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Comparing Enterprise Chatbots with Basic Chatbots

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“Hi, how can I help you?”

Chatbots have taken websites by storm. Conversational AI technologies have transformed customer service point-of-contact interactions in sectors like eCommerce, airlines, banking & financial services, insurance, manufacturing, telecommunications, and many others. They can be lightning quick to deploy, saving considerable time for both the client and the company.

In a world driven by the culture of immediacy and self-service, the provision of fast, high-quality responses to every request from customers and interested parties, all while reducing direct service contact, has become critical. To do so, chatbots are your best friend – but, not all chatbots are built the same. Here are some factors to consider when selecting your chatbot.

Different types of chatbot to drive your conversations

Many types of chatbots are available to meet different business needs and with so much choice available it can be challenging to make up your mind with confidence. First, ask yourself a few questions:

  • What is your goal? Do you want to provide short replies to simple questions or engage in deep conversations?
  • Do you want to give full freedom of inquiry to the customer, or do you want to limit the action options presented?
  • Where do you want to have the chatbot? (Website? Social Media? Everywhere?)
  • How much time do you have and what is your budget?

Having your replies to these questions in mind, you can start considering different types of chatbot and their relative complexity. However, even if your needs seem the height of simplicity, chatbots that are very basic may end up being an additional source of frustration for your customers. Fully-featured enterprise chatbots offer various functionalities to meet users’ expectations, and may be a better choice even in a comparatively simple application.

  • Menu/Button-based Chatbots

The most basic type of chatbot, this variety limits possibilities by offering the user a specific number of buttons. They can answer pre-defined questions and can facilitate the buying journey, for example by guiding user navigation of a website, but they are not able to solve complex requests. 

  • Keyword Recognition-based Chatbots

This type uses a basic analysis engine that recognizes some keywords, thus adding more interaction than menu/button-based chatbots. Users can interact by entering free text and receive a pre-loaded response based on the keywords identified and understood by the chatbot. This kind of system is good for exercising close control of your brand’s automated messaging. Inherent limitations include the potential misunderstanding of misspelled words, potentially generating user dissatisfaction. 

  • AI Chatbots – Service Quality on Another Level

Also called “contextual chatbots” or “conversational AI chatbots”, enterprise chatbots use advanced technology such as Machine Learning, Artificial Intelligence and/or Natural Language Processing to interact with users, and thereby are by far the most flexible and interactive solution. 

Not only do they understand whatever the user requests, from simple to complex, but they also remember conversations with previous users and improve their responses based on the context, can anticipate follow up questions, or even generate and send suggestions for customer’s next need on the basis of previous cases.

Enterprise chatbots can be specifically and finely tailored to requirements. Here are some features you will want to consider as you work through your chatbot project.

Must-have criteria for a great chatbot conversation 

  • Omni-Channel 

The shorter the path to information, the better. To do so, you need to implement a chatbot which can be accessible from multiple channels such as your website, Facebook, WhatsApp, and wherever else users or customers interact with you. Manage all these discussions through a single platform.

  • Third-Party Integrations 

Chatbots can serve different aspects of a business. Whether you want to help customer department, support the HR department or boost sales, you need a chatbot able to integrate with related third-party software: CRM software, Human Resource Information Systems (HRIS), or billing systems etc. By doing so, you open the gates for information to circulate easily from each third party to the bot to the person asking the question.

  • Escalation to Live Chat

Most customer interactions can be handled without a human agent, but technology cannot yet replace live agents in all cases. When complex cases arise, or when someone just wants to talk to a human, chatbots need to be able to transfer the conversation – including history and any other useful information – to a real agent. 

  • User Friendly

It is axiomatic that good design improves user experience. Chatbots do not offer many options in terms of flexibility in design but simply put, having an accessible and user-friendly platform will make the chatbot more pleasing to use. For instance, you want to have a chatbot that is going to display nicely on all types of devices, or that makes content easier to digest by avoiding long text blocs, or at most basic merely has a comfortable color scheme.

  • Analytics and Continuous Learning

A bot should also be able to learn from previous conversations and feedback to enhance customer experience. You want to know which are the popular interactions, discover the busiest moments, track the number of messages or users in a given frame of time. To do so, an archive of all past chats, errors, and failures should be recorded and downloadable to monitor and provide insights on the customer experience. 

  • First-Party Technology

Is it a first or a third-party technology? In the first-party case, the software editor completely manages, and owns the technology. Not only this ensures more responsiveness from the chatbot software vendor, but also it contributes to lowering costs of the overall project. 

  • Multilingual

A multilingual chatbot can lead a conversation in multiple languages during a live chat. The chat user selects the language in which they are most comfortable, and the bot adapts to the request. Having the multilingual option gives you broader horizons for business (better customer experience a greater geographic span, increased database etc.). The Inbenta Chatbot module has symbolic AI-fueled Natural Language Processing (NLP) technology at its core and can understand the nuances in 30+ languages.

Symbolic AI & NLP remain the key ingredients for success

To avoid the “it does not understand my request” feeling from the user, you need to invest in an NLP-based chatbot, using deep learning techniques to detect user intent. Thus, effectively imitated human interactions give the end-user the feeling that they are well understood and are having a real conversation rather than just being guided through a limited list of options, links, or FAQ chapters. 

Unlike keyword-based chatbots, enterprise chatbots associating Conversational AI technology and NLP understand the meaning behind words, or adapt to misspellings or slang, and thus provide a more smoothly organic user experience than any other type of chatbot.
The Inbenta enterprise chatbot goes one step further by detecting the meaning of words without the lengthy data training that is usually required by brute-force machine learning algorithms. With Inbenta’s chatbot module, you get the best solution in the market and remove the question of timing – Inbenta can be deployed within a matter of days.

Reduce your customer issue resolution times. Discover how the Inbenta AI Chatbot automatically engages in complex conversations, with minimal training.

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Source: https://www.inbenta.com/en/blog/basic-chatbot-versus-enterprise-chatbot/

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Optimal Dynamics nabs $22M for AI-powered freight logistics

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Join Transform 2021 this July 12-16. Register for the AI event of the year.


Optimal Dynamics, a New York-based startup applying AI to shipping logistics, today announced that it closed a $18.4 million round led by Bessemer Venture Partners. Optimal Dynamics says that the funds will be used to more than triple its 25-person team and support engineering efforts, as well as bolster sales and marketing departments.

Last-mile delivery logistics tends to be the most expensive and time-consuming part of the shipping process. According to one estimate, last-mile accounts for 53% of total shipping costs and 41% of total supply chain costs. With the rise of ecommerce in the U.S., retail providers are increasingly focusing on fulfilment and distribution at the lowest cost. Particularly in the construction industry, the pandemic continues to disrupt wholesalers — a 2020 Statista survey found that 73% of buyers and users of freight transportation and logistics services experienced an impact on their operations.

Founded in 2016, Optimal Dynamics offers a platform that taps AI to generate shipment plans likely to be profitable — and on time. The fruit of nearly 40 years of R&D at Princeton, the company’s product generates simulations for freight transportation, enabling logistics companies to answer questions about what equipment they should buy, how many drivers they need, daily dispatching, load acceptance, and more.

Simulating logistics

Roughly 80% of all cargo in the U.S. is transported by the 7.1 million people who drive flatbed trailers, dry vans, and other heavy lifters for the country’s 1.3 million trucking companies. The trucking industry generates $726 billion in revenue annually and is forecast to grow 75% by 2026. Even before the pandemic, last-mile delivery was fast becoming the most profitable part of the supply chain, with research firm Capgemini pegging its share of the pie at 41%.

Optimal Dynamics’ platform can perform strategic, tactical, and real-time freight planning, forecasting shipment events as far as two weeks in advance. CEO Daniel Powell — who cofounded the company with his father, Warren Princeton, a professor of operations research and financial engineering — says that the underlying technology was deployed, tested, and iterated with trucking companies, railroads, and energy companies, along with projects in health, ecommerce, finance, and materials science.

“Use of something called ‘high-dimensional AI’ allows us to take in exponentially greater detail while planning under uncertainty. We also leverage clever methods that allow us to deploy robust AI systems even when we have very little training data, a common issue in the logistics industry,” Powell told VentureBeat via email. “The results are … a dramatic increase in companies’ abilities to plan into the future.”

The global logistics market was worth $10.32 billion in 2017 and is estimated to grow to $12.68 billion USD by 2023, according to Research and Markets. Optimal Dynamics competes with Uber, which offers a logistics service called Uber Freight. San Francisco-based startup KeepTruckin recently secured $149 million to further develop its shipment marketplace. Next Trucking closed a $97 million investment. And Convoy raised $400 million at a $2.75 billion valuation to make freight trucking more efficient.

But 25-employee Optimal Dynamics investor Mike Droesch, a partner at BVP, says that demand remains strong for the company’s products. “Logistics operators need to consider a staggering number of variables, making this an ideal application for a software-as-a-service product that can help operators make more informed decisions by leveraging Optimal Dynamics industry leading technology. We were really impressed with the combination of their deep technology and the commercial impact that Optimal Dynamics is already delivering to their customers,” he said in a statement.

With the latest funding round, a series A, Optimal Dynamics has raised over $22 million to date. Beyond Bessemer, Fusion Fund, The Westly Group, TenOneTen Ventures, Embark Ventures, FitzGate Ventures, and John Larkin and John Hess also contributed .

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Source: https://venturebeat.com/2021/05/13/optimal-dynamics-nabs-22m-for-ai-powered-freight-logistics/

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Code-scanning platform BluBracket nabs $12M for enterprise security

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Join Transform 2021 this July 12-16. Register for the AI event of the year.


Code security startup BluBracket today announced it has raised $12 million in a series A round led by Evolution Equity Partners. The capital will be used to further develop BluBracket’s products and grow its sales team.

Detecting exploits in source code can be a pain point for enterprises, especially with the onset of containerization, infrastructure as code, and microservices. According to a recent Flexera report, the number of vulnerabilities remotely exploitable in apps reached more than 13,300 from 249 vendors in 2020. In 2019, Barracuda Networks found that 13% of security pros hadn’t patched their web apps over the past 12 months. And in a 2020 survey from Edgescan, organizations said it took them an average of just over 50 days to address critical vulnerabilities in internet-facing apps.

BluBracket, which was founded in 2019 and is headquartered in Palo Alto, California, scans codebases for secrets and blocks future commits from introducing new risks. The platform can monitor real-time risk scores across codebases, git configurations, infrastructure as code, code copies, and code access and resolve issues, detecting passwords and over 50 different types of tokens, keys, and IDs.

Code-scanning automation

Coralogix estimates that developers create 70 bugs per 1,000 lines of code and that fixing a bug takes 30 times longer than writing a line of code. In the U.S., companies spend $113 billion annually on identifying and fixing product defects.

BluBracket attempts to prevent this by proactively monitoring public repositories with the highest risk factors, generating reports for dev teams. It prioritizes commits based on their risk scores, minimizing duplicates using a tracking hash for every secret. A rules engine reduces false positives and scans for regular expressions, as well as sensitive words. And BluBracket sanitizes commit history both locally and remotely, supporting the exporting of reports via download or email.

BluBracket offers a free product in its Community Edition. Both it and the company’s paid products, Teams and Enterprise, work with GitHub, BitBucket, and Gitlab and offer CI/CD integration with Jenkins, GitHub Actions, and Azure Pipelines.

BluBracket

Above: The Community Edition of BluBracket’s software.

Image Credit: BluBracket

“Since our introduction early last year, the industry has seen through Solar Winds how big of an attack surface code is. Hackers are exploiting credentials and secrets in code, and valuable code is available in the public domain for virtually every company we engage with,” CEO Prakash Linga, who cofounded BluBracket with Ajay Arora, told VentureBeat via email.

BluBracket competes on some fronts with Sourcegraph, a “universal code search” platform that enables developer teams to manage and glean insights from their codebase. It has another rival in Amazon’s CodeGuru, an AI-powered developer tool that provides recommendations for improving code quality. There’s also cloud monitoring platform Datadog, codebase coverage tester Codecov, and feature-piloting solution LaunchDarkly, to name a few.

But BluBracket, which has about 30 employees, says demand for its code security solutions has increased “dramatically” since 2020. Its security products are being used in “dozens” of companies with “thousands” of users, according to Linga.

“DevSecOps and AppSec teams are scrambling, as we all know, to address this growing threat. By enabling their developers to keep these secrets out of code in the first place, our solutions make everyone’s life easier,” Linga continued. “We are excited to work with Evolution on this next stage of our company’s growth.”

Unusual Ventures, Point72 Ventures, SignalFire, and Firebolt Ventures also participated in BluBracket’s latest funding round. The startup had previously raised $6.5 million in a seed round led by Unusual Ventures.

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Source: https://venturebeat.com/2021/05/13/code-scanning-platform-blubracket-nabs-12m-for-enterprise-security/

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Data governance and security startup Cyral raises $26M

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Data security and governance startup Cyral today announced it has raised $26 million, bringing its total to date to $41.1 million. The company plans to put the funds toward expanding its platform and global workforce.

Managing and securing data remains a challenge for enterprises. Just 29% of IT executives give their employees an “A” grade for following procedures to keep files and documents secure, according to Egnyte’s most recent survey. A separate report from KPMG found only 35% of C-suite leaders highly trust their organization’s use of data and analytics, with 92% saying they were concerned about the reputational risk of machine-assisted decisions.

Redwood City, California-based Cyral, which was founded in 2018 by Manav Mital and Srini Vadlamani, uses stateless interception technology to deliver enterprise data governance across platforms, including Amazon S3, Snowflake, Kafka, MongoDB, and Oracle. Cyral monitors activity across popular databases, pipelines, and data warehouses — whether on-premises, hosted, or software-as-service-based. And it traces data flows and requests, sending output logs, traces, and metrics to third-party infrastructure and management dashboards.

Cyral can prevent unauthorized access from users, apps, and tools and provide dynamic attribute-based access control, as well as ephemeral access with “just-enough” privileges. The platform supports both alerting and blocking of disallowed accesses and continuously monitors privileges across clouds, tracking and enforcing just-in-time and just-enough privileges for all users and apps.

Identifying roles and anomalies

Beyond this, Cyral can identify users behind shared roles and service accounts to tag all activity with the actual user identity, enabling policies to be specified against them. And it can perform baselining and anomaly detection, analyzing aggregated activity across data endpoints and generating policies for normal activity, which can be set to alert or block anomalous access.

“Cyral is built on a high-performance stateless interception technology that monitors all data endpoint activity in real time and enables unified visibility, identity federation, and granular access controls. [The platform] automates workflows and enables collaboration between DevOps and Security teams to automate assurance and prevent data leakage,” the spokesperson said.

Cyral

Existing investors, including Redpoint, Costanoa Ventures, A.Capital, and strategic investor Silicon Valley CISO Investments, participated in Cyral’s latest funding round. Since launching in Q2 2020, Cyral — which has 40 employees and occupies a market estimated to be worth $5.7 billion by 2025, according to Markets and Markets — says it has nearly doubled the size of its team and close to quadrupled its valuation.

“This is an emerging market with no entrenched solutions … We’re now working with customers across a variety of industries — finance, health care, insurance, supply chain, technology, and more. They include some of the world’s largest organizations with complex environments and some of the fastest-growing tech companies,” the spokesperson said. “With Cyral, our company was built during the pandemic. We have grown the majority of our company during this time, and it has allowed us to start our company with a remote-first business model.”

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact. Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

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  • our newsletters
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Source: https://venturebeat.com/2021/05/13/data-governance-and-security-startup-cyral-raises-26m/

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Data governance and security startup Cyral raises $26M

Avatar

Published

on

Join Transform 2021 this July 12-16. Register for the AI event of the year.


Data security and governance startup Cyral today announced it has raised $26 million, bringing its total to date to $41.1 million. The company plans to put the funds toward expanding its platform and global workforce.

Managing and securing data remains a challenge for enterprises. Just 29% of IT executives give their employees an “A” grade for following procedures to keep files and documents secure, according to Egnyte’s most recent survey. A separate report from KPMG found only 35% of C-suite leaders highly trust their organization’s use of data and analytics, with 92% saying they were concerned about the reputational risk of machine-assisted decisions.

Redwood City, California-based Cyral, which was founded in 2018 by Manav Mital and Srini Vadlamani, uses stateless interception technology to deliver enterprise data governance across platforms, including Amazon S3, Snowflake, Kafka, MongoDB, and Oracle. Cyral monitors activity across popular databases, pipelines, and data warehouses — whether on-premises, hosted, or software-as-service-based. And it traces data flows and requests, sending output logs, traces, and metrics to third-party infrastructure and management dashboards.

Cyral can prevent unauthorized access from users, apps, and tools and provide dynamic attribute-based access control, as well as ephemeral access with “just-enough” privileges. The platform supports both alerting and blocking of disallowed accesses and continuously monitors privileges across clouds, tracking and enforcing just-in-time and just-enough privileges for all users and apps.

Identifying roles and anomalies

Beyond this, Cyral can identify users behind shared roles and service accounts to tag all activity with the actual user identity, enabling policies to be specified against them. And it can perform baselining and anomaly detection, analyzing aggregated activity across data endpoints and generating policies for normal activity, which can be set to alert or block anomalous access.

“Cyral is built on a high-performance stateless interception technology that monitors all data endpoint activity in real time and enables unified visibility, identity federation, and granular access controls. [The platform] automates workflows and enables collaboration between DevOps and Security teams to automate assurance and prevent data leakage,” the spokesperson said.

Cyral

Existing investors, including Redpoint, Costanoa Ventures, A.Capital, and strategic investor Silicon Valley CISO Investments, participated in Cyral’s latest funding round. Since launching in Q2 2020, Cyral — which has 40 employees and occupies a market estimated to be worth $5.7 billion by 2025, according to Markets and Markets — says it has nearly doubled the size of its team and close to quadrupled its valuation.

“This is an emerging market with no entrenched solutions … We’re now working with customers across a variety of industries — finance, health care, insurance, supply chain, technology, and more. They include some of the world’s largest organizations with complex environments and some of the fastest-growing tech companies,” the spokesperson said. “With Cyral, our company was built during the pandemic. We have grown the majority of our company during this time, and it has allowed us to start our company with a remote-first business model.”

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact. Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://venturebeat.com/2021/05/13/data-governance-and-security-startup-cyral-raises-26m/

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