Jeff Herbst said in a statement adding that they were “delighted to award them the $100,000 first place prize at our Early Stage Challenge contest this past April. And we are equally excited to follow that up with an equity investment at this time.”

“We were impressed with the complexity of problems the Map-D platform could handle at amazing speeds using off-the-shelf GPUs,” noted Google Ventures general partner Rich Miner.

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(Image Credit: Capture Queen)

Monday saw the unveiling of Tamr, a scalable platform for data curation, at the Databeat Conference in San Francisco. Founders Andy Palmer and Michael Stonebraker also announced they had accrued an impressive $16 million of first-round funding from Google Ventures and New Enterprise Associates.

Palmer and Stonebraker came up with idea for the software during their research at MIT, during which they discovered a wide-spread demand amongst tech companies for software that would enable them to prepare data for analysis faster. “We came to the conclusion that what was required was something that automated the integration of new sources and new attributes over time and would insulate the system from the changes in the fundamental sources so that you didn’t have to go … and re-engineer from the top down all the time all this ETL [extract, transform, and load work],” said Palmer.

Tamr sits on top of the company’s exisiting databases and provides a holistic view across all of the systems. Through its machine learning algorithm, Tamr roots out similar sets of data across different databases and delivers a report on this data to the company. Each report item has a ‘confidence rating’ (i.e, an indicator of how certain the programme is that the datasets are similar). Human input is then required to decide if the data is similar; if it is, Tamr maps the two fields or collumns together, making the systems more cohesive and streamlined.

Using this software to integrate and combine datasets could give companies a competitive advantage in data analysis over firms who are only exploring one data set in isolation, rather than gaining a wider perspective. Rich Miner of Google Ventures, one of Tamr’s primary investors, said of its value: “Businesses can’t keep up with the number and depth of data sources exploding within their companies. Tamr combines machine learning and corporate knowledge to unlock a unified view of companies’ most valued data repositories.”

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(Photo credit: Tamr website)