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Bim Dave

Bim Dave is an experienced legal tech leader, with 20 years experience in the legal software arena that spans technical support, support team management and global technical services delivery strategy and execution. He is technically focused, driven by quality and customer satisfaction and able to bring global teams together.

Tell me a little about your background and how you ended up doing what you do now.

I currently serve as EVP at Helm360, a legal technology company that helps law firms implement best of breed solutions. Prior to that I spent 16 years at Thomson Reuters which is where I started my career in legal technology. My first role entailed providing technical support for customers of the Elite product line which in those days was Elite for Windows, Enterprise, WebView and a number of ancillary products. I was the first technical support person in Europe as Elite, as it was then known, expanded in the region. I then went on to manage the EMEA Support team for Thomson Reuters and after a few years took on the role of Global Technology Services Director where I was responsible for all of the technical implementation teams that were involved in delivering Elite’s 3E product line. This included data migration, custom development, integrations as well as templates, reports etc. While I was there, I architected and delivered an ETL framework that significantly lowered the cost of delivering data migrations.

At Helm360, I look after all of our products and services teams which include Termi, our AI chatbot, our 3E test automation tool and Digital Eye, our data discovery and cleansing product.

I have always had a passion for customer service, having grown up in a newsagent I’ve been serving customers in some shape or form since a very young age!

How do you define a chatbot and why should we care about chatbots?

Chatbots can, when implemented correctly, bridge the gap between a user and numerous underlying business systems. In my experience, firms typically implement best-of-breed solutions for time entry, cost recovery, financial management, billing, collections etc and as a result, tend to have very differing user experiences between each vendor's application. They may not be “bad” experiences but can be significantly different and lead to frustration and lack of user adoption at a firm, particularly at the lawyer level.

I remember talking to a managing partner at a global law firm who had implemented a new finance system. During the implementation the partner was very engaged in the billing process and how his team needed to be self-serving when it came to the workflow. He was keen to get involved in design decisions and actually came up with some great suggestions that would lead to an efficient workflow being implemented. After they went live, I went back to visit the firm to see how they were getting on. When I asked the managing partner how he and his team were getting on with their custom billing workflow, he replied “Bim, you guys delivered a great solution… our finance teams are loving it. We can see business efficiencies and positive ROI but I have to be honest with you, neither myself or my teams use it!”. I was pretty shocked to hear this as you can imagine but his explanation made it all make sense: “Bim, by the time it takes me to open the system, do all of the clicks it takes to edit or approve a bill, I could simply send a quick IM (Instant Message) or email to my billing secretary and they will do it for me”.


The bottom line was that his time was valuable and every minute saved self-serving in the finance system could be better spent serving his clients. It was at this point I wrote the first version of Termi, our AI chatbot solution that allows lawyers to write a simple instruction in natural language and get an answer back, whichever system that data may live in or where it needs to be actioned. Things that used to take time or caused frustration that led to low user adoption became as simple as sending a quick message. For example:

● "Send me the latest invoice for <client>" would instantly retrieve the invoice copy from the billing system and send it to the lawyers device wherever they were.

● "What have we billed <client> this year?" would provide the lawyer with a quick and easy to digest number from the finance system.

● "Who at our firm speaks French?" would perform a skills lookup to determine which multi-lingual lawyers could help win new business with a new French speaking client.

● "What are collection follow ups do I have?" could invoke a collections process that automatically schedules appointment follow ups in your calendar to chase customers.

● "Show me my approvals" would allow easy one click mobile approvals for bills over predetermined amount.

What is the role of AI in chatbots and their utility for companies?

AI plays a crucial role in chatbots. We've all had a bad experience with simplistic chatbots of the past that would very easily get confused and lead to lots of "I don't know how to answer that question" responses. What AI allows us to do is use prebuilt models that are very easy to train on the knowledge contained within a specialist area of law for example. Chatbots can be trained using machine learning algorithms to improve their performance over time. This allows chatbots to learn from past interactions and improve their accuracy and efficiency. The more you feed it with knowledge, the more useful it becomes. From a law firm and legal department perspective, this could have a great impact on bringing efficiencies to routine legal talks resulting in cost savings and better value for clients. Some possible applications include:

Document review: AI can be used to quickly review and analyse large volumes of legal documents, such as contracts, leases, and settlement agreements. This can save time and reduce the need for manual review by lawyers.

Predictive analytics: AI can be used to analyse past legal cases and predict the outcomes of similar cases in the future. This can help lawyers to prepare their cases and provide more accurate advice to clients.

Legal research: AI can be used to quickly search through large volumes of legal literature, such as case law and statutes, to find relevant information. This can help lawyers to more easily find the information they need to build their cases.

Contract drafting: AI can be used to generate legal documents, such as contracts and leases, based on templates and input from lawyers. This can help to reduce the time and cost of contract drafting.

As well as these key benefits, its also important to highlight some of the risks of AI technology so that they can be managed correctly to ensure this risk is mitigated whilst getting the best value out of the technology:

Bias: ChatGPT was trained on a large dataset of text from the internet, which may contain biases and prejudices. This means that the AI system may inadvertently reproduce biases and perpetuate discrimination.

Misinformation: Since ChatGPT generates text based on its training data, there is a risk that it may generate false or inaccurate information, especially if the training data contains misinformation.

Privacy concerns: When interacting with ChatGPT, users may provide personal information that could be sensitive or confidential. There is a risk that this information could be compromised if the system is hacked or misused.

Security risks: There is a risk that ChatGPT could be used for malicious purposes, such as spreading propaganda or generating fake news.

Whilst these are focused around ChatGPT, the same risks typically apply to any AI system.

What is ChatGPT and why has it generated such interest and excitement?

GPT stands for "Generative Pre-trained Transformer". It's a type of artificial intelligence technology that is designed to understand and process human language. ChatGPT is a product from OpenAI that leverages this GPT model to allow users to have intelligent (to a certain degree!) conversations with a chatbot.

Essentially, GPT is a machine learning algorithm that uses deep neural networks to analyze large amounts of text data and learn patterns in language. Once it has been trained on this data, it can generate new text that is similar in style and tone to the data it was trained on.

ChatGPT has generated a lot of excitement and buzz in the legal industry and far beyond due to the advanced nature in which it is able to understand what is being asked and then use this to generate meaningful responses. There are 4 key areas that make it very interesting:

Conversational Capabilities: ChatGPT's ability to hold human-like conversations and respond to a wide range of queries makes it feel like you're interacting with a real person. This has led to many people using it as a tool for generating marketing content (e.g. Blog posts), writing code in multiple languages like python and .NET as well as fun stuff like writing contextual poems!

Accessibility: ChatGPT is available 24/7, and anyone with an internet connection can access it from anywhere in the world. This makes it an incredibly convenient and accessible tool for people who need quick answers or just want to have a conversation.

Natural Language Processing: ChatGPT is built on advanced natural language processing (NLP) technology, which enables it to understand and interpret natural language input. This makes it easier for users to communicate with the AI in a way that feels natural and intuitive.

Cost savings: Companies can save on customer support costs by using chatbots. Chatbots can handle routine inquiries and provide basic support, freeing up human staff to focus on more complex issues.

From a Termi perspective, we've integrated it into GPT's Davinci model allowing firms to benefit from our ready-to-go integrations into leading systems like Elite 3E, ProLaw and Aderant but now combining that data with GPT's capabilities. This means within the same experience, Termi can answer and action based on data living in those in-house systems but it can also empower lawyers to use it to generate blog content, review and generate contract clauses and so much more.

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