Evolution of IT, AI, and Automation in Intellectual Property Industry

AI and Machine Learning are revolutionizing IP practices all over the world. But have you wondered how these emerging technologies will impact the IP workforce? What are the new opportunities that lie ahead through digital transformation? Tune in to our IT for IP webinar and discover answers to these core questions and more.

Hosted by

  1. Sumit Prasad, Group Manager, ICT, Sagacious IP
  2. Prateek Mohunta, COO, Sagacious IP

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Webinar Transcript

From logistics point of view, everyone will be in listen only mode. In case you have any questions, I invite you to drop down your questions into the GoToWebinar portal on right-hand side of your screen.

About Sagacious

So, before I start, a quick round of introduction of who we are. Sagacious IP is an award winning IP research solutions provider working with the world’s largest companies, law firms, institutions, research organizations, and individual inventors. We help them monetize, defend and expand the patent portfolio along with driving innovation within their industries.

These are our solution capabilities, but I would like to today emphasize on why Sagacious is the right company to talk on this topic of adaptation of AI and automation in IP industry.

For past five years, Sagacious has been interacting with a lot of revolutionary software players. We are trying to innovate in terms of processes, automate the manual patent practices, and build effective solutions to increase efficiency in the overall IP industry.

Me, as a part of automation journey, we have been associated with a lot of our clients. We implement and solve some of their problems with help of these evolving IT technologies. Believe that we have a balance capability to help companies from current phase of IP to the next generation of IP. That’s what the name IT for IP stands.

Statistically speaking, Sagacious IP is one of the largest IP strategy consulting firms with more than 350 IP strategists located in 10 offices across 6 countries. That’s a sufficient introduction for our first time listeners.

Without any further delay, I would like to invite my co-speaker on the panel, Mr. Prateek Mohunta. Good evening Prateek, a very warm welcome to you.

Prateek Mohunta: Good evening Sumit. It’s great to be here. Just to quickly introduce myself, I am the CEO at Sagacious and have been in the business of patent research for about 14 years now. And it’s great to having worked with Sagacious. I have had a chance to work with a lot of R&D managers, patent attorneys and investors and taking strategic decisions about their IP and technology. And, today, talking about IT for IP, it’s a pleasure to be here and to be speaking about this topic.

Sumit: Thanks, Prateek. I would like to take some initial remarks from Prateek on this topic and how relevant it is in today’s era.

Initial remarks of the speaker

Prateek: Right. So, as I said, it’s really a pleasure to be speaking about it, because I’ve been doing this for about 14 years. And what we have actually seen in this field in terms of services, it has grown very slowly and gradually. It has evolved very gradually and very slowly, but, because most of the things that you will find related to the services in the field of IP, they are human dependent. Whatever you’re doing, searching or drafting, and even trying to manage the patent portfolio in terms of IP management and the audit work. It’s always under tight timelines and under certain budget constraints.

And when you’re dealing with a large amount of data, when you usually end up doing, a human intensive work, manually intensive work, it becomes very inefficient, at least, for humans because as humans, we can make informed judgements. But when it comes down to manually intensive work, you’re not very efficient about it.

So, keeping all of this in mind, I think it is clear that we need to think about how to make this more efficient, how to take that next leap in the quality of work that we do. And that’s why, I think we’re here talking about this. We want to talk about this more want to build the context here, and get everyone to understand what IT is doing on IP, and how we can all make use of that.

Sumit: That’s very correctly said. Let’s put a foundation of our webinar today, and try to quickly segment the complete webinar into four different sections.

Agenda of webinar

  • First, we’ll talk about how IT as a technology or as a service has evolved in IP practices, a quick journey about it.
  • Then we’ll talk about how IT has been adapted in IP practices. What is the adaption, what type of companies are playing role, and in which type of patent practices. That kind of landscape will try to quickly go through.
  • And then we’ll talk about the acceptance aspect of this IT technology in IP. Is it really being accepted by the IP practitioners or is it a far-fetched dream as of now?
  • And towards the end, we’ll talk about some of the challenges that still lie ahead and how Sagacious can help in resolving some of those challenges.

So, without further delay, I’ll quickly go to the first part of our webinar.

The patent practice itself is a very old service industry. It’s very old practice that we are doing from the time when the concept of invention was coined. There was a protection system in place in different jurisdictions across the world.

At the time, when we were more labour intensive, and we were more manual dependent on the patent filing process. The system of maintaining those documents was manual. We were maintaining physical files at the PTOs as different patent offices.

And even for searches, for what you grant of a patent, there were physical searches that used to happen. We used to rely on fax system, as that was the communication technology at that point of time.

Which changes were brought up by the new era of IP?

As we grew, as we went ahead in the timeline, the new era of IP started. Usually people called it as second version IP or second inning of the IP. In this, the patent documents were actually digitalized.

Fig.1: Changes in patent industry in last 15 years

Availability of machine translation

People started filing patents electronically, the availability of machine translation and all the data across different lingual systems. They came together, and we had machine translation so that we can understand inventions happening across the globe. We were not only relied on one particular language. It was a barrier earlier for manual searching and all the other analytics work.

E-mail communications and electronic searches

We shifted to e-mail communications and authorizations. All the searches that used to happen were now electronic, with the help of machines or computers.

Software companies providing new IP technologies

Fig.2: Changes in patent industry in last 10 years

In the last 10 years, we have seen even a more aggressive improvement in terms of technology. We saw a lot of companies coming, a lot of software companies coming in and providing patent proofreading technologies and proofreading softwares, patent docketing softwares, IDS tools, and different searches, the bullying and semantic search grew a next level we saw a lot of software players coming into picture and they provide a way to automatically search in the patent data, a huge depository of patent data that we have.

Fig.3: Patent industry now

As Prateek was mentioning, data grew up till the time we had limited literature to be searched, we were good. We had limited computing power, and we were able to meet the expectations. But when the data grew to a new volume where humans cannot manually or even with help of low hanging technologies cannot match up to that volume. Then, people started using the AI technologies or the next wave of technologies, and that’s where lot of debate started.

Whether machines would be compatible or are accurate enough to get the results? Or should we rely on manual based searching where we rely on the analysts and the examiners or examiner’s consent on patentability aspect of a patent.

So, now, we have a lot of experiments that are going across in the field of AI based search tools. We have a lot of softwares that are talking about big data analytics. So, that we can understand the data that is there in patent. We are even talking about two companies who are automating the process altogether, process of drafting a patent application. We have a lot of softwares and tools that are talking about document automation or the workflow automation in the filing system.

From this, what was the next leap that we are going to take? We are going to see a lot of convergence of this big data analytics. The more the technology advances, we’re going to see more convergence of AI, ML, and deep running algorithms into understanding of the patent data, into the understanding of the scientific literature that we are accumulating. And, obviously, the manual work that we are having as a system in place, there will be seeing a lot of automation, that is going to happen around us in the IP. That’s what we call would be the next generation of IP as we progress.

So, this was a quick overview of the evolution. And, let us also see, how the landscape looks like at the current stage. And what is the adaptation of these IT technologies into IP practices.

So, in front of you, you can see a landscape of companies. And this is just a representative landscape which is quite encouraging in the sense that we see a lot of players that are coming in. They are providing solutions to automate, or even improve the efficiency of the existing patents.

Tools for auto-generating patent drafts

So, it starts from the left-hand side, which is the creation aspect of IP. We have a lot of tools that are talking about auto-generated patent drafts. Also are talking about increasing the efficiency in the claim drafting process by maybe adding voiler plates, to claim mirroring. We improve the aspects of claim drafting by automatically writing the descriptions of the flow charts, or the summary, or maybe the abstract also.

These all softwares aimed to increase efficiency and let the IP practitioners focus on the important segment of the draft where they actually need to invest time. Then we also have a lot of software that are coming in to improve the proof-reading of the patent documents.

If someone will rely on human accuracy, then we are not very accurate about when we have to analyze or review a legal document which is 70-80 pages. So, there we have a lot of tools like patent bought or patent optimizer. They are very good in proofreading the patents based on the antecedents or filing the claim for support. You don’t have to look for those terms in the patent draft anymore. You can be relaxed and these tools can automatically do that task for you. You can check the inconsistency in the figure number or maybe inconsistency in the reference labels in the draft often a tedious task to manage.

Tools for search and analytics

Similarly, the aspect of search and analytics, there are a lot of tools that have matured to provide good pre-filing search capabilities, where you don’t have to wait for a manual search to complete the task and they can assist you, in completing that search in a very fast manner and these tools are increasing the accuracy day-by-day.

They are tested against various past examination histories, or maybe official patent invalidity of positions. They are trying to build a database or they’re trying to build that capability across that. So, that you spend less time searching and spend more time doing the work that matters. That is, in this case, interpretation of the claims or an interpretation or argument preparation for that particular case. AI assisted patent search platforms, they are quite known in the industry now and it’s a debate, how accurate that is. But it has been there in the industry for quite some time and we can see a lot of players coming into picture.

Clearly, there are a lot of players, like Black Hills and ReleSense that provides MPL database. Then we have a lot of tools, like Markify and Orbit Trademark. They help you to identify and to do the trademark search in seconds depending on the input and the algorithm has evolved over a period of time.

Tools for management of IP

Similarly, there are a lot of tools that are active in the management side of IP. It can be remote IP management, or innovation management, and, specifically for R&D and legal departments of big firms. Here managing innovation itself is a challenge.

Also, there are tools that are contributing in effectively managing the prosecution and the stages of responding to PTOs. This has overall improved the productivity and accuracy of the prosecution phase of the IP life cycle.

These tools are now being connected with you and you now have real-time data at your doorstep. You can customize the output based on your requirement and play with data at ease with the current IT technologies. There are many more players in all these verticals and maybe there are a lot more players that are innovating right now. They are trying to build solutions that would improve the overall efficiency of the process.

So, I’d like to invite Prateek. To share his thoughts on this landscape if he wants to, and what does he interpret from this snapshot.

Prateek: Right, Sumit. You are correct. A lot of these tools have actually helped us become very efficient in a lot of things that we do. So, one thing that we need to understand is, as I was saying specifically in terms of IP services and IP work that we do. The custom requests with custom deliverables and most of it can’t to be reached here and cannot be used again. It’s not reusable. Once we have done it, that’s about it. We’re not really able to use that analysis of the work that we do very efficiently again.

But if there are tools like these, for example, as we talked about, IP management, especially, that has improved massively. Similarly, there are tools which have come up on the searching and analysis. Even on the creating sites, which are making use of the data that’s out there. We are making use of the work that’s already done to make efficient use of the analysis that we do.

So, if we can continue to do that and continue to use the information and data available, we’ll be able to make our work a lot more efficient. It will make things better, make us focus on quality work that we do. So, all of these tools have actually focused on that, and tried achieving that. That’s exactly what we need to keep doing as we move forward.

Yes, so, as we move forward, these software and these tools have been using the underlying technologies. They have evolved in the IT space in a parallel regime. There are a lot of developing technologies that are evolved long back. I think there is a significant gap in the evolution of technology and the evolution of IT technologies in IP. But, it’s a good news that we have started using these technologies into our IP practices and started thinking of making it more efficient.

Software driven technologies at present

So, I’ll quickly talk about some of the technologies that the softwares are using at present.


The very first is digitalization. When we moved from paper system to the online filing system, the one of the biggest challenge was how to recreate that data, which we have in physical form. So, optical OCR and ICR, they played a very significant role while digitalizing the complete archive.

Then, we have cognitive document processing with the help of the computer vision technology. So, cognitive document processing involves conversion of these typed or hand-written text, or maybe scanned electronic documents into electronic information that can be used in the subsequent workflow.

So, within document processing, we have a document automation, which includes logic based system that can segment the complete document. It allows you to reassemble or assemble the legal documents in form existing information that is available with you.

The document automation can automate all the conditional text, or the variable text or the data that is contained in the repository, or within other documents. It has the capability of automating all of those things which allows us to focus on some of the key IP practices that we do right now.

Moving on to the layout analysis, again, using the computer vision and natural language processing, that is quite mature. We achieve this document layout analysis, system identifies and categorizes the region of interest in a text document. Based on that, it also detects the label, different zones and the layouts like title, caption, foot-notes. All these things are semantically available for the tool to apply the IP knowledge on to that document. And create the patent drafts, or the legal documents, or the contracts, or things of that sort. Document modeling, it looks at the inherent structure of the document. For example, tree like structure, it’s more how the document itself is structured, and has again evolved a lot in terms of technology.

Text Processing

Moving on to the next part, text processing. So, in text processing, we have text mining, where you can extract data. This enables us to search and analyse the records that are there as information that is there in the patents.

Using, again, the natural language processing, or natural language generation, we can process that data very efficiently. We can try to replicate what we think, as human and train machines to do that, and process that information.

In the last couple of years, we have seen availability of APIs, so that these softwares can build on top of that data, which is right now, available with PTOs. There are a lot of APIs that are available for these companies to try and innovate and build efficient practices for IPs industry.

Search Interface

Search interface, it has been there in industry for quite some time. And with Google Search engine, you saw that there was a lot of innovation. It has happened in the searching space, in the indexing space that has been applied to patent documents as well.

Data visualization tools

Data visualization tools, there are a lot of tools that represents the data which is in millions of records. And, how we can identify different aspects of patent document or IP document. How can you use that data to make informed decisions. And the multiple tools that have evolved to give you that representation.

Business process automation tools

And finally, on the operations side of IP. So, there are a lot of business process automation tools that allow you to process e-mail exchange functions, document flow functions, etc. This probably 10 or 15 years back, someone has to manually take care of it.

Fig.5: The SHIFT in tech

So, this is what is already there and what’s the shift that we are talking about? So, this is already there but the next thing, we are already there in that space. The big data is going to boon most of the digital industry that we are right now working with. And patent is also digitalized and it is considered to be a digital part of the industry.

So, as we can see that average CAGR is 13%. We assume that big data is going to be the next big breakthrough. It is in terms of analyzing information, the way humans do.

Similarly, to supplement big data analytics, we have different AI based systems which can assist you in developing those algorithms. So, that you can actually understand and analyse the data that is there in your repository.

Process automation

To supplement these two things, there is another growing market, which is called process automation. This is again, the next big thing in the field of digital space. That also includes robotic process automation, to enhance the capability of converting the manual processes into an automated process.

So, considering these technological shift, we believe that in next coming years, or next generation of IP, these new generation technologies would play a significant role. So, we think that there would be two ways on how this would impact the overall process.

It will completely automate the manual processes and there are a lot of processes that can be completely automated. This is with help of these technologies like AI Enabled Hyper automation for Document Processing. So, documents, now, process in a much more natural way, as human processes after reading an e-mail.

So, there are a lot of ways how you can implement these workflows in your company. All the clerical work that used to happen, at a manual level, that can be automated. It can be automatically taken care by the machine with very minimal error in those processes.

So, that is one part of IP practice that will be completely automated and something like preparation of the patent documents. So, the application area where these next generation technologies would play a significant role. We would see much more advanced version of softwares that could help us in automating these tasks, such as proofreading. It is already there, and it would be much more advanced and much more accurate.

Similarly, as we talked about robotic process automation, RPA, and IT automation technologies. So, this will allow us to automate the processes like scheduling meetings with internal teams, R&D teams or inventors, preparing the filing forms that can be automated, filing the documents with the patent office within a due time, client reporting, docketing, invoicing, IDS preparation and management.

So, we are already seeing a good convergence of technology on these services. We believe that these new technologies would be further automated to let us say overlap with the 90 to 100%.

Now, there is another branch of technology, which is right now evolving and we still need control in our hands. This can help to take a decision at the right time. And that should just augment the process that we are doing. We should focus on the aspect which is more research intensive rather than a manual process.

So, as we said, that in patent search, AI is assisting us in identifying the right set of documents. So, the role would be now to analyse the documents rather than find those documents. In those areas, like searching or patent classification and ranking FTO, infringement identification or IP landscapes and these analytics projects deep learning and AI algorithms are going to play a significant role in augmenting the overall patent practices with sufficient support.  This can help us improve the efficiency of its overall process.

So, that is what we believe that is going to be IP industry in coming years.

Let’s pass on the baton to Prateek to talk about whether whatever we just talked about the IT overlap on IP, is it actually materializing or is it is still a far-fetched dream for us?

Prateek: Thank you. Thank you, Sumit for that. And thank you for nicely explaining the entire landscape of various IT tools in IP.

So, moving on to the next slide. So, what we’re going to talk about now is going to be around how IP is getting impacted with IT. So, there have been a lot of surveys, lot of reports, that have happened and we have been researching in this particular space for really long.

We did come across a survey by IP Trend Monitor in 2019, that was focused on how AI will transform management of IP. The numbers are there for you to see. As you can clearly see, especially on the right side of the blue box, there are 2 or 3 things that received a really high positive response. And what’s clear from this is that IP experts actually see digitalization and advent of new technologies as a huge opportunity. What I believe, that’s a personal opinion, that it can actually be a game changer for the industry, as well.

Specifically, the IP portfolio management, patent searching and annuities payment responses positively, as above 60%. This shows that industry professionals are open and openly thinking about accepting or replacing specific administrative tasks. They are related to monitoring, research, filing annuity payments with some sort of automation tech. And that’s something that they actually feel will happen. However, what about the other things that are on-going, will this actually be potentially disruptive?

What we tried and did before this particular webinar is that we ran a very small, very quick survey. We tried and identify what people think, now in 2020, at this stage, especially with the circumstances around us. That is going to be the impact of automation and AI and big data, and these kind of technologies on IP services.

Sumit, can you move to the next slide?

Fig.8: Sagacious online survey

Right. And this was a survey that we did, and we’ll publish a more detailed report around it in the coming days. But what we can definitely see from here, again, it’s very similar, that prior-art searching patent analytics is something that people still think will be the segments, which will be affected most in the short term. Whereas, the more complicated and more human judgement and human analysis dependent, aspects, like transactions and drafting would be the least impact.

This is what the surveys showed, and this was, sort of a sample survey size of about 100 to 200 participants. What we also did to further validate, this was awesome.

We went out and asked a few questions to certain industry experts. I’ve been in the industry who are actually working on automating things. People who are actually getting impacted by these tools that are coming in. So, we decided to talk to a few people and see what they actually thought.

So, one of the questions that we talked about was, how is AI and automation based solutions going to find adoption in the industry. We talk to different people doing different things. And we also talked to people who are sort of using these kinds of things.

Fig.9: Industry says: Increase in acceptance in near future

The general understanding across the board was that this should increase the acceptance in the next 12-18 months. That’s something that was talked about by amplified AI. That was something that’s talked to about by MAG systems, which works on ideas automation, even specific which is dealing with automating the patent drafting market. And all of them together and even people who are using it. So, this is one of our clients, it’s a Fortune 100 company, they start-up at US. They said that they are also using AI for conducting prior-art searches and they’re aware that other people are also doing the same thing.

They expect to further increase over the next couple of year. They specifically expect that other players in the market would start coming up with certain more innovations, which will help this to become more widespread.

All right. So, this is the basic idea and this is sort of validated by what we were finding out based on the service. And this is something that clearly shows that this is there to be here and to help take us to the next level.

Cost savings

Fig.10: Industry says: 20-30% cost savings

So, the next question that we talked about was on cost savings.

Whether they think that this is something that will help them save costs, again, across the board, the average consensus was about 20 to 30%. Someone even went up to 40% in terms of cost savings that they expect. Would come in if they start using these automated tools and AI based technologies, as they move forward.

The idea behind this is that AI is going to come in here. Automation is going to come in here. It’s going to get adopted here, it’s already accepted at certain levels, and it’s going to get accepted further. So, this is something that we need to understand and we need to be aware of this change that’s happening in the industry.

Now, one thing that we also need to understand is that industry has already gone through a lot of changes in the past. There has been technology that has come in like dictation technology, there have been word processing that has happened, specifically natural language processing. It helped proofreading and automated proofreading to come in and now not having a tool like that is really unthinkable.

So, all of this has happened, and this has been accepted as we have moved forward. The roles have changed, but in terms of how the human interaction with it, or how the human level experience, that has not gone away. That has always increased, then moved on to more relevant and more value added things and this is something that is going to happen very similarly again. This is something that one of our experts said to us when we were asking them questions, and they talked about parallels that have occurred in parallel industry. So, just think about accounting or just think about something like architecture. So, you had electronic spread-sheets that came in, electronic tools that came in into accounting.

Now, CAG came into architecture, and both of them led to lowering of cost, it improve the quality. But, at the same time it improves or increases the demand for accountants and architects and this is something very similar. We can expect to happen in the patent or IP world, where if we start accepting and adopting this technology, our quality of work will improve. The value that we add to this will improve, but, at the same time, the demand for this will improve. This is because of the accessibility that we’ll be able to provide. This is also because of the amount of work that we’ll be able to do in terms of the quality and deliveries.

Now, one of the things that we’ve often heard, especially in terms of AI and technology coming in. Will this completely replace available manual solution and industry primarily focuses on? Is there not really going to be job cuts, rather, there’s going to be increase in quality roles?

Now, this is something that we need to understand, and this is something that we need to believe. Wherever there is quality in terms of creativity and judgement needed, humans are always going to be there in the loop. At least for the foreseeable future, they are going to be there.

So, that’s something that’s important for us to understand that this is not really going to cause job cuts. But it’s actually going to improve and move people to more value added services and spend time on value added things.

Sumit, I think we can move to the next slide.

This was based on what we talked in terms of stakeholders who are already there. One of the key stakeholders that in this industry are, patent offices. And it’s something that various patent offices have been doing since 2016. In German Patent Office, European Patent Office, USPTO, every one of them have specific budgets allocated towards this. They have specific teams, focused and geared towards working on AI based solutions, big data analytics and a lot of relevant digital technologies that are coming in. And they’re researching on it, they’re analysing it, and they are actually developing tools for their own usage.

Challenges faced by IP industry

Fig.14: On challenges – Industry says

Let’s just think about what the challenges would be. It’s something that we reached out to the industries and talked to them about it. Primarily, what we talk to them about, key ideas behind those was there are three specific things: Economics, Trust, and Control. How are we going to look at these challenges. Look at economics, look at the trust, look at the control, and how are we going to address them.

That’s how this industry is going to move forward and that is something that we have to tackle. Based on what we have learned, I think it is good to be something which will have to happen gradually. In the initial stages, we might need a manual override process when a human is there to catch specific wrong things.

But as the detection of these errors or the anomalous behavior, keep decreasing and keeps becoming less as we move forward, I think that human intervention will start decreasing, and that’s where the trust will build.

Fig.15: The Big idea around our thought process

And then, that human time can be allocated to more sophisticated activity, as we have been talking about. The manual activity or the automated things that we are talking about will become something which will progress to the next level. The humans will progress to the next advanced activity level. So, that is something that is going to happen in the next couple of years. And, in order to build that trust, it is going to be a hybrid model that is going to be used. That is something that we’ll have to move forward with.

So, industry also believes something like that. The big idea behind our thought process right now, is to understand those challenges, and to help. Because we have been in this business for the last 14-15 years, and we want to understand this. Understand the IP practices that are already there. Try and bring them together to create something which will help take both human expertise and technological tools together. It will improve results which, humans or machines alone, by themselves, cannot achieve.

And we will need to study all of that. Use all the latest algorithms and softwares that are there, and put them in the hands of the most capable analysts. And that is how we will deliver the most reliable results. And that’s how this thing is going to move forward. And this is where Sagacious IT 4 IP initiative, is something, that we’re trying to break. We want to help hand hold the companies, and clients and bring them into this. We want to help them embrace this IT 4 IP change that is happening. We plan to do that. That’s what we are planning to move forward with.

All right, so, as we were discussing that, we came up with a lot of things that we thought. People would come up with a lot of questions that will come up in their minds. So, we talked about patent search tools that are there. There are RFP process, an RFQ processes that people take up for selecting search vendors.

So, there could be similar questions around how can we evaluate an AI powered patent search tool. So, that could be one question that’s out there. How good is an automated patent draft? So, as Sumit was explaining the landscape of the tools that are available. There are a lot of people who are trying to automate patent draft.

So, how do we understand all of this? There are certain other questions which can be similar to an hybrid approach that we were talking about. How can this setup and implement a hybrid service approach, where there is an automation and as well as manual intervention?

So, how do we go about doing that? How do we fit tools that are already existing into our existing processes, do we have to change existing processes? Are there customizations that are possible?

So, all of these questions are going to come up. How to make the right selection with so many tools available? How to decide whether AI or automation tools are actually relevant for the processes that you have?

So, what we think, and what we want to go through this webinar as the Sumit mentioned earlier, as well. What can we actually do help answer these questions? And that’s where this particular webinar came up. And that’s what we plan to do as we move forward.

We plan to answer these questions too, future webinars that would be coming up. And I think we haven’t got a couple of them lined up. And the others can be checked out on our webinar registration page. So, please go there and check it out. The next one is on “Hybrid Patentability Searches”. And there are other webinars, as well, which are going to be in the series, “AI based Patent Searches”, “Patent Summary Tools”. So, we’re going to talk about more of these challenges and take up each of them, 1 by 1. And then try and answer and provide you with relevant information so that you can make correct decisions and informed decisions.

Right, I think that sort of brings us to the end of this webinar in terms of what we wanted to talk about, what we wanted cover. So, this is something that we have covered. And this slide shows, very quickly, the services that we are bringing in, in terms of the services that we will be providing, and that you can expect from someone like us.

Right, so, Sumit, I think we have come to the end of the webinar. Let us see if there are any questions that are out there, and see if we can take up some of them.

Question and Answer

I think there are a couple of questions that are there. First is,

What is possible right now that was not possible earlier?

So, I think, what is possible by AI today, maybe wasn’t possible even 5 to 10 years back. And the primary reason behind this, I think, is the volume of data that is available. At the same time, the processing power, that we have available, access to quickly utilize that volume of data.

One of the people that we talk to during this entire process said something very interesting. Applications today have actually become a lot more dumber rather than smarter. And what he meant by that was, earlier more complicated the app, the more sophisticated and advanced features were. It was perceived to be advanced, able to perceive to be something which was important and relevant. Whereas, now, the, simpler the app, the simpler everything is. And the less it forces us to deviate from our natural thought process, the better it is perceived to be and the more advanced it is thought to be.

So, for example, just think about MS Word 10 years back and compare it to what MS Word is today. That gives you an idea as to the less our mind is burdened with, the freer it will be to become more creative. That’s what we need to move forward to. And that’s why AI and the data that is available today, we don’t need to be burdened by that. We need to make tools available that will help us achieve that. Make use of that data to provide services that we can use. And also, make more efficient use of all the information that we have access to.

Have PTOs started using AI tools or these are just experimental projects?

Sumit: There’s another question that I can see in the chat box, that is targeting Prateek. People want to know that you showed that there is a survey of different PTOs. Have you actually observed that PTOs have started using AI tools or these are just experimental projects? As you said, that PTOs have started allocating budgets to these tasks. As of today, is it being practiced or is it just to experiment?

Prateek: It is actually being practiced right now. We have PTOs with a specific budgets. EPO, USPTO, German Patent Office, they have actually allocated budget, and they even have developed tools for their own usage. So, it’s not just that they are looking out for tools outside, which are already available.

They’re actually also developing tools for specific things that they’re doing. And, a lot of it has already been automated, especially if you look at on the trademark side of it. For example, the classification of the image marks that has come in, that’s been automated. And that’s completely AI based. So, machine translations that are available for a lot of PTOs websites, especially EPO. That’s, again, automated and it’s AI driven.

So, all of that is something the PTOs have actually gone in and done. And there are more things that they are coming up with they want to. Very recently, there was an RFP from one of the PTOs, which wanted to get a tool. It enabled them to analyse and make sense of the application faster and more efficient. So, they wanted to see if there was a tool that can highlight the indefiniteness in the claims. That highlight any mismatch between what is there in the claims and the specifications. And there were a lot of other things that this PTO wanted from this particular RFP.

So, they are actually taking it very seriously, and they’re actually spending money on it. They are looking to take this forward as soon as they possibly can.

Sumit: Thanks, Prateek. OK, so there is another question, quick question, probably, you can answer it in one line only. I think, already you have given a hint during the presentation. They will want to know, when we’ll be going to publish the survey results of AI and IP?

Prateek: So, we are actually working for the survey, actually got closed a couple of days back. We are working on analyzing the data that we have obtained. So, hopefully we should be out with the survey results in a week’s time or so.

Has Indian Patent Office adapted any automated tool using AI or ML for searchings or classification?

Sumit: OK, another question, I will take this up. Has Indian Patent Office adapted any automated tool using AI or ML for searching or classification?

So, yes, we came across a press release where they were saying that they are evaluating a Chandigarh based company called PT Consultants and their tool called XL Plat Labs to be integrated into the four patent offices that we have in India. There was no concrete confirmation, but, yes, they are kind of evaluating the tools that are available right now in the market.

So, people are asking for to share the presentations. OK, we’ll definitely share the, the video links of this webinar. Yeah, recording of this webinar.

Prateek: Perfect, I think Sumit with that, we go to the end of this webinar.

Sumit: Yes, they are a lot of other questions, we’ll try to address them individually. Thank you, Prateek, thank you for your time. I want to express a big thank you to our listeners who helped to start this webinar on time. We are up on time and finishing it on time. We highly appreciate your continued concentration and participation.

Please join us in our next webinar. We are going to dive deep into these questions as Prateek said. We’ll try to compare the tools that are available. You will get more information about these upcoming technologies that are going to disrupt the IP industry.

Thanks again, and have a great evening ahead for Indian listeners and for East Coast, have a good day ahead.

Thank you so much.

Prateek: Thank you everyone. Bye-bye.

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