What is your role and which team/technology do you handle at iManage RAVN?

I’m one of the Co-founders of RAVN, which was acquired by iManage in May 2017. Presently, I’m Vice President of Strategy at iManage for RAVN. I’m responsible for the product’s ‘Go to Market’ strategy aimed at corporations and financial services organizations globally.

How did you start in this space? 

I started way back in this space when I was at BT in the Information Retrieval and Research Lab. Subsequently, I worked at other companies too in the Information Retrieval space. I was very fascinated by data – data was growing exponentially, presenting a huge management challenge for organizations and so there was a dire need to find a solution.

How is your interaction with smart technologies like AI, Customer Data Analytics, and Intelligent Automation? What galvanized you to be part of iManage?

Fast-forwarding to 2010, I co-founded RAVN Systems, to expressly to address the problem of unstructured document data. We realized that to be efficient in this process, we needed to understand the content more deeply rather than just relying on keyword searches. So, we developed the capability using AI and Machine Learning to search unstructured data as well as undertake the process of identifying the types of documents, classifying them and then extracting the required information. For example, the technology can be used to initially identify Property Lease documents, and thereafter key information such as rent, termination clauses and so on can be detected. The legal industry, due to the high volume of documentation that it generates, was a logical fit for the RAVN solution. We were seeing annual revenue growth rates of over 80%.

In May 2017, we were acquired by iManage, the leading technology for document management in the legal sector. iManage is the perfect home for RAVN. iManage had so much document data ‘under management’ so to speak based on the solution’s deployment across the legal industry, and RAVN had the capability to understand that data.

What are the various technologies and principles driving Document Management Solutions?

We are constantly taking advantage of newer technologies to evolve our document management solution, iManage Work. We are using modern and highly scalable technologies to provide reliable, stable and scalable solutions to organizations in the Cloud.

On the AI front, we are developing a vast amount of Machine Learning capability in-house to further evolve iManage Work – in addition to applications that are aimed more directly at using AI capabilities on specific document sets.

It is critical that document management isn’t seen solely as a technology issue. What makes any solution relevant is when domain expertise is applied to the business problem it aims to address. With this approach, we are exploiting AI technology to help tangibly address the challenge of unstructured data in the legal and financial services sectors.

What is your vision into developing AI for Marketing, Sales and Customer Support?

Our mission is to make professional services organizations such as legal and financial services more efficient. Our solutions are industry-focused, not on specific roles or functions within an organization. Many different departments can use iManage RAVN, depending on their needs and projects.

How do these capabilities impact Digital Transformation journeys for an organization?

We deal with industries’ legal and financial services that are quite old-fashioned in the way they typically operate. So, when our solutions are deployed in these organizations, they often have a dramatic effect on the business as many routines, manual and even arduous tasks are automated for the professionals. Because our solutions can deliver automation at scale, firms experience a much higher throughput of work as suddenly, these organizations are not constrained by the capacity of individuals to manually perform tasks.

To illustrate, a law firm potentially deals with thousands of documents per case per year. So, lawyers physically read these documents to draw out key information. If technology then makes this entire process say, 50% quicker for them, it instantly impacts their efficiency and productivity – and their morale, an area that is often overlooked in firms. AI technology takes away the unnecessary drudgery from professionals’ day-to-day activity, allowing them to focus on tasks that really matter in resolving and winning legal cases or giving professional advice. This, in turn, has a positive effect on the firm’s bottom line.

What is your vision for growing AI-driven revenue opportunities?

We deliver AI technology to clients who then use the solution to make revenue gains. So, we are one step removed, in that sense, from exploiting the technology for revenue gains. Our clients reap the commercial benefits of utilizing technology.

As mentioned above, AI greatly enhances a firm’s ability to deal with caseloads that otherwise would be significantly constrained by the capacity of humans and hence impact the organization’s ability to grow revenue.

How should Marketing and Sales organizations leverage AI to extract better ROI from their data?

There is definite value for Sales organizations utilizing AI adoption. A large telecom company is a good example. The Sales organization in this corporate has been able to spot other commercial opportunities, which probably would not have come to the fore without the use of AI technology.

With contracts under management in RAVN, they have been able to compare information in these legal agreements with other data existing in the wider organization. For example, one of the telecom company’s clients was contracted to use a maximum of 1000 phone lines at peak times, but the technical systems showed that they were using more than that. This visibility of contractual information presented the telecoms company with an opportunity to up-sell. Without RAVN, this visibility would not have been possible.

For any organization, having this kind of data at their fingertips can be transformational.

How should young technology professionals train themselves to work better with AI, Automation and Optimization techniques?

For technology professionals today, there is a multitude of courses that impart knowledge and train individuals to work with AI. But the real question is, how can other professionals (e.g. lawyers), who aren’t engineers and computer scientists, adapt to this new reality?

AI adoption is still new in the legal sector, but anecdotally speaking, increasingly, the most desirable legal professional today is one whose background in law is coupled with expertise in/applied use of new and upcoming technologies. They are undoubtedly the most sought after. We are regularly asked by our clients for guidance on what technical skills they should be looking for in their staff.

In firms and individuals alike, there is a growing realization that there needs to be a human-machine partnership so that people can do their jobs better. While the machine can do the routine tasks more efficiently and faster, that doesn’t mean that it also understands the ‘why’ or ‘how’ to do that task. The need for human input and guidance will always remain. Professionals must exploit the capability that AI offers for their individual and organizational benefit.

What technologies within AI/NLP and Cloud Analytics are you interested in?

We are interested in all aspects of NLP and Deep Learning capabilities in order to train our models.

The core algorithms in the AI space are open and were developed a long time ago. The reason they are fashionable now is that there’s now the computing power to deploy them.

The crux is therefore not the technology, but what industry expertise solution providers can offer to help organizations exploit these technologies. The level of industry expertise (e.g. law, finance) that AI vendors apply to solutions is what will set one apart from another. Also, quality data is paramount. An algorithm without data is nothing. He who controls the data controls the algorithm and the value that AI technology can provide. These two issues are often overlooked or not given the due importance they deserve.

What industries you think would be fastest to adopting Analytics and AI/ML with smooth efficiency? What are the new emerging markets for these technology markets?

Typically, the technology industry has been the quickest to adapt to AI. By nature, technology companies have a culture of not fearing disruption. The retail sector has been an early adopter.

AI presents a huge opportunity to the professional services sectors such as legal and financial services, but they are historically averse to disrupting themselves. This said, attitude is changing, and a definite shift is taking place in these markets too.

Tag the one person in the industry whose answers to these questions you would love to read.

These questions are most relevant to companies, but on the subject of AI, Professor Richard Susskind is always interesting. Also, there is Professor Dan Katz, who is very knowledgeable and has a fascinating view of AI in the legal sector and more widely in industry.

Thank you, Peter! That was fun and hope to see you back on MarTech Series soon.