Jun
04
2020
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Searchable.ai nabs additional $4M seed to continue building AI-driven search

Searchable.ai is an early-stage startup in the alpha phase of testing its initial product, but it has an idea compelling enough to attract investment, even during a pandemic. Today the company announced an additional $4 million in seed capital to continue building its AI-driven search solution.

Susquehanna International Group and Omicron Media co-led the round, with participation by Defy Partners, NextView Ventures and a group of unnamed angel investors. Today’s investment comes on top of the $2 million in seed money the startup announced in October.

Company co-founder and CEO Brian Shin said that when he presented to his investors in early March at the last event he attended before everything shut down, they approached him about additional money, and given the economic uncertainty, he decided to take it.

“Honestly we probably would not have taken additional money if it was not for the uncertainty around the macro environment right now,” he told TechCrunch.

The company is trying to solve enterprise search and, being pre-revenue, Shin recognized that having additional capital would give them more room to build the product and get it to market.

“We are trying to solve this problem where people just can’t find information that they need in order to do their jobs. When you look within the workplace, this problem is just getting worse and worse with the proliferation of different formats and people storing their information in many different places, local networks, cloud repositories, email and Slack,” he explained.

They have a few thousand people in the alpha program right now testing a personal desktop version of the application that helps individual users find their content wherever it happens to be. The plan is to open that up to a wider group soon.

The road map calls for a teams version, where groups of employees can search among their different individual repositories; a developer version to build the search technology into other operations; and eventually an enterprise tool. They also want to add voice search starting with an Alexa skill, with the general belief that we need to move beyond keyword searches to more natural language approaches.

“We believe that there’ll be a whole new category of search, search companies and search products that are more conversational. […] Being able to interact with your information more naturally, more and more conversationally, that’s where we think the market is going,” he said.

The company now has more money in the bank to help achieve that vision.

May
11
2020
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Amazon releases Kendra to solve enterprise search with AI and machine learning

Enterprise search has always been a tough nut to crack. The Holy Grail has always been to operate like Google, but in-house. You enter a few keywords and you get back that nearly perfect response at the top of the list of the results. The irony of trying to do search locally has been a lack of content.

While Google has the universe of the World Wide Web to work with, enterprises have a much narrower set of responses. It would be easy to think that should make it easier to find the ideal response, but the fact is that it’s the opposite. The more data you have, the more likely you’ll find the correct document.

Amazon is trying to change the enterprise search game by putting it into a more modern machine learning-driven context to use today’s technology to help you find that perfect response just as you typically do on the web.

Today the company announced the general availability of Amazon Kendra, its cloud enterprise search product that the company announced last year at AWS re:Invent. It uses natural language processing to allow the user to simply ask a question, then searches across the repositories connected to the search engine to find a precise answer.

“Amazon Kendra reinvents enterprise search by allowing end-users to search across multiple silos of data using real questions (not just keywords) and leverages machine learning models under the hood to understand the content of documents and the relationships between them to deliver the precise answers they seek (instead of a random list of links),” the company described the new service in a statement.

AWS has tuned the search engine for specific industries including IT, healthcare and insurance. It promises energy, industrial, financial services, legal, media and entertainment, travel and hospitality, human resources, news, telecommunications, mining, food and beverage and automotive will be coming later this year.

This means any company in one of those industries should have a head start when it comes to searching because the system will understand the language specific to those verticals. You can drop your Kendra search box into an application or a website, and it has features like type ahead you would expect in a tool like this.

Enterprise search has been around for a long time, but perhaps by bringing AI and machine learning to bear on it, we can finally solve it once and for all.

Dec
03
2019
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AWS announces new enterprise search tool powered by machine learning

Today at AWS re:Invent in Las Vegas, the company announced a new search tool called Kendra, which provides natural language search across a variety of content repositories using machine learning.

Matt Wood, AWS VP of artificial intelligence, said the new search tool uses machine learning, but doesn’t actually require machine learning expertise of any kind. Amazon is taking care of that for customers under the hood.

You start by identifying your content repositories. This could be anything from an S3 storage repository to OneDrive to Salesforce — anywhere you store content. You can use pre-built connectors from AWS, provide your credentials and connect to all of these different tools.

Kendra then builds an index based on the content it finds in the connected repositories, and users can begin to interact with the search tool using natural language queries. The tool understands concepts like time, so if the question is something like “When is the IT Help Desk is open,” the search engine understands that this is about time, checks the index and delivers the right information to the user.

The beauty of this search tool is not only that it uses machine learning, but based on simple feedback from a user, like a smiley face or sad face emoji, it can learn which answers are good and which ones require improvement, and it does this automatically for the search team.

Once you have it set up, you can drop the search on your company intranet or you can use it internally inside an application and it behaves as you would expect a search tool to do, with features like type ahead.

Oct
28
2019
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Stealthy search startup Searchable.ai snags $2M seed

Searchable.ai wants to solve an old problem around search in the enterprise. The stealthy startup announced a $2 million seed round.

Defy Partners led the round with a slew of other participants, including Paul English, co-founder of Kayak; Wayne Chang, co-founder of Crashlytics; Brian Halligan, co-founder and CEO of HubSpot; Jonathan Kraft, president and COO of the Kraft Group and the New England Patriots; MIT Prof. Edward Roberts; Eric Dobkin, founder and chairman emeritus of Goldman Sachs Global Equity Capital Markets; and Susquehanna International Group.

The prestigious group of investors saw that Searchable.ai is trying to solve a big problem around findability. Company co-founder Brian Shin says that knowledge workers have been struggling for years trying to find a way to better utilize all of the information that exists within an organization.

“The problem we’re really solving is that there are a trillion documents created every year in Microsoft Office, Google Docs, etc., and it’s really difficult if you’re a knowledge worker to find what you need in terms of either a document, an asset like a slide or worksheet within a document or the actual answer to a question that you have,” Shin said.

The questioning part could be particularly valuable because it lets you ask a natural language question and find a specific piece of information within a document, rather than just the document itself. “Let’s say you have a giant spreadsheet, you could actually ask a question of all your spreadsheets and find the atomic unit of knowledge that you’re actually looking for,” he said.

The product itself is not quite ready for the big reveal, but if it works as described, it will be a huge boost to knowledge workers who have continually struggled to find a nugget of information they know is out there across the myriad documents in an organization.

Shin is an experienced entrepreneur who has helped launch and sell three companies. He reports he has raised $100 million in venture capital and most recently has worked as a venture capitalist himself, but he saw this opportunity and decided to jump back into the development side of things.

He admits he’s giving up a lot to go back to the startup lifestyle, but he and his co-founders decided this was worth it. “You know the draw, the compulsion to do another startup is is really what this is about. So my three other colleagues and I have have all started companies before and we’re all giving up big jobs to do this, and I’m so excited about the team and the massive opportunity.”

He promised more details about the company and the solution would be coming early next year.

Sep
18
2019
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Salesforce brings AI power to its search tool

Enterprise search tools have always suffered from the success of Google. Users wanted to find the content they needed internally in the same way they found it on the web. Enterprise search has never been able to meet those lofty expectations, but today Salesforce announced Einstein Search, an AI-powered search tool for Salesforce users that is designed to point them to the exact information for which they are looking.

Will Breetz, VP of product management at Salesforce, says that enterprise search has suffered over the years for a variety of reasons. “Enterprise search has gotten a bad rap, but deservedly so. Part of that is because in many ways it is more difficult than consumer search, and there’s a lot of headwinds,” Breetz explained.

To solve these issues, the company decided to put the power of its Einstein artificial intelligence engine to bear on the problem. For starters, it might not know the popularity of a given topic like Google, but it can learn the behaviors of an individual and deliver the right answer based on a person’s profile, including geography and past activity to deliver a more meaningful answer.

Einstein Search Personal

Image: Salesforce

Next, it allows you to enter natural language search phrasing to find the exact information you need, and the search tool understands and delivers the results. For instance, you could enter, “my open opportunities in Boston” and using natural language understanding, the tool can translate that into the exact set of results you are looking for — your open opportunities in Boston. You could use conventional search to click a series of check boxes to narrow the list of results to only Boston, but this is faster and more efficient.

Finally, based on what the intelligence engine knows about you, and on your search parameters, it can predict the most likely actions you want to take and provide quick action buttons in the results to help you do that, reducing the time to action. It may not seem like much, but each reduced workflow adds up throughout a day, and the idea is to anticipate your requirements and help you get your work done more quickly.

Salesforce appears to have flipped the enterprise search problem. Instead of having a limited set of data being a handicap for enterprise search, it is taking advantage of that, and applying AI to help deliver more meaningful results. It’s for a limited set of findings for now, such as accounts, contacts and opportunities, but the company plans to add options over time.

Dec
04
2018
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Forethought scores $9M Series A in wake of Battlefield win

It’s been a whirlwind few months for Forethought, a startup with a new way of looking at enterprise search that relies on artificial intelligence. In September, the company took home the TechCrunch Disrupt Battlefield trophy in San Francisco, and today it announced a $9 million Series A investment.

It’s pretty easy to connect the dots between the two events. CEO and co-founder Deon Nicholas said they’ve seen a strong uptick in interest since the win. “Thanks to TechCrunch Disrupt, we have had a lot of things going on including a bunch of new customer interest, but the biggest news is that we’ve raised our $9 million Series A round,” he told TechCrunch.

The investment was led by NEA with K9 Ventures, Village Global and several angel investors also participating. The angel crew includes Front CEO Mathilde Collin, Robinhood CEO Vlad Tenev and Learnvest CEO Alexa von Tobel.

Forethought aims to change conventional enterprise search by shifting from the old keyword kind of approach to using artificial intelligence underpinnings to retrieve the correct information from a corpus of documents.

“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,” Nicholas told TechCrunch in September.

He points out that it’s still early days for the company. It had been in stealth for a year before launching at TechCrunch Disrupt in September. Since the event, the three co-founders have brought on six additional employees and they will be looking to hire more in the next year, especially around machine learning and product and UX design.

At launch, they could be embedded in Salesforce and Zendesk, but are looking to expand beyond that.

The company is concentrating on customer service for starters, but with the new money in hand, it intends to begin looking at other areas in the enterprise that could benefit from a smart information retrieval system. “We believe that this can expand beyond customer support to general information retrieval in the enterprise,” Nicholas said.

Nov
30
2018
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DoJ charges Autonomy founder with fraud over $11BN sale to HP

U.K. entrepreneur turned billionaire investor Mike Lynch has been charged with fraud in the U.S. over the 2011 sale of his enterprise software company.

Lynch sold Autonomy, the big data company he founded back in 1996, to computer giant HP for around $11 billion some seven years ago.

But within a year around three-quarters of the value of the business had been written off, with HP accusing Autonomy’s management of accounting misrepresentations and disclosure failures.

Lynch has always rejected the allegations, and after HP sought to sue him in U.K. courts he countersued in 2015.

Meanwhile, the U.K.’s own Serious Fraud Office dropped an investigation into the Autonomy sale in 2015 — finding “insufficient evidence for a realistic prospect of conviction.”

But now the DoJ has filed charges in a San Francisco court, accusing Lynch and other senior Autonomy executives of making false statements that inflated the value of the company.

They face 14 counts of conspiracy and fraud, according to Reuters — a charge that carries a maximum penalty of 20 years in prison.

We’ve reached out to Lynch’s fund, Invoke Capital, for comment on the latest development.

The BBC has obtained a statement from his lawyers, Chris Morvillo of Clifford Chance and Reid Weingarten of Steptoe & Johnson, which describes the indictment as “a travesty of justice,”

The statement also claims Lynch is being made a scapegoat for HP’s failures, framing the allegations as a business dispute over the application of U.K. accounting standards. 

Two years ago we interviewed Lynch onstage at TechCrunch Disrupt London and he mocked the morass of allegations still swirling around the acquisition as “spin and bullshit.”

Following the latest developments, the BBC reports that Lynch has stepped down as a scientific adviser to the U.K. government.

“Dr. Lynch has decided to resign his membership of the CST [Council for Science and Technology] with immediate effect. We appreciate the valuable contribution he has made to the CST in recent years,” a government spokesperson told it.

Oct
18
2018
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Seva snares $2.4M seed investment to find info across cloud services

Seva, a New York City startup, that wants to help customers find content wherever it lives across SaaS products, announced a $2.4 million seed round today. Avalon Ventures led the round with participation from Studio VC and Datadog founder and CEO Olivier Pomel.

Company founder and CEO Sanjay Jain says that he started this company because he felt the frustration personally of having to hunt across different cloud services to find the information he was looking for. When he began researching the idea for the company, he found others who also complained about this fragmentation.

“Our fundamental vision is to change the way that knowledge workers acquire the information they need to do their jobs from one where they have to spend a ton of time actually seeking it out to one where the Seva platform can prescribe the right information at the right time when and where the knowledge worker actually needs it, regardless of where it lives.”

Seva, which is currently in Beta, certainly isn’t the first company to try to solve this issue. Jain believes that with a modern application of AI and machine learning and single sign-on, Seva can provide a much more user-centric approach than past solutions simply because the technology wasn’t there yet.

The way they do this is by looking across the different information types. Today they support a range of products including Gmail, Google Calendar, Google Drive,, Box, Dropbox, Slack and JIRA, Confluence. Jain says they will be adding additional services over time.

Screenshot: Seva

Customers can link Seva to these products by simply selecting one and entering the user credentials. Seva inherits all of the security and permissioning applied to each of the services, so when it begins pulling information from different sources, it doesn’t violate any internal permissioning in the process.

Jain says once connected to these services, Seva can then start making logical connections between information wherever it lives. A salesperson might have an appointment with a customer in his or her calendar, information about the customer in a CRM and a training video related to the customer visit. It can deliver all of this information as a package, which users can share with one another within the platform, giving it a collaborative element.

Seva currently has 6 employees, but with the new funding is looking to hire a couple of more engineers to add to the team. Jain hopes the money will be a bridge to a Series A round at the end of next year by which time the product will be generally available.

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.

Feb
09
2017
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Swiftype launches a new product to help companies search across Dropbox, Office, G Suite and more

Swiftype Swiftype started out helping publishers like TechCrunch offer better site search, but it’s been expanding into other areas like customer support and e-commerce. Now it’s making its biggest leap yet, with the launch of an enterprise search product. Basically, Swiftype is offering large and small businesses a place where they can search all their documents and files across a variety… Read More

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