Thanks, Aleksey. Good afternoon everyone, and welcome to our earnings call for the first quarter of fiscal year 2023. Revenue for Q1 2023 was $33.1 million. Adjusted EBITDA was negative $13 million and total customer count grew to 1,388. Revenue was above the high end of our guidance range and adjusted EBITDA significantly exceeded our guidance range. We have made steady progress on the operational changes that we expect will lead to profitability, including the launch of our new office in Delhi. As Michael will share in more detail, this has allowed us to improve our adjusted EBITDA outlook for this year and pull forward our anticipated timeline for achieving positive adjusted EBITDA from Q4 2024 to Q3 2024. Q1 was a very exciting quarter for us from both the product and the sales and marketing perspective. First, let's talk about product. We are huge believers in AI at Disco. Recent advances in large language models that you will have read about in the news as well as less heralded but equally important advances in technologies like vector search represent in my opinion, the most important technology development since the mass adoption of the internet in the 90s. These technologies which AI Labs throughout the world have been working on for years are finally ready to be incorporated into products that can deliver real value to everyday users. In Q1, we introduce Cecilia, an integrated AI chatbot for large scale Ediscovery. Cecilia will allow lawyers to ask natural language questions and receive narrative answers based on information in the documents in a customer's private Disco Ediscovery database. To support her answers, Cecilia will provide citations to documents in the database, allowing lawyers to verify her answers, cite evidence in support of them, and use the documents as a starting point for further investigation. Cecilia is differentiated by her ability to answer questions based on private data rather than the public internet or public corporate of books and articles. To do so at Ediscovery scale in databases that may involve millions or tens of millions of documents to cite evidence in support of her answers and to do all this while integrated into a secure platform that lets lawyers do other legal work like ingesting data, exploring and analyzing documents, orchestrating large scale reviews and preparing productions or disclosures. We launched Cecilia at Legalweek in New York and allowed customers and prospects to begin testing her, asking her questions themselves. At these initial demonstrations and in conversations with our top customers, we are hearing fantastic feedback. Lawyers immediately see the power of Cecilia to accelerate the process of understanding the facts and finding evidence in legal disputes and investigations. I would've loved to have had Cecilia help me on cases when I was a practicing attorney. We anticipate that Cecilia will be generally available in 2023 after an initial staged rollout. We will provide further information on pricing at that time as well. Cecilia is both the first step in our productization of modern AI technologies and a continuation of Disco's investment in AI that dates back almost to our founding. I am often asked about Disco AI and the direction we are going. What is Disco AI exactly? What does it do? How is it differentiated? Disco AI is a collection of technologies that is fully embedded in our platform and that is productized to allow lawyers to seamlessly use AI in the course of legal work. Disco AI powers predicted tags, which helps lawyers identify documents related to particular legal issues. Our predicted tags technology predicts how a lawyer would tag a document based on how lawyers have tagged other documents in the past. For every document predicted tags generate scores for each tag that indicates how likely Disco AI believes the document is to be tagged a certain way. Users can then search by these scores to find documents that are likely to be what they’re looking for. They can incorporate predicted tag scores as part of more complicated searches in filters and search visualization. Predicted tags can help them review documents more quickly by telling them what they should be looking for in a document. Predicted tags can be used to sort documents for review, ensuring that lawyers are looking at more of the important documents per unit time invested and that lawyers find more of the important documents more quickly. And predicted tags can be used to do real-time quality control on human reviews. Identifying areas where human reviewers disagree with Disco AI’s recommendation. Disco AI powers topic clustering with automatic indexing, which can take millions of documents and organize them by relevant topics labeled using terms and phrases used in the actual documents. This allows lawyers to understand what topics are covered by documents in a database before beginning a review. It helps lawyers learn the particular language or jargon used in a database. And in conjunction with filtering and search visualization, it lets lawyers see what topics are covered in particular subsets of a database, for example, in the documents from a particular witness or party. And Disco AI powers cross matter AI, which allows lawyers to use models trained on earlier matters on new matters. This allows lawyers and ultimately their clients to get leverage on the work they invested in prior matters to accelerate review on new matters that involve similar facts or similar legal issues. Just as a lawyer who has handled a certain kind of case many times in the past can be more efficient than a lawyer who is handling that kind of case for the first time, Disco AI can become more and more effective as it learns across matters, not just within a single matter. When we think about Disco’s product roadmap, we think about modern AI technologies unlocking features in four areas, first is question answering of which Cecilia is an example. Second is document analysis. We think modern AI can be used to tag and parse documents, labeling, summarizing and extracting data as instructed in natural language on a document by document basis. Third is drafting and document generation. And fourth is providing a natural language user interface for Disco’s platform where a user can simply ask the computer to do what they want, making our products even easier to use. Our ability to take modern AI and integrate it into a broad platform where lawyers already do their work and through which we have access to private data and work product to power our AI models represents a material advantage for Disco relative to pure-play AI companies. To be clear, these are ideas for future product development, not product features that we have today. But we believe this framework can help you understand how we are thinking about productizing modern AI technologies into our platform and give you insight into why we think these technologies will be impactful in accelerating and automating legal work and improving the experience of practicing law for our customers. Artificial intelligence is not the only element of our platform we are excited to discuss. This quarter we’ve also announced the release of Timelines in Case Builder. Timelines allows lawyers to collaboratively create events and facts, link them to depositions, documents and other evidence in the Disco platform and elsewhere, and assemble them into timelines and chronologies that the legal team uses to understand, develop and present their case. Timelines is part of our strategy to be the end to end legal technology provider, whereas Ediscovery generally occurs well into a legal matter, Case Builder is now well positioned to capture the matter in the moment a client comes to a lawyer with an issue. Our customers have been asking for the capability that Timelines provides for some time and we are very pleased to bring it to market. There are other under the hood features we released this quarter as well that are core to improving Disco capabilities. One example of this is live re-indexing. Periodically as we develop our products, we make changes to the underlying data or search architecture that enable improved performance or new capabilities. Live re-indexing automates the process of moving databases that are on older versions of our platform to the latest versions. Previously, this was a time-consuming task managed by human engineers on a case by case basis. We believe live re-indexing will improve the user experience for our clients, especially those clients whose matters tend to last for multiple years on our platform. On the sales and marketing side, Q1 was a productive quarter. The highlight of the quarter was strong funnel activity on an aggregate and per rep basis. Across our measures such as meetings, near-term opportunities and wins, we have been seeing accelerations since the start of the year. This is telling us that the operational initiatives we have been implementing internally and that we discussed on the last earnings call are starting to drive results. In our industry neither we nor our customers know how large a matter will ultimately be, but we do control our ability to go after every deal. Our improving pipeline metrics demonstrate success in that effort. While we are pleased with a continued improvement in pipeline metrics and the resulting growth in total customers, we continue to see less usage of our platform on very large matters across all our products. Additionally, we continue to see pressure from our largest customers to reduce their spend on our platform by reducing the amount of data in our platform more aggressively utilizing lower cost Disco offerings like Disco ECA, and renegotiating total spent. Given our usage based business model, this pressure on usage levels can mean that revenue does not grow in line with the improvement we are seeing in the pipeline metrics that we more directly control. We can sell lots of new customers and add lots of new matters without necessarily seeing the net increase in usage that would drive revenue growth. We continue to believe that the right strategy is to continue adding new customers to our platform, drive increased adoption of our platform across more matters at each customer, and drive customers to adopt more Disco products. Over time, we believe this will result in increased usage and consequently increased revenue. In Q1, we launched our Law Better marketing campaign. Law Better announced to the world the Disco is here to make the law work better for everyone. We launched on digital streaming services with full length commercials as well as a targeted digital blitz on social media. You might have even seen our Lady Justice or Lady J on your own TV. If you have not, you should look up our spot. Our customers and new prospects have been very positive about this campaign. We are seeing high engagement with our content across all media channels. On our website, visitors are spending 15 times more time on our campaign pages versus sitewide averages. We are seeing engagement with some of the largest legal buyers in the world coming to our website, exploring our products, and reaching out for conversations. Both Cecilia and Law Better were on full display and Legalweek in New York this past March where we saw strong attendance, engagement with our team and lead generation. One lawyer at the show told us that when he saw the Law Better campaign on TV, he brought his entire family into watch. It’s not often lawyers receive marketing attention. We are pleased with the excitement our campaign has generated among our customers and prospects. Finally, operationally, we are continuing our push to globalize with the opening of our new office in Delhi. Through our India presence, we will be able to provide 24/7 customer service and support to our customers worldwide and continue to scale out other business functions including engineering. This team will augment our existing team of Discovians in North America and Europe and will be a tailwind on our path to profitability. With that, I will turn it over to Michael.