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Chatbot best practices

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I’m stating the obvious here, but it’s really important to know what you want to achieve, and how this can be measured. Many of your KPIs will be sector or domain specific, but I will give you some chatbot specific KPIs to think about. Listed in order of importance:

  • Satisfaction rate — the percentage of those users who were satisfied. I generally recommend offering a binary choice “satisfied” vs “not satisfied” instead of a rating from 1 to 5, but the choice is yours.

Like most technology, a bot is designed to automate tasks that would otherwise be done by a human operator. Before embarking on a chatbot it’s essentials that you know exactly what you are trying to automate. The best way of doing this is to first employ human agents to respond to your users’ messages. Why do this?

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

Ok, you need to be mindful of GDPR, so you can’t log everything. For your purposes we don’t actually need personally identifiable information. What you’re after is the phrases users use. In particular, you’re interested in:

  1. entities — yes, a jacket. Entities (relevant nouns) form the basis of named entity recognition
  2. parts of speech —I want a black or white dress”. The adjectives, prepositions and conjunctions. You will use these to train your part of speech tagging models.
  3. sentiment — I’m not happy” or “thanks for your help”. You can use text classification and sentimental analysis to detect when users are satisfied or dissatisfied.

If you’ve followed our first piece of advice, you should have some decent training data. Now it’s time to put it to use.

  1. body — e.g. “last Monday”. These messages may contain additional entities
  2. sign-off — last couple of messages e.g. “thanks for your help”. Useful for sentimental analysis

Experienced IT professionals think carefully about validation and error handling when building apps or websites. You can usually rely on the UI to help enforce constraints. For example, by using a dropdown select box with the valid options. The challenge arises when trying to enforce the same constraints in a chatbot.

Quick replies

Some channels offer quick replies— prefilled responses which can act as a replacement for select dropdowns, radio buttons and checkboxes. Quick replies can be used as a means of constraining user behaviour, but should be used with care. Unlike dropdown boxes, the options are typically displayed horizontally or vertically and take up valuable screen real estate, especially on mobile devices. This makes them suitable for responses with only a few options.

Message validation

Free text entry is at the heart of a chatbot. It’s unconstrained, so good validation and error handling is especially important. Remember — whilst your NLU model may correctly identify an entity, this doesn’t mean your downstream systems can handle it. 100 pounds or last monday are examples of entities that an NER model will probably recognise, but need transforming for downstream consumption.

Here’s the typical chatbot flow:

  • Process reply
Agent: hello how can i help?
User: hi
User: i want to check my order status
User: order A123
Bot: hello how can i help?
User: hi
Bot: Sorry i dont understand
User: i want to check my order status
User: order A123

Support chit chat

Basically you train the chatbot to recognise “chit chat” type messages, which it can either reply to or simply ignore. Taking the example above, the bot would either ignore the “hi” or reply with “hello”. Either way, it wouldn’t generate an error.

Buffer incoming messages

Buffer all incoming messages. Wait until N seconds have elapsed since the last message. At this point concatenate all the buffered messages together into a single message and process it. Taking the above example it would look like:

Bot: hello how can i help?
User: hi
User: i want to check my order status
User: order A123
(wait N seconds)
Bot: Ok …

Buffer but short circuit

The same approach as described above, but instead of always waiting N seconds, you try to process the message buffer every time a message is received. If you can process it, you do so immediately, avoiding delay. Going back to the contrived dialog it would look something like:

Bot: hello how can i help?
User: hi
(can’t process — wait)
User: i want to check my order status
(bingo)
Bot: Ok what is your order number?

As well as validating each user response, you will want to set up various “checkpoints”. This means telling the user what the bot has understood and asking them to confirm this. For example saying something like:

Drill down

We call the first strategy the “drill down” approach. Start out by asking users open questions e.g. “how can I help?” or “what are you looking for?”. Run the responses through the NLU models and algorithms and checkpoint the conversation.

Bailout

We call the second approach the “bailout”. Put simply if you can’t understand the user’s needs you fall back to human intervention. See below for more details.

What can you do with the outliers? Firstly it’s important the system recognises when it’s failing to meet the user’s expectations. For your users, there’s nothing worse than talking to brick wall. One way of detecting this is to count the number of “sorry I don’t understand” type responses generated for each dialog. As mentioned above, checkpointing is also very important.

The reason you’re logging the conversations is to build up training data, allowing you to build accurate models. To borrow a cliché — this is a process not an event. Whilst the data captured during the initial “human” stage gets you started, you need to retrain the models as you collect more data.

Chatbots are freeform, users can say whatever they like. This presents challenges but also opportunities. Chatbots are great for market research.

Implementing an enterprise grade chatbot requires careful planning. It’s important to understand the KPIs and business drivers before embarking on the project. Having a means of measuring success is also really important.

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://chatbotslife.com/chatbot-best-practices-b7c7d4bb0086?source=rss—-a49517e4c30b—4

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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.”

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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
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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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Data governance and security startup Cyral raises $26M

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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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