In the 80’s and 90’s Sony ruled the world of portable music. Everyone remembers the game changing Walkman series of products that revolutionized the portable music landscape and enriched our lives. Then digital music came along in the form of mp3’s. And now all the music online was in this format, with the only problem being that Sony only supported their proprietary ATRAC format on all their meticulously manufactured hardware. This was not a recipe for success for Sony, and culminated in the dead-on-arrival Sony Network Walkman. In 1999 it was the smallest digital music player on the market. Beautifully crafted, like all Sony products were back then (though it kind of looks like a bicycle lock now), it defiantly only played ATRAC files.

Network Walkman

Figure 1: Beautifully crafted obsolescence

The death knell tolled for the Sony digital music division in October 2001 when Apple announced, in all its mock-turtlenecked glory, the iPod combined with iTunes. It was the ultimate mp3 player. It took Sony a further four years to fully realize what had happened to them (ironically right before the iPhone was announced), but the rest of the world got it immediately.

Today we are seeing a similar parallel. Chatbot vendors that are delivering solutions that require you to load all your data into their proprietary AI systems, with their proprietary formats.

These are AI systems that you have no control over, and, often, systems that are highly insecure. Why would any vendor require that when we have such a thing as API’s? Shouldn’t AI technology be smart enough to use API’s to look at your data in real-time and figure stuff out? The answer is simple: yes, it should.

In 2018, API’s are to AI, what mp3 was to digital music in 2001.

Let’s go with the most basic of examples to illustrate this. All chatbot vendors provide what’s called an FAQ feature (though the better solutions do a LOT more). Meaning that you ask the chatbot a question and it gives you an answer. But what the “bad” vendors do is that they require you to load all the answers into their proprietary AI solution, in their proprietary format. Why is this bad? Let us count the ways:

  1. Those answers already exist in some knowledge base in your current systems. Now you have to maintain the answers not just in your current systems, you also have to maintain the same answers in the chatbot AI too. This is called dual maintenance, and it’s bad. The chances of your web systems’ content being out of sync with your chatbot content just went through the roof.
  2. The tight control you have in your current content management systems (CMS), and all the sophisticated features they come with, almost certainly don’t exist within the chatbot vendors solution (which was never built to be a true CMS). So, you now have to deal with a knowledge base that is very loosely controlled, and one which would never pass muster as a CMS if you were actually in the market to purchase a new one. Which was never your intention in the first place (and nor should it be).
  3. From having your content tightly controlled on your systems (cloud or on-premise), you’ll now have your content stored on someone else’s server in an environment you have no control over.
  4. If you did decide to store all your Q&A’s within the chatbot vendors solution, then you now have what’s called vendor lock-in. The vendor will like that, but that doesn’t help you in any way at all.

The lesson to be learned is that you should not be so dazzled by the thought of AI that you thrust yourself into a world of disorder. As always in life, be aware of the Cynefin framework:

Cynefin illustrative sketch

Figure 2: Avoid selecting a solution formulated in the wrong domain (especially the fifth one – Disorder)

In simplest terms, the Cynefin framework exists to help us realize that all situations are not created equal and to help us understand that different situations require different responses to successfully navigate them.

So now we know how things shouldn’t work, let’s look at how it should work.

    1. Any true AI chatbot FAQ feature needs to be able to consume answers already stored in your, potentially, many knowledge base repositories. These include:
      • Oracle Content & Experience Cloud
      • Salesforce
      • PeopleSoft Interaction Hub
      • Oracle Service Cloud
      • PeopleSoft HR Help desk
      • ServiceNow
      • Drupal
      • SharePoint
      • WordPress
      • Etc.
    2. Also, the answer for each question could be contained in any of those systems, and your chatbot should know exactly which one.
    3. It needs to be role/group aware. Such that it knows key demographic data about who is asking the question and is therefore able to deliver the correct answer for that person.
      Ex: If a French employee wants to know what the time off policy is, don’t reply with the USA policy.
    4. It needs to be able to understand questions asked in potentially more than 100 languages.
    5. It needs to be able to utilize AI to summarize long answers down to a digestible length.

Doesn’t this sound better? It does to us too. And that’s why we built our chatbot this way. A chatbot that adapts to your content and your data on day one.

To summarize: an AI solution that requires a massive data and content dump of all your Enterprise systems is not a valid proposition that anyone should be considering. Other than the obvious data privacy issues, it’s also not a technically tenable solution. Yet in the rush to market by hundreds of vendors peddling chatbots, there is a general hope by them that all these giant red flags will be ignored.

Our advice is that organizations should be diligent, and only accept solutions that accommodate the scalability and security requirements of large Enterprise systems.

And as we have said in previous blogs, in the world of technology, all that glitters is not necessarily gold.

We hope that this blog has laid out a better way for your organization to take advantage of the next industrial revolution: Automation via AI.

To find out more, please contact us below…

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Automation: the application of machines to tasks once performed by human beings

It’s hard to comprehend, but it was just over a hundred years ago when car manufacturers relied on horse-drawn carriages to deliver each frame to the workers. Then, in 1913, Henry Ford introduced the industry’s first moving assembly line at the Highland Park Plant in Detroit.

Now, complex robots with “laser eyes” perform everything from welding, to die casting and painting, alongside their human colleagues on the factory floor.

Meanwhile, automation in the so-called “hi-tech” world of software has been much slower coming. Servers need bouncing, patches must be applied, security alerts need investigating, performance needs to be tuned, and code needs to be developed. All by hand.

And this is just maintenance of the actual machines! If we then flip the script and look at the experience of the humans using the software, we see the same glaring inefficiencies.

Chatbot Service

Figure 1: The help desk of the future

Entire “call center” industries have been created, all predicated on the idea that Enterprise software is too difficult to use – and only manual intervention can fix that.

The advent of the Cloud was the first step in starting to solve this problem, but in itself was not the solution. What it was, was the enabler of the solution. Step one was about creating one infrastructure and one code-line supporting thousands of organizations.

Step one was great, but step two is where the Cloud starts to realize its true potential. Step two is all about automation.

And this is where the real benefits to organizations are realized, all powered by the driver of what will be the next industrial revolution: Artificial Intelligence (AI). Today we can confidently say that the future is autonomous. And that the future is now “open for business”.

Rosie from the Jetsons

Figure 2: The future, as described in The Jetsons, isn’t so far away!

But what is fascinating about this new era is that it will differ in one key way that will make it massively different to every revolution beforehand: barrier to entry.

In the past only the super-rich could take advantage of each industrial revolution. Want to build cars? Well, good luck finding the money to create a factory of robots and assembly lines. However, if you want to fully automate your entire IT infrastructure, and enable robots to automatically handle “help desk” calls? All you need is a subscription. Everything you need has already been built and it’s in the Cloud.

The new industrial revolution will be priced on a pay-on-demand basis, and will be available and attainable for all organizations, big or small. There will be almost no barrier to entry. The playing field will be leveled by the most egalitarian revolution in the history of mankind.

API’s and AI will combine to enable automation in the same way a faucet, when turned on, provides water.

A water tap

Figure 3: Once upon a time this was a revolutionary means of transporting water!

So, why is the autonomous revolution now market-ready? Two things:

1. Oracle’s Autonomous Cloud Platform
A self-driving, self-securing, self-repairing stack that exists at each level: IaaS, PaaS, SaaS.

Autonomy across the entire platform is key for many reasons:

  • Lower downtime
  • Improved performance and stability
  • Lower operational costs
  • Ease of compliance
  • Greater security

Note: the security aspect cannot be stated more strongly. Many Cloud systems are hardened at the perimeter only, like an egg with a hard shell. Unfortunately, once the perimeter is broken into, there is little to prevent further intrusion.

With Oracle autonomously baking security into every level, there are multiple levels of security that are all monitored, patched, and repaired in real-time.  This means the entire system is always in compliance without the need for human intervention.

85% of all security breaches occur when a patch is available but not applied.

2. IntraSee’s Autonomous Chatbot Solution (which resides solely on the Oracle Autonomous Cloud platform)
A chatbot that autonomously builds itself utilizing pre-built Enterprise skills that provide a fully-formed chatbot from day one. Also, because it resides on the Oracle Autonomous Cloud platform, it is the most secure chatbot solution available.

Figure 4: Automation, the new “Easy” button

What also stands out with Oracle’s and IntraSee’s offerings is the low barrier to entry. At IntraSee we pride ourselves on making AI a turnkey solution. Which is why both Oracle and IntraSee provide pilot options, where you can quickly see the value of automation for your organization.

With our chatbot solution we can implement and configure in just four weeks. Let your department kick the tires for another four weeks. Then roll it out to a larger pilot audience for another four weeks.

If you like it? Then roll it out to your entire organization in another four weeks.

Using IntraSee’s Chatbot 4×4 implementation methodology, the benefits will be instant. Chatbots dealing with complex calls for less than one dollar a conversation. Compared to $5 to $200 for an actual human. Plus, with the added bonus of higher customer/employee/student satisfaction and a lot more reasons too.

The future will belong to those organizations that embrace autonomy. And those that don’t will struggle with never-ending spiraling operational costs that will hinder their ability to compete.

Imagine if Ford were still trying to transport car frames via horse-drawn carriages. That’s right, they wouldn’t exist today. The lesson in life, as always, is adapt or perish.

typewriter vs laptop

Figure 5: Old vs. New

If you’d like to know more, please contact us.

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Since the dawn of time (almost), people have been communicating via conversations. And this worked great for many thousands of years. Then computers happened, and suddenly we all had to learn a different mechanism for communicating. This was loosely referred to as computer-speak. And over the years it changed as technologies changed. From mainframe, to MS-DOS, Windows/Mac, client-server, and then the web. But the one constant over the years was that it was still computer-speak. Meaning that it had nothing to do with how humans actually spoke to each other.

And this is the crux as to why your Enterprise systems are so difficult for your organization to use today. And why it costs you so much money to support everyone, and everything.

Implementing a chatbot solution for your Enterprise, if done right, will save your organization millions of dollars per year, increase organizational efficiency, and improve user satisfaction with your systems.

The ROI is dramatic. A conversation with a chatbot should cost less than 50 cents per conversation. Whereas a conversation with a human is costing your organization at least 10+ times as much, and, if HR professionals are involved, often 100+ times as much.

But to get there everyone needs to be comfortable with what this new era will look like, and how to get it started. To that end, the recommendation of Gartner (and we wholeheartedly agree) is to pilot the solution to ensure that you don’t embark on a failed IT journey.

So, here’s our recommended 10 steps to ensure that you hit this one out of the park on the first pitch.

Step 1: Understand how much it will cost

First off, pilots should be cheap, and they should be short (and if they are not, then that’s a red flag). But it’s also super-important to understand what the cost structure looks like once you’ve rolled this out across your entire organization. So, work with the vendor that’s pitching the pilot to fully explain what things will cost after the pilot is done and you’ve decided to roll this out to everyone in your organization.

The last thing you want to tell your CEO is that the pilot was a success, but it’s not cost-effective to roll out the solution organization-wide. Remember, the #1 reason for implementing a chatbot solution is to reduce operational costs.

Step 2: Understand how much of your team’s time will be needed, and what is required to support it

All implementations will require some time from your internal teams. That’s normal and desirable. But you really should avoid solutions that could tie up teams of your people for months on end.

Also, once implemented, you should expect support and maintenance to be minimal too. If you suddenly discover you are now performing “dual maintenance” of content, then this means you chose the wrong solution.

A chatbot solution should require minimal involvement from your team to setup, monitor, and support.

Step 3: Ensure that infrastructure/security is discussed and vetted early on

It feels like every day we hear about a security breach at some of the biggest internet companies in the world. Concerns about security and infrastructure are very real and must be addressed. It’s critical to understand the architecture that the chatbot provider is proposing, as you may discover that your data is not only flowing through channels you’d prefer it not to, but is also actually being stored in places it shouldn’t be.

At IntraSee we take infrastructure and security very seriously. Which is why we reside solely within the fully certified Oracle Cloud.

Step 4: Identify your pilot audience

We would recommend around 200 people for an average chatbot pilot. And while it may be tempting to select them all from the IT department, we would recommend a broad range of your organization, but would focus on employees/managers or students/faculty (in the higher education world).

Try to select a broad demographic that most accurately represents your organization.  Including those who speak any languages you would want the chatbot to support.

Step 5: Understand any language requirements

Chatbots are capable of conversing in many languages, some better than others. So be aware of which languages the people in your organization will be conversing in, and check with your vendor to get feedback on how competent they believe the chatbot is in those languages.

Adjustments can be made for any languages that the chatbot may not be completely proficient in. Just let your vendor know up front.

Step 6: Have a pilot-to-production plan in place

Ok, so the pilot went great. Everyone loved it and now you want everyone in your organization to get to use it. Be sure that you have a pilot-to-production plan in place before you started your pilot. Because now you’ll know what to do next, and how much it should cost.

The key to pilot-to-production is that it should be a relatively quick process. We would say that four weeks should be attainable, but that anything more than twelve weeks would be excessive.

Step 7: Think in “conversational” terms when solving for use-cases: what do people need help with?

Talk to your help desk team, and your HR Generalists, they can provide you with the top 100 things that they get asked on a frequent basis. That’s a great start. But also get insight into how the conversations go.

  • How are the questions phrased?
  • Are there follow up questions based on specific answers?
  • Are discovery questions needed?
  • Would the inclusion of specific data help with the conversation?
  • What’s the best way to answer a question?
  • Does the answer vary based on location, seniority, etc.
  • Is a follow up required after the answer has been given?

This will help with configuring how the chatbot interacts with your people.

The idea is that the chatbot understands your best practices and follows them every single time. Just like a perfect employee would.

Step 8: Understanding context

It’s critical that your chatbot understands context, because then it can make helpful suggestions during a conversation. Just like a well-trained support person would. Plus, it’s also important that the chatbot understands who you are and where you are. This way a meaningful conversation can take place, as opposed to a simple Q&A.

So, for example, if someone asks a question about taking time off work, the chatbot should already know that if the person resides in Germany, that it should respond with whatever is the German policy (because that may be different to the American policy). And, also, that it offers to help the person complete a leave of absence request, if they so wish.

Step 9: Think big, but be agile

There is a school of thought that says that chatbot pilots should only include a small number of “intents” (aka functionality). We at IntraSee do not subscribe to that point of view. A pilot using this methodology may appear to be a success – but that could all be an illusion.

The main (but not only) purpose of a pilot should be to see what would happen in a full rollout to your entire user population, but with a smaller group of people where you can monitor and see what works and what doesn’t. And the only way to do that properly is to try and make your pilot scope close to what you expect your full production scope to be.

This means you also need to be agile during the pilot and can adjust to things you see, such that by the end of the pilot you have a close match to what your pilot-to-production path would be. HINT: This is why you need a configurable and fully automated solution.

Step 10: Don’t try and “roll your own” chatbot pilot

There’s no doubt that chatbots are the most exciting thing to happen in the software industry in the past 20 years. And there’s a ton of examples on the internet about how easy it is to create a chatbot that can accept pizza orders. But Enterprise chatbots are highly complex and sophisticated creatures. And to build one properly from scratch would take many years. So, the strong recommendation would be to use something already built off-the-shelf that can quickly be configured for all your needs. This isn’t just our recommendation, this is the recommendation of Gartner too, from last year’s Gartner Application Summit.

Gartner’s clear advice for IT is to stop building things that are already built. Ultimately, it’s not just a waste of time and money, it also contributes to IT being primarily focused on being in “maintenance mode”, instead of “innovation mode”.

If you’d like to know more, fill out the following form and we will send you our white paper.

With the proliferation of Amazon’s basic one-size-fits-all AI, millions of users have experienced Alexa playing music, summarizing the news, and providing information found on the internet. After the initial thrill is gone, many come to find out Alexa can’t really do much more without adding Alexa Skills to make her smarter. These “skills” are the bridge between your commands and actually getting something accomplished, like adjusting your thermostat or turning on a smart light bulb.

In the Enterprise world, IntraSee’s chatbot-automation bridges the gap between artificial intelligence and real-world business transactions, empowering AI platforms like Oracle Intelligent Bots to turn on the proverbial smart light bulb for your enterprise or institution.

When people ask us what we do at IntraSee, we explain that we are like Amazon Skills for the enterprise. These skills are what large organizations need to realize millions of dollars in savings. Instead of wasting time and money designing and maintaining websites that beat around the bush, IntraSee’s chatbot solution gets straight to the point and does the work users need to get done. There’s basically no web page, just a chat window. We’ve developed a means of automating chatbot implementations that makes configuring these solutions quick and simple, so the AI knows how to do the stuff that needs doing – right out of the box!

AI hand touching human hand

AI and Enterprise software finally collide

IntraSee’s suite of products empowers users to accomplish tasks like moving an employee to a different team, tracking a new hire’s to do list, aiding a nurse restocking medical supplies, or helping a student register for classes by phone. All the user has to do is ask straightforward questions, and the chatbot will do the rest. Without navigating through a website, a busy nurse can simply ask the chatbot to “Buy more bandages,” and the chatbot will guide them through the required steps: “What type of bandage? What size? How many? Would you like to add something else to your order?” College students can give the command, “Search for English classes,” and after choosing a class from a list the chatbot will ask, “Would you like to add English 101 to your cart?” Simplicity makes cents.

At IntraSee we have taken leadership in the Enterprise UX space, and transformed that into an automated means of generating a chatbot that is multi-talented from day one. It is so advanced that it can immediately solve problems that your development teams have spent decades, and masses of money, working on. And while automatically turning on a light bulb is a nice trick (and saves someone having to push a button). Our chatbot can perform things immediately that often take teams of people days to achieve. This is exponentially better than anything Alexa can do.

So, while programmers are churning out thousands of simple AI skills, none of these applications can handle complex business logic or the decision process required for multi-step transactions like tracking time in Kronos. Alexa can’t make intelligent decisions because she doesn’t know anything about the user. This is where IntraSee puts the “I” in business intelligence. We leverage all of the information we know about users without asking, utilizing known data such as reporting structure to logically streamline workflows. When the chatbot has all the information it needs it provides a summary of the transaction and executes the process securely and efficiently on the backend.

Many Alexa users worry about security and privacy because Alexa is “always listening,” and you would never want co-workers to hear you say something sensitive like, “Give Jimmy a big bonus.” Chatbots eliminate such security concerns by allowing users to type questions and commands. The entire suite of IntraSee products is designed to seamlessly work with highly secure data systems such as PeopleSoft, Oracle HCM Cloud, Oracle Student Cloud, Salesforce, Taleo, Kronos and many more. Each month we continue to add to the library of skills, so if it’s not there now, it will be soon.

In business it never makes sense to spend a dollar chasing a nickel. At IntraSee, our focus has always been to streamline business processes to save your organization money, increase productivity and reduce frustration. IntraSee has been helping organizations increase profitability by simplifying the user experience since our inception. To say that IntraSee is ahead in the AI skills game is an understatement. For nearly a decade IntraSee has been developing a suite of products that provide cost-saving self-service solutions straight out of the box. It turns out that our mature transactional architecture is the perfect fit for the next generation of AI, marrying complex transactional processes with the AI platforms of the future.

Artificial intelligence investment is intelligent business today, not something your organization should wait to do tomorrow. Building a library of AI assets is something that needs to start today. We encourage you to look at IntraSee chatbot solutions as you would Alexa Skills,  the necessary smarts needed to get meaningful work done. Being a business that is ahead of the curve in AI integration will make the difference between winning and losing.

Launching artificial intelligence for your organization’s users is simple and straightforward. The AI’s have matured, IntraSee’s got the skills covered, and our risk free pilot takes the guesswork out of adoption timing. Contact us to start your Chatbot Pilot today.

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