Sep
05
2018
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Forethought looks to reshape enterprise search with AI

Forethought, a 2018 TechCrunch Disrupt Battlefield participant, has a modern vision for enterprise search that uses AI to surface the content that matters most in the context of work. Its first use case involves customer service, but it has a broader ambition to work across the enterprise.

The startup takes a bit of an unusual approach to search. Instead of a keyword-driven experience we are used to with Google, Forethought uses an information retrieval model driven by artificial intelligence underpinnings that they then embed directly into the workflow, company co-founder and CEO Deon Nicholas told TechCrunch. They have dubbed their answer engine “Agatha.”

Much like any search product, it begins by indexing relevant content. Nicholas says they built the search engine to be able to index millions of documents at scale very quickly. It then uses natural language processing (NLP) and natural language understanding (NLU) to read the documents as a human would.

“We don’t work on keywords. You can ask questions without keywords and using synonyms to help understand what you actually mean, we can actually pull out the correct answer [from the content] and deliver it to you,” he said.

One of first use cases where they are seeing traction in is customer support. “Our AI, Agatha for Support, integrates into a company’s help desk software, either Zendesk, Salesforce Service Cloud, and then we [read] tickets and suggest answers and relevant knowledge base articles to help close tickets more efficiently,” Nicholas explained. He claims their approach has increased agent efficiency by 20-30 percent.

The plan is to eventually expand beyond the initial customer service use case into other areas of the enterprise and follow a similar path of indexing documents and embedding the solution into the tools that people are using to do their jobs.

When they reach beta or general release, they will operate as a cloud service where customers sign up, enter their Zendesk or Salesforce credentials (or whatever other products happen to be supported at that point) and the product begins indexing the content.

The founding team, mostly in their mid-20s, have had a passion for artificial intelligence since high school. In fact, Nicholas built an AI program to read his notes and quiz him on history while still in high school. Later, at the University of Waterloo, he published a paper on machine learning and had internships at Palantir, Facebook and Dropbox. His first job out of school was at Pure Storage. All these positions had a common thread of working with data and AI.

The company launched last year and they debuted Agatha in private beta four months ago. They currently have six companies participating, the first of which has been converted to a paying customer.

They have closed a pre-seed round of funding too, and although they weren’t prepared to share the amount, the investment was led by K9 Ventures. Village Global, Original Capital and other unnamed investors also participated.

Sep
05
2018
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McCarthyFinch AI services platform automates tedious legal tasks

McCarthyFinch sounds a bit like a law firm — and with good reason. The startup has developed an AI as a Service platform aimed at the legal profession. This week, it’s competing in the 2018 TechCrunch Disrupt Battlefield in San Francisco.

The company began life as a project at a leading New Zealand law firm, MinterEllisonRuddWatts. They wanted to look at how they could take advantage of AI to automate legal processes to make them more efficient, cost-effective and faster, according to company president Richard DeFrancisco.

“They were working on leveraging technology to become the law firm of the future, and they realized there were some pretty tremendous gaps,” he explained. They found a bunch of Ph.Ds working on artificial intelligence who worked with more than 30 lawyers over time to address those gaps by leveraging AI technology.

That internal project was spun out as a startup last year, emerging as an AI platform with 18 services. MinterEllison, along with New Zealand VC Goat Ventures, gave the fledgling company US$2.5 million in pre-seed money to get started.

The company looked at automating a lot of labor-intensive tasks related to legal document review and discovery such as document tagging. “Lawyers spend a lot of time tagging things with regards to what’s relevant and not relevant, and it’s not a good use of their time. We can go through millions of documents very quickly,” DeFrancisco said. He claims they can lower the time it takes to tag a set of documents in a lawsuit from weeks to minutes.

He says that one of their key differentiators is their use of natural language processing (NLP), which he says allows the company to understand language and nuance to interpret documents with a high level of accuracy, even when there are small data sets. Instead of requiring thousands of documents to train their models, which he says law firms don’t have time to do, they can begin to understand the gist of a case in as little as two or three documents with 90 percent accuracy, based on their tests.

They don’t actually want to sell their platform directly to law firms. Instead, they hope to market their artificial intelligence skills as a service to other software vendors with a legal bent who are looking to get smarter without building their own AI from scratch.

“What we are doing is going to technology service providers and talking to them about using our solution. We have restful APIs to integrate into their technology and do a Powered By-model,” DeFrancisco explained.

The startup currently has 10 trials going on. While he couldn’t name them, he did say that they include the largest law firm in Europe, largest global provider of legal information and the fastest growing SaaS company in history. They are also working on agreements with large systems integrators including Deloitte and Accenture to act as resellers of their solution.

While they are based in New Zealand, they plan to open a U.S. office in the Los Angeles area shortly after Disrupt. The engineering team will remain in New Zealand, and DeFrancisco will build the rest of the company in the U.S as it seeks to expand its reach. They also plan to start raising their next round of funding.


Sep
05
2018
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PoLTE lets you track devices using LTE signal

Meet PoLTE, a Dallas-based startup that wants to make location-tracking more efficient. Thanks to PoLTE’s software solution, logistics and shipment companies can much more easily track packages and goods. The startup is participating in TechCrunch’s Startup Battlefield at Disrupt SF.

If you want to use a connected device to track a package, you currently need a couple of things — a way to determine the location of the package, and a way to transmit this information over the air. The most straightforward way of doing it is by using a GPS chipset combined with a cellular chipset.

Systems-on-chip have made this easier as they usually integrate multiple modules. You can get a GPS signal and wireless capabilities in the same chip. While GPS is insanely accurate, it also requires a ton of battery just to position a device on a map. That’s why devices often triangulate your position using Wi-Fi combined with a database of Wi-Fi networks and their positions.

And yet, using GPS or Wi-Fi as well as an LTE modem doesn’t work if you want to track a container over multiple weeks or months. At some point, your device will run out of battery. Or you’ll have to spend a small fortune to buy a ton of trackers with big batteries.

PoLTE has developed a software solution that lets you turn data from the cell modem into location information. It works with existing modems and only requires a software update. The company has been working with Riot Micro for instance.

Behind the scene PoLTE’s magic happens on their servers. IoT devices don’t need to do any of the computing. They just need to send a tiny sample of LTE signals and PoLTE can figure out the location from their servers. Customers can then get this data using an API.

It only takes 300 bytes of data to get location information with precision of less than a few meters. You don’t need a powerful CPU, Wi-Fi, GPS or Bluetooth.

“We offer 80 percent cost reduction on IoT devices together with longer battery life,” CEO Ed Chao told me.

On the business side, PoLTE is using a software-as-a-service model. You can get started for free if you don’t need a lot of API calls. You then start paying depending on the size of your fleet of devices and the number of location requests.

It doesn’t really matter if the company finds a good business opportunity. PoLTE is a low-level technology company at heart. Its solution is interesting by itself and could help bigger companies that are looking for an efficient location-tracking solution.


May
15
2018
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Aircall raises another $29 million

French startup Aircall has raised a funding round of $29 million for its cloud based call center solution. Draper Esprit led the round with NextWorld Capital, Balderton Capital and Newfund also participating.

The company has raised $40.5 million in total. Aircall participated in the Startup Battlefield at TechCrunch Disrupt SF a few years ago. The company first started at eFounders.

Aircall is following the software-as-a-service playbook. First, you take a boring industry like phone systems for large support and sales teams. Second, you bet everything on software. And third, you keep adding new features and integrations, and chasing new customers.

The company now has two offices in New York and Paris and handles millions of calls every day. With today’s funding round, the company plans to hire more people in both offices.

When you sign up to Aircall, you get virtual phone numbers in one or multiple countries. You can then configure a greeting message, add business hours and handle your call queue.

But the magic happens when you have multiple people handling sales or support calls. When someone calls, it can ring multiple people at once or someone specific first, then a second person if the first person isn’t available, etc. You get an overview of all your calls so you can assign them, tag them and more.

Aircall doesn’t work in a vacuum. So you can integrate Aircall with CRMs and other solutions like Salesforce, Zendesk and Zoho. The startup also launched a deep integration with Intercom that lets you switch from a text conversation to a phone call from the popup window.

It’s hard to list all the features right here. But chances are that if you’re running a call center, you’ll have everything you need for your team. Aircall currently costs $30 to $50 per user and per month to access all of this.

Sep
18
2017
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Goodbye, photo studios. Hello, colormass virtual photoshoots

 Berlin-based colormass, one of the startups presenting today at TechCrunch Disrupt as part of the Battlefield, has developed a platform that lets you recreate an IKEA-style experience for your own merchandise: highly realistic, but digitally manipulated 3D facsimiles. Read More

May
16
2017
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DefinedCrowd is teaching machines to better understand the complexities of language

 What DefinedCrowd offers isn’t particularly easily to distill into a quick elevator pitch. Taking the stage today as part of the Disrupt New York Battlefield, the Washington state-based company deals in complex concepts of machine learning, providing rich data sets for speech and natural language processing systems. Read More

May
16
2017
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Nexla launches data operations platform with $3.5 million investment

 Nexla, a competitor in the TechCrunch Disrupt Battlefield this week in New York City, has more on its plate than simply impressing the judges. It also chose to launch at the event and, while it was at it, announced $3.5 million in funding led by Blumberg Capital with participation from Storm Ventures, Engineering Capital and Correlation Ventures. Read More

May
16
2017
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With version 2.0, Crate.io’s database tools put an emphasis on IoT

 Crate.io, the winner of our Disrupt Europe 2014 Battlefield, is launching version 2.0 of its CrateDB database today. The tool, which is available in both an open source and enterprise version, started out as a general-purpose but highly scalable SQL database. Over time, though, the team found that many of its customers were using the service for managing their machine data. Read More

May
15
2017
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Riminder uses deep learning to better match people to jobs

 There’s nothing efficient about sorting through 30,000 resumes by hand. Recruiters spend months evaluating applicants only to have great prospective candidates get lost in the pile. At TechCrunch’s Startup Battlefield, French startup Riminder made the case for how its deep learning-powered platform could augment recruiters — helping them better surface ideal contenders for… Read More

May
15
2017
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NuCypher is using proxy re-encryption to lift more enterprise big data into the cloud

 After spending time at a London fintech accelerator last year, enterprise database startup ZeroDB scrapped its first business plan and mapped out a new one. By January this year it had a new name: NuCypher. It now will try to persuade enterprises to switch to their specialized encryption layer to enhance their ability to perform big data analytics by tapping into the cloud. Read More

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