Tom Dunlop, CEO and Founder, is an excellent business and technical attorney, and Tom’s experience in reviewing contracts is the catalyst that leads to summary. Prior to this, he served as Global Legal Director for several fast-growing technology companies.
The summary is to change contract lifecycle management (CLM) by enabling the entire enterprise (not just the legal team) to faster and smarter contracts. The platform integrates directly into widely used tools such as Microsoft Word, Teams, Slack, Outlook, and Gmail, meeting users they already work for. With an intuitive user experience, expert implementation and powerful AI, simplifies and accelerates the contract process. Summarizing CLM adoption focused on driving business scope, redefining how contracts are managed, reviewed and executed across organizations.
What prompted you to create a summary? Have the specific challenges you face as general counsel led you to develop AI-driven legal solutions?
Several things inspired me. Previously, as Global Legal Director, I would mark and print out with my highlighter, review contracts and try to create a summary of everyone. There are also some very demanding teams of salespeople who need attention and understandably want to complete the deal. Obviously, automation tasks are needed. I work in a very high growth technology environment, so when it comes to innovation, I have an entrepreneurial mindset. Everyone around me is also constantly looking for a better way to do things. These things are the catalysts I developed and started to summarize.
Since its establishment in 2018, how has the summary developed? What are the key milestones along the way?
At first we were a universal summary tool, so when we decided to focus on the legal industry, especially internal consultants, it was a big step forward. Next is our goal of creating a holistic solution that will serve as a touch point for each shrinking interaction, which also leads to an expansion of our capabilities. The third milestone is when we start embedding intelligence into other tools, leading to the real takeoff of adoption. Then we expanded to the United States and subsequently the rapid growth.
We have achieved a lot along the way. We first use Word add-ins and AI features. We arrived at the market for the first time with teams and slack chatbots that can interact with the law and create contracts. And, in the near future, we will get the extra features of the first-time market. We are constantly evolving.
What setup summarizes other contract lifecycle management (CLM) solutions on the market?
Our unique selling point is our embedded approach, rather than an all-in-one CLM platform. Fundamentally, these are options, and we believe that there is a stronger embedded experience with existing and familiar tools and facilitate adoption. Our use of artificial intelligence (AI) and natural language processing (NLP) is also a differentiator. Its ability to simplify processes and reduce manual efforts is driving new levels of cost efficiency for legal teams.
At present, which industries or legal functions are leading in AI adoption and which industries are lagging behind?
Because of the large number of transactions and focus on efficiency, internal consultants of technology and software companies are more likely to adopt AI. When you are in a more centralized environment, removing the blocker to speed up the transaction process is key. We see adoption of all legal functions. However, as the voice of the enterprise, the general internal team may actually be an obstacle to AI. They need to approve solutions, which may slow down adoption of users and wider business capabilities. However, larger business teams that focus on focus know that they will increase productivity and savings immediately, so they adopt AI faster.
How do you view the legal work of AI beyond contract analysis? What other legal tasks can AI simplify?
A contract is a system of record for any business transaction that provides all relevant relationship data, from the person you sign up to the special obligation to the termination details. Accessing that information and making it available is something we are dealing with contract analysis and summary. Putting AI on the back, you can drive data drives between systems and workflow orchestration across various parts of your business. This opens the door to the application world. It may sound far-fetched, but AI can even change the legal service model in one day, allowing companies to charge based on the knowledge provided rather than the time.
according to Summary of recent surveys89% of in-house legal professionals use AI tools, but remain focused on privacy and security (45%), limited understanding or training (37%), and lack of clear use cases (31%). How can legal teams go beyond initial AI adoption to ensure they use it safely and effectively in their workflow as trusted partners?
They need to understand how AI works, what to look at from a security perspective and how data interacts with AI models. You have to make sure they use it safely and effectively as trusted partners in your workflow. This requires training and clearing AI policies. Team members should also understand how AI will affect the role of general counsel over the next five years. Once this knowledge is acquired, they can apply what they have learned to develop larger use cases and stimulate further adoption,
How do you think of tools like AI-driven tools that will change the roles of general lawyers and internal legal teams over the next five years?
I think this will get them out of lower value, large capacity tasks so they can focus on the right type of work. This will also allow the general lawyer to expand the knowledge of the legal team and the business itself as well as their experience. In addition to giving up time-consuming manual tasks, leaders will know that such work is being done to their standards.
Do you think the regulatory framework needs to be developed to better control the use of AI in legal technology?
The regulatory framework will require specifying the data used by the language model (LLMS). Additionally, the model may be required to use validated content, which will shift the focus from the amount of data to quality and relevance. Overall, I do think we will see the evolution of regulatory frameworks and that the model will better understand the data it uses before presenting the answer.
What role does integration (e.g., Microsoft Word, Teams, Slack) play in making AI-powered legal tools more accessible and user-friendly?
Moving forward, it is crucial to embed AI into user workflows and experiences. The question is, how do you do it and make it easy for the user? Integration with words, teams, and slack is fundamentally important because people are already using and adopting these tools every day, making it the easiest point of access to launching queries.
Integration with everyday tools will ensure AI-driven legal tools are easier to access and user-friendly.
What’s next? Should we expect any upcoming features or extensions?
We just launched the next-generation AI-powered CLM and use smart agents to speed up reviews and unlock contract insights that use Aneccentic AI to handle tasks from redline to review. We have also expanded the capabilities of chatbots to interact with various datasets. These are just a few things we plan and we look forward to introducing other powerful CLM development projects.
Thank you for your excellent interview and hopefully learn more about the summary should be visited by readers.
