Sep
19
2018
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Einstein Voice gives Salesforce users gift of gab

Salespeople usually spend their days talking. They are on the phone and in meetings, but when it comes to updating Salesforce, they are back at the keyboard again typing notes and milestones, or searching for metrics about their performance. Today, Salesforce decided to change that by introducing Einstein Voice, a bit of AI magic that allows salespeople to talk to the program instead of typing.

In a world where Amazon Alexa and Siri make talking to our devices more commonplace in our non-work lives, it makes sense that companies are trying to bring that same kind of interaction to work.

In this case, you can conversationally enter information about a meeting, get daily briefings about key information on your day’s meetings (particularly nice for salespeople who spend their day in the car) and interact with Salesforce data dashboards by asking questions instead of typing queries.

All of these tools are designed to make life easier for busy salespeople. Most hate doing the administrative part of their jobs because if they are entering information, even if it will benefit them having a record in the long run, they are not doing their primary job, which is selling stuff.

For the meetings notes part, instead of typing on a smartphone, which can be a challenge anyway, you simply touch Meeting Debrief in the Einstein Voice mobile tool and start talking to enter your notes. The tool interprets what you’re saying. As with most transcription services, this is probably not perfect and will require some correcting, but should get you most of the way there.

It can also pick out key data like dates and deal amounts and let you set action items to follow up on.

Gif: Salesforce

Brent Leary, who is the founder and principal analyst at CRM Essentials says this is a natural progression for Salesforce as people get more comfortable using voice interfaces. “I think this will make voice-first devices and assistants as important pieces to the CRM puzzle from both a customer experience and an employee productivity perspective,” he told TechCrunch.

It’s worth pointing out that Tact.AI has been giving Salesforce users these kind of voice services for some time, and Tact CEO Chuck Ganapathi doesn’t seem too concerned about Salesforce jumping in.

“Conversational AI is the future of enterprise software and it’s not a question of if or when. It’s all about the how, and we strongly believe that a Switzerland strategy is the only way to deliver on its promise. It’s no wonder we are the only company to be backed by Microsoft, Amazon and Salesforce,” he said.

Leary things there’s plenty of room for everyone and Salesforce getting involved will accelerate adoption for all players. “The Salesforce tide will lift all boats, and companies like Tact will see their profile increased significantly because while Salesforce is the leader in the category, its share of the market is still less than 20% of the market.”

Einstein is Salesforce’s catch-all brand for its artificial intelligence layer. In this case it’s using natural language processing, voice recognition technology and other artificial intelligence pieces to interpret the person’s voice and transcribe what they are saying or understand their request better.

Typically, Salesforce starts with a small set of functionality and the builds on that over time. That’s very likely what they are doing here, coming out with a product announcement in time for Dreamforce, their massive customer conference next week,

Sep
19
2018
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Fresh out of Y Combinator, Leena AI scores $2M seed round

Leena AI, a recent Y Combinator graduate focusing on HR chatbots to help employees answer questions like how much vacation time they have left, announced a $2 million seed round today from a variety of investors including Elad Gil and Snapdeal co-founders Kunal Bahl and Rohit Bansal.

Company co-founder and CEO Adit Jain says the seed money is about scaling the company and gaining customers. They hope to have 50 enterprise customers within the next 12-18 months. They currently have 16.

We wrote about the company in June when it was part of the Y Combinator Summer 2018 class. At the time Jain explained that they began in 2015 in India as a company called Chatteron. The original idea was to help others build chatbots, but like many startups, they realized there was a need not being addressed, in this case around HR, and they started Leena AI last year to focus specifically on that.

As they delved deeper into the HR problem, they found most employees had trouble getting answers to basic questions like how much vacation time they had or how to get a new baby on their health insurance. This forced a call to a help desk when the information was available online, but not always easy to find.

Jain pointed out that most HR policies are defined in policy documents, but employees don’t always know where they are. They felt a chatbot would be a good way to solve this problem and save a lot of time searching or calling for answers that should be easily found. What’s more, they learned that the vast majority of questions are fairly common and therefore easier for a system to learn.

Employees can access the Leena chatbot in Slack, Workplace by Facebook, Outlook, Skype for Business, Microsoft Teams and Cisco Spark. They also offer Web and mobile access to their service independent of these other tools.

Photo: Leena AI

What’s more, since most companies use a common set of backend HR systems like those from Oracle, SAP and NetSuite (also owned by Oracle), they have been able to build a set of standard integrators that are available out of the box with their solution.

The customer provides Leena with a handbook or a set of policy documents and they put their machine learning to work on that. Jain says, armed with this information, they can convert these documents into a structured set of questions and answers and feed that to the chatbot. They apply Natural Language Processing (NLP) to understand the question being asked and provide the correct answer.

They see room to move beyond HR and expand into other departments such as IT, finance and vendor procurement that could also take advantage of bots to answer a set of common questions. For now, as a recent YC graduate, they have their first bit of significant funding and they will concentrate on building HR chatbots and see where that takes them.

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.

Aug
17
2018
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Klarity uses AI to strip drudgery from contract review

Klarity, a member of the Y Combinator 2018 Summer class, wants to automate much of the contract review process by applying artificial intelligence, specifically natural language processing.

Company co-founder and CEO Andrew Antos has experienced the pain of contract reviews first hand. After graduating from Harvard Law, he landed a job spending 16 hours a day reviewing contract language, a process he called mind-numbing. He figured there had to be a way to put technology to bear on the problem and Klarity was born.

“A lot of companies are employing internal or external lawyers because their customers, vendors or suppliers are sending them a contract to sign,” Antos explained They have to get somebody to read it, understand it and figure out whether it’s something that they can sign or if it requires specific changes.

You may think that this kind of work would be difficult to automate, but Antos said that  contracts have fairly standard language and most companies use ‘playbooks.’ “Think of the playbook as a checklist for NDAs, sales agreements and vendor agreements — what they are looking for and specific preferences on what they agree to or what needs to be changed,” Antos explained.

Klarity is a subscription cloud service that checks contracts in Microsoft Word documents using NLP. It makes suggestions when it sees something that doesn’t match up with the playbook checklist. The product then generates a document, and a human lawyer reviews and signs off on the suggested changes, reducing the review time from an hour or more to 10 or 15 minutes.

Screenshot: Klarity

They launched the first iteration of the product last year and have 14 companies using it with 4 paying customers so far including one of the world’s largest private equity funds. These companies signed on because they have to process huge numbers of contracts. Klarity is helping them save time and money, while applying their preferences in a consistent fashion, something that a human reviewer can have trouble doing.

He acknowledges the solution could be taking away work from human lawyers, something they think about quite a bit. Ultimately though, they believe that contract reviewing is so tedious, it is freeing up lawyers for work that requires a greater level of intellectual rigor and creativity.

Antos met his co-founder and CTO, Nischal Nadhamuni, at an MIT entrepreneurship class in 2016 and the two became fast friends. In fact, he says that they pretty much decided to start a company the first day. “We spent 3 hours walking around Cambridge and decided to work together to solve this real problem people are having.”

They applied to Y Combinator two other times before being accepted in this summer’s cohort. The third time was the charm. He says the primary value of being in YC is the community and friendships they have formed and the help they have had in refining their approach.

“It’s like having a constant mirror that helps you realize any mistakes or any suboptimal things in your business on a high speed basis,” he said.

Jul
17
2018
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Dialpad dials up $50M Series D led by Iconiq

Dialpad announced a $50 million Series D investment today, giving the company plenty of capital to keep expanding its business communications platform.

The round was led by Iconiq Capital with help from existing investors Andreessen Horowitz, Amasia, Scale Ventures, Section 32 and Work-Bench. With today’s round, the company has now raised $120 million.

As technology like artificial intelligence and internet of things advances, it’s giving the company an opportunity to expand its platform. Dialpad products include UberConference conferencing software and VoiceAI for voice transcription applications.

The company is competing in a crowded market that includes giants like Google and Cisco and a host of smaller companies like GoToMeeting (owned by LogMeIn), Zoom and BlueJeans. All of these companies are working to provide cloud-based meeting and communications services.

Increasingly, that involves artificial intelligence like natural language processing (NLP) to provide on the fly transcription services. While none of these services is perfect yet, they are growing increasingly accurate.

VoiceAI was launched shortly after Dialpad acquired TalkIQ in May to take this idea a step further by applying sentiment analysis and analytics to voice transcripts. The company plans to use the cash infusion to continue investing in artificial intelligence on the Dialpad platform.

Post call transcript generated by VoiceAI. Screenshot: Dialpad

CEO Craig Walker certainly sees the potential of artificial intelligence for the company moving forward. “Smart CIOs know AI isn’t just another trendy tech tool, it’s the future of work. By arming sales and support teams, and frankly everybody in the organization, with VoiceAI’s real-time artificial intelligence and insights, businesses can dramatically improve customer satisfaction and ultimately their bottom line,” Walker said in a statement.

Dialpad is also working with voice-driven devices like the Amazon Alexa and it announced Alexa integration with Dialpad in April. This allows Alexa users to make calls by saying something like, “Alexa, call Liz Green with Dialpad” and the Echo will make the phone call on your behalf using Dialpad software.

According to the company website, it has over 50,000 customers including WeWork, Stitch Fix, Uber and Reddit. The company says it has added over 10,000 new customers since its last funding round in September, 2017.

Mar
22
2018
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IBM can’t stop milking the Watson brand

More than seven years after IBM Watson beat a couple of human Jeopardy! champions, the company has continued to make hay with the brand. Watson, at its core, is simply an artificial intelligence engine and while that’s not trivial by any means, neither is it the personified intelligence that their TV commercials would have the less technically savvy believe.

These commercials contribute to this unrealistic idea that humans can talk to machines in this natural fashion. You’ve probably seen some. They show this symbol talking to humans in a robotic voice explaining its capabilities. Some of the humans include Bob Dylan, Serena Williams and Stephen King.

In spite of devices like Alexa and Google Home, we certainly don’t have machines giving us detailed explanations, at least not yet.

IBM would probably be better served aiming its commercials at the enterprises it sells to, rather than the general public, who may be impressed by a talking box having a conversation with a star. However, those of us who have at least some understanding of the capabilities of such tech, and those who buy it, don’t need such bells and whistles. We need much more practical applications. While chatting with Serena Williams about competitiveness may be entertaining, it isn’t really driving home the actual value proposition of this tech for business.

The trouble with using Watson as a catch-all phrase is that it reduces the authenticity of the core technology behind it. It’s not as though IBM is alone in trying to personify its AI though. We’ve seen the same thing from Salesforce with Einstein, Microsoft with Cortana and Adobe with Sensei. It seems that these large companies can’t deliver artificial intelligence without hiding it behind a brand.

The thing is this though, this is not a consumer device like the Amazon Echo or Google Home. It’s a set of technologies like deep learning, computer vision and natural language processing, but that’s hard to sell, so these companies try to put a brand on it like it’s a single entity.

Just this week, at the IBM Think Conference in Las Vegas, we saw a slew of announcements from IBM that took on the Watson brand. That included Watson Studio, Watson Knowledge Catalog, Watson Data Kits and Watson Assistant. While they were at it, they also announced they were beefing up their partnership Apple with — you guessed it — Watson and Apple Core ML. (Do you have anything without quite so much Watson in it?)

Marketers gonna market and there is little we can do, but when you overplay your brand, you may be doing your company more harm than good. IBM has saturated the Watson brand, and might not be reaching the intended audience as a result.

Mar
07
2018
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Voicera lands $13.5 million with help from big-time enterprise investors

 It seems that everyone agrees that meetings are a time suck. There have been many attempts to use technology to make it easier to organize and run them, but Voicera, a Bay area startup, is attacking the problem from a different angle. It wants to make it simpler to record meetings and pull out action items automatically using artificial intelligence. Today, it announced a $13.5 million Series… Read More

Mar
07
2018
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Voicera lands $13.5 million with help from big enterprise investors

It seems that everyone agrees that meetings are a time suck. There have been many attempts to use technology to make it easier to organize and run them, but Voicera, a Bay area startup, is attacking the problem from a different angle. It wants to make it simpler to record meetings and pull out action items automatically using artificial intelligence. Today, it announced a $13.5 million Series A from a mix of venture capital firms and big-time enterprise investors.

For starters on the venture capital side, the round was led by e.ventures with participation from Battery Ventures, GGV Capital and Greycroft. The big enterprise investors included Cisco Investments, GV (the investment firm affiliated with Google), Microsoft Ventures, Salesforce Ventures and Workday Ventures. Today’s investment brings the total raised to over $20 million.

While some companies like Zoom, BlueJeans and GoToMeeting want to help run the meeting and others like Cisco’s Voice Control Assistant want to help you control the nuts and bolts of the meeting using your voice, Voicera wants to concentrate on the meeting transcription side of the equation.

“The whole idea [behind the company] is to focus on conversation and not be distracted by the act of taking notes,” company CEO and founder Omar Tawakol told TechCrunch.

The company’s product is called Eva, an AI-fueled automated note-taking assistant. Eva’s job is to record the meeting, create a transcription, identify the important stuff and send out an email with the highlights to all meeting participants. That’s the ideal anyway.

For now, the transcription while decent, still requires some human oversight to correct errors. While you can specifically tell Eva to record an action item, the goal is to tune the artificial intelligence and machine learning so that the bot can eventually handle this task with as little human intervention as possible.

Voicer interface with meeting highlights. Screenshot: Voicera

The product has a number of integrations including Salesforce, Slack and email. You can share the transcript or action items with these other tools when appropriate. For instance, if you record a meeting with a new customer, the integration allows you to automatically create or update a Salesforce CRM record with data from the meeting.

For now, they are trying err on the side of privacy and are giving meeting participants full control over the transcript with the ability to delete it if they wish. Tawakol says they recognize this is a social experiment and people need to get used to the idea of being recorded and putting the note taking into the hands of technology.

The product is free for now while it’s still in Beta, but in the near future it will move to a subscription model. There will still be a free version, but also various tiers for individuals, teams and enterprises. The pricing is still being worked out, but Tawakol wants to keep it to around $10 a month for an individual user.

Note: We originally published this article as a $20 million Series A. We regret the error.

Sep
19
2017
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Google Cloud’s Natural Language API gets content classification and more granular sentiment analysis

 Google Cloud announced two updates this morning to its Natural Language API. Specifically users will now have access to content classification and entity sentiment analysis. These features are particularly valuable for brands and media companies For starters, GCP users will now be able to tag content as corresponding with common topics like health, entertainment and law (cc: Henry).… Read More

May
11
2017
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Salesforce aims to save you time by summarizing emails and docs with machine intelligence

 We have all seen the studies — some American workers spend upwards of six hours a day handling email. It’s not a great use of time, it destroys productivity and it ultimately costs businesses money. A new paper written by a team Salesforce MetaMind researchers could eventually provide summaries of professional communication. More effective text summarization tools would… Read More

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