Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a variety of sources.

1. Synthetic APIs Shape the Future of Data Acquisition and
Management
Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a
variety of sources.
Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies
Dana Gardner: Hello, and welcome to a special BriefingsDirect panel discussion coming to you
from the 2013 Kapow.wow user conference in Redwood Shores, California.
We'll hear how innovative companies are dodging data complexity through the
use of Synthetic APIs. We'll see how -- from across many different industries
and regions of the globe -- inventive companies are able to get the best
information delivered to those who can act on it -- with speed, and at massive
scale.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, and I'll be your moderator as our
panel explains how they improved data-use benefits from novel information integration to gain
business success. [Kapow Technologies is a sponsor of BriefingsDirect podcasts.]
Please join me in welcoming our panel: Jürgen Hase and Rüdiger Adam, both vice presidents of
the Machine to Machine (M2M) Competence Center at Deutsche Telekom AG in Bonn; Søren
Nissen, the CEO and founder of Click A Taxi in Copenhagen; Doug Potvin, the Chief Financial
Officer (CFO) at Trinity Logistics in Seaford, Delaware, and Pedro Saraiva, product manager for
the Content Shared Platform and Rapid Sourcing at Thomson Reuters in London.
One of the things that's been fascinating for me at this conference is to see how efficient “robots”
are accessing important data, which elevates the importance of the data
very rapidly, which then leads to innovation -- not just efficiency, not
just repaving of cow paths -- but in doing entirely new and different
business achievements.
The end result is often business transformation - and entirely changing
the nature of the business. So that's what we're going to be talking about today.
Jürgen, tell me a bit about your operations there at the Machine to Machine Competency Center,
and why what you’ve been doing with Synthetic APIs has been transformative.
Jürgen Hase: We have to collect data from whatever type of sources – structured and
unstructured data formats. And for us, for the future, a key driver is how to handle it all, based on
end cost. That's really important for us. And this is in a global way. That means it’s not merely a
solution for the Germans or for Europe. We have to act in an international way.

2. For this, the Synthetic API is one of the key drivers because we can't add millions of types of
APIs on a different technology layer or a different IT layer. We have to use the same way
internally. As you know, Deutsche Telekom has many different customer relationship
management (CRM) and enterprise resource planning (ERP) systems.
And to handle all of this we need a Synthetic API. I believe that makes it simpler and easier for
us. If not, we'd have to hire an additional 100,000 people to make it possible.
Transformative?
Gardner: And just to probe a bit more on that, has this been transformative in an economic
sense, as you’ve saved money by doing it this way or has it been transformative in an enablement
sense, that is to say, gaining advantage in processes and/or being able to accomplish things that
you really just couldn't do?
Hase: First of all, machine to machine (M2M) has two aspects. One aspect in general is to
optimize process, the customer's process, and one of its key drivers is to collect
the data and manage the data in the right way.
The second way is to generate new services and make it possible to onboard a
customer for an M2M solution. It’s really important that nobody is waiting two
months for a running system. We have to do it in one week or in a few days.
That's really important. Saving time and saving money are really important.
Gardner: Also at Deutsche Telekom, Rüdiger, you've been more involved with the hands-on
aspects of doing the synthetic API integration and access, pulling together the means of doing
this. I'm interested in that transformation basis.
How has this impacted your staff, the workers, the developers, the process analysts - those you
have tasked with doing this? What have been the efficiencies or benefits that would be of a
transformative nature from that perspective?
Rüdiger Adam: It takes a long time to create new interfaces and get data access to all of these
systems. It takes around 10-12 months to get it up and running with normal IT
development path. Our experience is that we can use a couple of these catalysts
and our business logic on top to create prototypes, which run in the short term,
10-40 days.
If it's a little bit more complex, then perhaps is takes two months. Then, we can
test and prove these, adopt other requirements or business needs, and be very
flexible. We're close to the customer, and that's the point that helps us to set up the
right requirements.

3. Gardner: Doug, I’d like to go to you next. You’re a little bit smaller than Deutsche Telekom.
One of the interesting things about Doug’s organization is he's the Chief Financial Officer, but
he's also in-charge of IT. So you can think of him as also the IT Director.
This has some benefits. He doesn’t have to argue for funding except in his own mind. Perhaps on
the way home, he has a little argument -- the devil on one shoulder and the angel on the other.
But, what he has been able to do is act rapidly. Tell us a little bit about what you've been doing
with Synthetic APIs and why that's been transformative for your organization?
Doug Potvin: It's transformative in the sense that I am not Deutsche Telekom. I am not Siemens.
I am not a large name out there in the marketplace. So, my being able to go to a FedEx and UPS
and say: "Build an API for me so I can go ahead and interact with your system," is not going to
happen, and I know that.
Business is easier
Finding a way to interact with these websites outside of that has enabled me to do business a
whole lot easier and better, and that's what makes it so nice. Now, I can play as a big player, go in
and do what I need to do, grab the information, the data and stuff, and then be able to process the
data and get their information done automatically. That's able to transform the business right
there.
Gardner: You started with being able to essentially do something better that was hard before. It
was manual and paper-based, and you improved on that. But then, as you told me, you've been
able to gain insight into things happening in the external market that put some ideas in your mind
about being able to give you an advantage vis-à-vis your competition and also to perhaps to stake
out entirely new lines of revenue. Tell us how that's transformative?
Potvin: I wasn’t going to enter the Kapplets competition, but just last night, I submitted this
idea. It just hit me hearing the discussion of how people were using the
technology to go out and look at getting all these carriers who submit to us either
by emails or carrier load boards where they are emptied at.
Taking all that information, I can have a business development person go out
there and say: "Give me all that and do it within a six-month period. Give me all
the carriers who maybe emptied in Toledo, Ohio." All of a sudden, I get a list of
12 carriers and those 12 carriers have trucks there, Monday, Tuesday,
Wednesday, Thursday, and Friday. All of a sudden, I know I've got available
capacity in that market, and I know where those trucks want to get to.
Then, I take a robot and say: "Go out to Hoover's and grab all the manufacturing companies
within a 50-mile radius of Toledo." Then, through a credit reporting agency I get the traffic spend
for those companies, go to D&B and make sure they cleared my credit standards, and I
deliver to my business-development people a known list of shippers who meet my credit

4. requirements. All of a sudden, they're not cold-calling. They're making an additional process
there.
I like Linkedin, because I know these people know people. Therefore, truck managers are going
to pick these things up. I may have a referral I can get from one of my existing business partners
there and put that all together. My business development person goes from the unknown-
unknown to the known-known in a very simple concept.
I was talking to my VP down in Texas just this morning. He said: "You know, we’ve got this
available-cash list you’re talking about, Doug." Every day we get bombarded with customers
who are on a first-come first-serve basis. We and a hundred other brokers get this list of people
who want to move lumber, because lumber is pretty cheap, and they want to move it as cheaply
as possible.
You’re not going to spend a lot of time on something that's a $50-75 market. But, if you can take
those two things, where the guy wants to ship a known capacity, have it put it automatically
together, give that to the sales guy or the business development guy, now all of a sudden we’re
just calling two or three carriers. And if they don't want to haul for the price, we can just stop it
and we just go on.
It's really the transformation process, and all of this has taken place in two days from the mind
thinking about it, based on what you hear how the people are using it. So it's really cool.
Gardner: This is a great example of this leap of simple, effective robots that nearly anyone with
a little bit of training can use effectively, accessing important data that's dynamic, that leads to
new business and therefore is transformative.
Let's go to the Søren next, Click A Taxi is an interesting story. You're managing scale, because
you're growing so rapidly. You have to be able to do this with finite resources as a startup. You've
been able to grow by using more-and-more robots and automating processes. Tell us how the
Synthetic APIs approach transforms you as a rapidly growing organization with limited
resources?
Limited resources
Søren Nissen: First off, you mentioned that the keyword for a startup is limited resources.
Obviously, we have this ambition that when we go live, boom, it's a success,
immediately. It's never like that, but we were hoping that there would be some
kind of growth and that we would be signing on more and more cab companies as
we went along.
As I mentioned yesterday, we needed a really structured process from day one to
on-board partners with the direct cab companies, airlines, and whatever. The
fantastic thing was that I hired a junior developer, put Kapow in front of him, and

5. he sounds like a PhD in APIs suddenly.
You put Kapow in front of a junior developer, and in any partner-integration discussions you
have, you just say: "We don't care how we do it. There are no requirements." The airline will ask
can you do this? We can. Just that, in itself, is fantastic when using Kapow. There are no
requirements from any external partners that we need to comply with, which is great.
Gardner: Something is also interesting about your organization. You're dealing with taxicab
companies, and when I think of taxicab companies, I think of surly men with beards, coffee,
maybe something stronger, yelling at people to do their job. There's not a lot of finesse, not a lot
of grace, but an absolute need to get the job done right on time.
What's it like dealing with that sort of organization and how has your ability to actually bring IT
to them, rather than expecting them to have any IT to bring to you, worked?
Nissen: The funny thing is that they actually all live at The Four Seasons and wear suits. No,
you're spot on in terms of the kind of people we're dealing with. In the typical cab company we
interact with, the general manager will sometimes be answering the phones in their own call
center.
It's taking some time to perfect our pitch, the first thing is that I can't do any integration. I can
send it in an email, and maybe they'll have an SMS gateway in their PBX system from the '80s.
The second you mention that we'll automate it and integrate it, they say that's not possible.
Before they hang up, we say, "We can do this without you lifting a finger." They don't really
believe it, but they we say, "Just send us a password and a login for your Web booking
application, and we'll call you in a couple of days and show you it works."
Gardner: So again, it's simplicity, being able to take the IT to those who might not be IT people,
still getting sophisticated things done, ultimately transformative, not APIs, not software for
integration at a platform level. It's a very interesting approach.
Next, Pedro of Thomson Reuters, an information company. You are the information broker
within the information company. It sounds like a pretty good authority on what works and what
doesn't work, when it comes to moving unstructured information around. Tell us what you're
doing at Thomson Reuters with this approach of synthetic APIs. Is it transforming your task?
Everything is changing
Pedro Saraiva: I'm hearing many common themes here. One of them, beyond any doubt, is
agility. The world keeps changing. Data is changing. The sources are changing. Our customers
are changing. We are changing.

6. So our requirements for content are constantly changing. The ways in which we look at content
are changing, and previously it took us months, years, perhaps forever, because we couldn’t even
do it.
Now, we can look at the source and confidently say two days, perhaps three
days, but we'll do it, and we'll get it done. There is a certain amount of
excitement about being able to do that. Suddenly, you're thinking, "If I can do
this, what will I be able to do next?" It changes the way you look at web-
content acquisition, going from being something you don't want to do to
something that you want to do more of.
The other way in which we can really get a lot of value from leveraging the right technology is to
think about synthetic APIs. I just thought about this now. A lot of what we do is exactly that. It's
going to a website, a Web source, that has a user interface. They don’t have a structured
documented feed, but we need their data. They actually want to provide that data. If we want to
automate it reliably and predictably, if we want to have a straight through automation of that
acquisition, there is one thing we know we can do, which is build a robot. And we know it
works.
We are not aware of many technologies that would give that degree of confidence. Can you do it,
can you do it now and can you do it quickly? So it really optimizes our task and allows us to
focus on what we want to do.
Gardner: Another takeaway for me from this event, and it jibes with some of the thinking I have
been developing lately as well, is that the traditional IT diagram always has data at the bottom
usually represented by cylinders, round objects, icons, and that everything else is on top.
The bottleneck is in how well your applications, middleware, or platform can access that data.
But, it seems, based on what we're hearing, is that information, especially when it's mission-
critical information that needs to be used in processes right in the field, changes that.
We should start to think about taking the data from the bottom of the diagram and maybe moving
it to the side, because we are going to be accessing data in more ways across the organization’s
boundaries as well. So, if you have an ecosystem, a supply chain, a thousand taxicab companies,
this changes fundamentally what the data integration requirements are. Therefore we have to
think differently about the architecture.
I’d like to pose similar questions to our panel and see if they agree. Is it time to rethink the
architecture of data at the bottom or is data something that surrounds IT and therefore IT needs to
adapt to that? Let's start again with Deutsche Telekom, the biggest company here.
Is it time to rethink architecture and even the concept of data now that you can use Synthetic
APIs to bring it into processes almost at any point and with significant ease?

7. Accept and adapt
Hase: I personally believe that we cannot change the whole world. It takes around 10, 15, or
20 years to change the world from the technology side. We have to accept the world’s existing
IT infrastructure, the data format, all of these things, and we have to adapt it.
Our part is how we can optimize the data flow between the different layers. On the other side,
we'll have more open interfaces and different platforms from different partners, and to adapt all
of this in the right form will take more time. For me, it's using technology we can use today, like
Kapow Technology, to adapt it. How we can optimize the data world is the second step.
It's a journey like with cars. We can adapt new data technology in a car, but in Germany we are
selling in the German market around three million new cars per year. So it takes 10 years to
change the whole world of the automotive industry from the data formats and all these things, as
things coming up from the IT, from the data structure.
That means we have to follow the world and adopt the old technologies, the existing technology,
and also implement step-by-step new data formats and data structures.
Gardner: So as with the previous speaker, the large bank, they have a little bit of everything. It
doesn't go away. You have to not just replace, ripping out and bringing in new, you have to have
it all and support it all. That's the nature of a large legacy business.
Rüdiger, anything more to offer on this concept of a different architectural concept, now that we
have such easy ability to access data and use it within our processes?
Adam: Due to these different interfaces it's also crucial to reduce the risk of losing data. We
heard yesterday also that the absence of data is a problem, and it's also the same for us.
So if we are introducing or buying new systems, we look into our key projects, and that means
that we get the data access for those purposes. We'd like to be flexible on that too. That's the
reason we set up Kapow Katalyst with our solution on top. We're very flexible to adopt other data
sources in a very easy way on that one, and to check out what is possible on that.
We'd like to transfer this knowledge as well back to the industry. If you'd like to follow this
approach and if we can work together on those standardization of interfaces, that would be great.
Then we're more up to common requirements.
Gardner: Let's go to a mid-tier company, in this case, Trinity. You don't have to follow the
architectural diagram. If you want to throw it out and start do something different, you are a bit
more flexible and dynamic. I think small-to-medium sized businesses (SMBs) actually have
some advantage in agility, particularly when they can start using software as a service (SaaS) and
cloud services.

8. Doug, how do you come down on this notion that, I don't need to think about data in some barrel,
in some diagram at the bottom, but I can rethink it? Is this an architectural shift for you, how do
you view this from the structure of IT?
Data always existed
Potvin: So the architectural diagram doesn't exist for me in the first place. What it really
revolves around to me is that all this data always existed in one format or another. Whether it's in
emails, in data, on a website, whether it's some type of report, it all exists somewhere. The ramp-
up of the information is just because you can access it on the web, but this information has
always been there in one form or another.
We enabled the home-type technology. It allows you to get access to the data, which changes
everything. That diagram that we're talking about was a very specific amount of data. Now, all
this data is completely, as you say, Dana, around the processes.
It allows us to attack it in a completely different way. All of a sudden, with the transformation
within the business environment with the use of Kapow within that business, people begin
thinking, what if. People begin asking if we can do this.
I've got this report coming in and I get it weekly. Can we do something with this, so I can extract
the data? It's a 15-page report, and I just want two numbers out of it. I just want this section out
of it. I can extract that, pull it, and give it to them, so they can make a real-time business decision
without going through the entire fluff to find what they are looking for.
Gardner: At the other end of that typical architectural diagram with all that data, structured data
at the bottom, we've had the client, the PC, and for lack of a better way, the killer app of data on
that PC has been the spreadsheet, at least for many internal business processes, for many
organizations and how they run things.
Let's go now to Click A Taxi. You've just started this business fresh. Do you use spreadsheets?
Are they a problem or a good thing for you?
Nissen: We do use spreadsheets, but we use it very little. Spreadsheets still work very well for
budgets and stuff like that.
But then we used social collaboration tools and actually a tool called Podio, which is fantastic.
It’s an evolution of Microsoft SharePoint. But as I have mentioned a couple of times, if a daily
process of any person in the company takes more than 30 minutes, we want to build a robot to
automate it and get rid of it.
The funny thing is that I have a finance background. Kapow and the decision around Kapow
started as a pure, almost cost-benefit financial analysis. How many developers can I potentially
cut away and how much of my call-center expenses in Romania can I cut away by buying this

9. piece of software. Okay, it checks out. I’ll buy it. But when you, as an organization, have been
working with Kapow for six to nine months, it evolves from being originally a pure financial
decision to actually becoming that I can innovate much faster than I could before.
Gardner: And do you use your Kapow robots to access any of those spreadsheets?
Nissen: We do, yes.
Gardner: And do you then also have what we would consider traditional data, say structured
relational data that you are also perhaps tapping in some manner or another with a robot?
Nissen: We use it in all ways and forms to connect sources.
Different types of data
Gardner: So, there it is, from the side. That’s what’s interesting to me. Now, Pedro, in your
organization, dealing with many different types of content, both from news organizations and
financial feeds, real-time, very fast transactional-type information, do these robots also fill that
need for you? Is there an ability to tap different types of data and information across the
spectrum of the IT landscape?
Saraiva: It’s interesting that you asked me that question, because it’s a question I am asking
myself right now. Up until now, we've been focused on Web content acquisition. We're now at a
stage where we're thinking we've done a good job with this part of the problem. Let’s look at
their content acquisition requirement feeds and so on. Perhaps we can take into consideration the
availability of technologies such as Kapow and our understanding of how to make them work.
Right now, I'm looking at how I would redraw the whole picture and try to understand how far
we want to go, why, and what’s going to work best. have a strong suspicion that we'll find that
Kapow is going to find its way very quickly to automating and improving the architecture around
many areas that we previously didn’t think we were going to use it for.
There are other things happening, and they were not planned. That’s also quite interesting. We
now have people thinking about Kapplet-type applications.
"Here I am in Bangkok, in this office. I do this job. I heard about you." They heard about me,
because I've been to this conference and they know about Kapow. They heard about Kapplets
and they add one-and-one and say, well this is two. If I talk to Pedro, and he can get me a robot
for which I get the Kapplet and I do this, then my job will be much easier.
So there is an emerging set of use cases that we haven’t anticipated, and they're being identified
almost daily. At some point, there will be a pattern and we'll find a way of looking at it and
saying that now we want to really take the opportunity to do something about it, not just on an
ad-hoc basis, but we're going to apply Kapow to achieve this new kind of capability.

10. Gardner: Another major trend that we all need to consider these days is the impact of mobility
and delivering applications, data, and information to mobile devices but also enabling those
mobile devices to be the generators of even more information and data, so that it’s a two-way
street.
The notion of enabling mobile devices to take the place of manual processes, paper processes,
even reducing the size of the device from a PC to a tablet, perhaps even to a smartphone, brings
in some issues. But if you have a Synthetic API approach, where you can access it through a
browser, perhaps a WebKit browser on your mobile device, a native browser to the mobile
device, that again prompts some thinking that would lead to transformation.
Let’s go back to Deutsche Telekom. You probably have more insight into this, because you're
dealing on the M2M level. Is there anything now about rethinking data coming from the device
into the IT infrastructure that the Synthetic API approach, the robot approach, is transformative?
It's a fairly open-ended question, but let’s think about this now from getting the device or the
person in the field or the taxicab on the city street as the input to the larger information
landscape.
Adam: Mobility is an important one for us, as we lead to build up the right combination. When
we started, it was classical voice and then the smartphones to collect the data. Nobody is using it
for voice. Everybody is using it for mobile Internet. The next step, the next wave, is coming up
from the Internet of things, M2M.
Combining the data
But we have to combine it. On one side, we're collecting data from the device, from the
machines, and to the back end system, to the classical IT. There, we have to use it to think about
new IT infrastructure, how to combine it, how to use intelligent robots for the smartphone part.
We have to also take feeds from the residential market and from the enterprise market, combine
it in an intelligent way, and then send it back to the customer to choose the devices and to
manage the world. There are a lot of opportunities to think about how we should use this new
technology in a really intelligent and smart way.
Gardner: If I hear you correctly, the opportunity to make all these devices, from the sensor in
the chip to the person with the data-connected smartphone, the input entity, then we're going to
start to see a whole lot more data. But is this data that should be going back to those cylinders at
the bottom of the architectural diagram? Should they be going to the cloud?
They probably will be going to all of those places, and so again this strikes me as a
transformative step, in itself. Making the mobile tier the input device changes the architectural
requirements for the data, but probably in ways that favor the synthetic API access to that data
over time. That’s my theory. What do you think?

11. Adam: From my point of view, it’s really important. We have just read that per person, per user
they will have about six devices to deal with. From tablets to smartphones to the normal PC,
people would like to be very flexible.
For us, as a company, it’s crucial also to deliver this data in a secure mode. Very high security is
the center of all. So we need a very clever logic so that this data is not used by others. That’s one
of the keys, but the presentation and the information that we would like to make available to
those parties or people should be always the same, and that’s the big challenge for us as well.
Devices are changing. The standards are changing. Today, they're using JavaScript. Tomorrow,
they'll also have a Google solution in place. Apple is working on its own application system. So
this has to be harmonized. This has to be also the same standard for us. The presentation should
be the same for that one. And the data and the cloud should be accessible at any time and should
be presented in the same manner. That’s the point.
Gardner: So we're talking about big data, but we're not talking about it just in the traditional
warehouse infrastructure. We’re not talking about big data in the context of a business
intelligence (BI) application set. We’re talking about it across more consumer-type activities, but
we still need to deal with this data in a governed, secured, managed way. So, we're facing some
problems.
From your perspective Doug, you don't probably have to worry about big data so much. You just
want to access the services and the results of big data. You’re not going to be building out a
warehouse. But, from this point of mobility and then those implications of the volume of data
going up, how do you prepare your organization to take advantage of the big data without it
being chaotic, knowing that you’re down the food chain, on the receiving end of the analysis.
Potvin: Our mobility is not necessarily for us. We’re in an office with a phone and the computer,
and that's pretty much what we do. We do it every day. We've had discussions about providing a
mobile app for carriers, for value partners.
Available publicly
If we give them the mobile app, a lot of this information is available publicly. We know that
they're going from point A to point B hauling our product or hauling the shipper’s product. We
can give them the application saying here’s all your rest stops, here’s all the diesel stations, here’s
the pricing of the diesel station, and think about it adding value to them.
If we can add value to our carriers, it strengthens that relationship even more so. It's now a
matter of using data to strengthen the partnerships that we have. When I get back to the office
Monday, I'll be getting the mobile app dusted off, bring it back up, and add in a few more notes
to this whole situation. Extracting information is already out there brings value to all the way up
and down the entire process for us, entire vertical market.

12. We value our customers, our carriers, and our team members, and we value the communities that
we find ourselves in. So, if we can add some value to these relationships, and strengthen those
relationships, it's looking at data not just from my use and perspective, but also from
strengthening the relationships we have.
Gardner: We have one more line of questions for our panel. What interests you about what
you've heard and what might you think would be the top requirement for the next initiative for
Kapow, based on your business needs? Why don't we start with you, Doug? What would you like
to see from Kapow next?
Potvin: We're just looking for better information coming off those PDFs and to be able to parse
them a whole lot better than what we're currently able to do. That's the biggest thing, because the
generation of that data that becomes critical to us.
Gardner: Okay. Deutsche Telekom, same question. What, if you had a dream wish and you were
the only client of Kapow, and they had to listen to you absolutely 100 percent, what would you
ask them to do?
Hase: For us, it's how to monetize it, not to monetize for Deutsche Telekom, but together. That's
really important. We have to adapt all the different hundreds of partners of solution into the
whole system. For me, that’s one of the key points that we have to think about together with
Kapow, because we are not the experts on robots. We're a transport company provider, not
experts of robots.
Gardner: Okay. Rüdiger, your wish-list.
Adam: From a technical point of view, I think it's important as well to be very flexible, also to be
flexible in providing data as a service. If this is possible, I would appreciate working with Kapow
on those topics.
Gardner: Very good. Pedro, any thoughts about what you've seen in terms of future direction
and/or wishes for your organization?
Saraiva: I would like Kapplets anywhere. I would like to take a little sexy button and just throw
it across the room, so that someone can just plant it on their application.
Gardner: How would you refer to that? If you could brand that capability, what would you call
it?
Kapplets Anywhere
Saraiva: Kapplets Anywhere.

13. Gardner: Kapplets Anywhere.
Saraiva: Kapow would probably prefer to call it Kapplets Everywhere.
Gardner: Kapplets Everywhere, okay, very good, as opposed to Windows Everywhere, that
wouldn't matter.
Saraiva: No, there might be an issue there with trademark on them.
Gardner: Søren, do you have a wish list for things for the future?
Nissen: Yesterday, we were talking about directions for Kapow, and this would probably be a
really long-haul project for Kapow, spending time with the institutions that determine how
websites are built. Google has guidelines and tags for optimizing a website for their Web
crawlers. A lot of small companies out there have one Web developer, and that one Web
developer doesn’t also have time to build a very neat and nice API.
So, if Kapow would work with the HTML institutions and build guidelines where a Web
developer could simply use a Kapow widget in some entry field, and select it as mandatory, this
is a tag equals this, this is the data structure, and Kapow would wrap it as a RESTful API. So the
small 1 to 10 people companies that don't have the resources to build an actual RESTful API
with Kapow widgets inside the HTML code could just push one button and turn it into a
RESTful API.
Gardner: Kapplets Everywhere Ready Website Standard . . . awesome.
Well, I’m afraid we’ll have to leave it there. You’ve been part of a special BriefingsDirect panel
discussion, coming to you from the 2013 Kapow Wow user conference in Redwood Shores,
California.
We’ve been exploring the latest in real-time data acquisition, rapid information integration, and
proven ways to extract business value from big data across multiple sources. And we’ve now
heard how innovative companies are dodging data complexity through the use of Synthetic APIs
-- and in doing so transforming their businesses.
Please join me in thanking our panel: Jürgen Hase and Rüdiger Adam, both vice presidents of the
Machine to Machine (M2M) Competence Center at Deutsche Telekom AG in Bonn; Søren
Nissen, the CEO and founder of Click A Taxi in Copenhagen; Doug Potvin, the Chief Financial
Officer (CFO) at Trinity Logistics in Seaford, Delaware, and Pedro Saraiva, product manager for
the Content Shared Platform and Rapid Sourcing at Thomson Reuters in London.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout this series of
end-user success discussions. Thanks for listening, and come back next time.
Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies

14. Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a
variety of sources. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.
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