Revolutionize legal research with LegaWrite! AI system transforms legal analysis into pleading and outcome predictions. Utilizing fuzzy logic graph theory to map laws and precedents in seconds.
Current Status
Traction: Contracts secured with several law firms eager to use & collaborate on LegaWrite's development, with a 26-point requirement list from one, addressing 11 in the initial release. Pricing: Attorneys show readiness to pay around $500/seat subscription fees, with experts seeing huge potential in LegaWrite to revolutionize the sector. Tech Status: Presently at TRL L3, featuring an operational foundational knowledge graph, input translator, and inference capabilities through fuzzy logic algorithms. In 4-6 months, expect significant improvements and a prototype ready for production.
Market
Primary customers are law firms of all sizes, corporate legal departments, legal document companies, legal research aggregators, and individual attorneys. Offer customized enterprise pricing plans for organizations based on use cases and users. Individual attorneys can purchase via monthly subscriptions starting at $300 per case analysis. Total addressable market just within U.S. legal industry is approximately $300 billion. Competitors like Casetext focus only on search, Trellis on analytics. Our solution uniquely combines research automation, predictive insights, and knowledge graph leverage. By increasing productivity 10x, we will capture market share starting with 0.01% of total spend - $30 million revenue. Land-and-expand model to gain user buy-in across customer segments. Significant market opportunity as legal sector adopts technology to improve efficiency and quality.
Problem or Opportunity
The current process of legal research and analysis is time-consuming, inefficient, risky, and expensive for both attorneys and clients. There is a clear need for leveraging technology like AI and big data analytics to help transform the practice of law.
Solution (product or service)
LegaWrite is an AI-powered legal research and analytics platform. It transforms how attorneys conduct research and assess cases by automating manual work, providing predictive insights, reducing costs, and unlocking the power of legal data. Our solution aims to bring legal services into the 21st century through cutting-edge AI and data analytics capabilities tailored to the practice of law.
Competitors
Main competitors are Casetext for legal research, Trellis for analytics, WestLaw and LexisNexis for case law databases. Casetext provides search to find relevant cases faster but no automation. Trellis focuses on analytics and judge tendencies but no workflow integration. Westlaw and LexisNexis offer vast databases but no AI for analysis. Other players like Kira and LawGeex focus narrowly on contracts. Our solution is unique in combining automated research, predictive insights, and knowledge graph leveraging. By improving efficiency 10x over current manual methods, we address a key pain point. Law firms still rely on expensive, time-consuming manual research and guesswork for case strategy. Our AI assistant tackles these frictions directly by automating legal analysis end-to-end. Significant potential for cost savings, productivity gains, and data-driven insights. Other notable mention is www.harvey.ai is well funded startup but they are struggling with the rolling out of the product while we're on the roll.
Advantages or differentiators
Our AI transforms legal research and analysis by automating manual workflows. Key differentiators are our knowledge graph architecture ingesting vast legal databases, proprietary input translator converting text to conceptual graphs, and fuzzy logic engine enabling reliable reasoning. By synthesizing legal data into a structured format, we enable targeted querying and links between case facts, applicable laws, and precedents. This results in 50%+ efficiency gains over traditional manual methods while also providing predictive insights not humanly possible. Unlike competitors, our solution is end-to-end - from ingesting case documents to predicting outcomes. We increase productivity 10x for lawyers through automation. No more slogging through textbooks or guessing winning strategies. LegaWrite enhances decisions with data-driven analytics. Our approach combines advanced AI with legal expertise to solve real workflow pain points. The time is now to bring legal services into the 21st century.
Finance
Revenue through 3 models - SaaS subscriptions, enterprise licensing, and professional services. Subscriptions priced per case analysis starting at $300. Enterprise licenses priced by number of users and use cases, starting at $500 per user per month. Professional services for configuration, integration, training priced from $5K to $60K. Costs primarily related to R&D and engineering to enhance AI technology. Legal data licensing fees around $10K annually. Cloud hosting, security measures, legal compliance also contribute to costs. As revenue grows with market adoption, costs expected to scale proportionately to support growth. Estimated gross margins around 75% owing to software/AI business model. Company currently pre-revenue focused on R&D and proving value proposition. Once beta launches net burn rate expected to decrease steadily as monetization initiates. Profitability projected by year 3-4 with sufficient capitalization. Significant operating leverage once revenue generation commences
Business model
SaaS subscriptions, enterprise licenses, and professional services provide revenue streams.
Money will be spent on
Majority of funding will solidify the AI technology through improvements to the knowledge graph, input translator, and fuzzy logic engine. A law professor will extensively test the system to identify any gaps in reasoning capabilities. Engineers will then integrate this feedback by refining the algorithms and logic to ensure outputs align with legal experts. Additional budget will be used for acquiring more legal data, cloud infrastructure, security measures, and basic operational costs. However, the primary focus is leveraging legal expertise to train, validate, and refine our core natural language processing and analytical engines. This will enable the construction of an robust prototype ready for real-world usage. The technical product - our AI and knowledge graph architecture - forms the foundational innovation. We will prudently direct capital to optimize this technology with real-world testing and iteration.
Offer for investor
We are providing a 15% incentive in the form of either KISS or SAFE vehicles, depending upon the investor's preference. Negotiable terms are available, with the aim to reach a fair agreement.
Being on the cutting-edge of AI comes with risks. The ambiguity inherent to legal reasoning could demand more tuning than anticipated. We are committed to extensive feedback loops with legal experts to continuously train the system. There are also data quality risks in constructing the knowledge graph. We are implementing robust validation methods and exploring crowdsourced data review. The reasoning engine may initially face limitations in handling edge cases. Our proprietary fuzzy logic is designed to act prudently, deferring unclear situations to human experts. We view these challenges as opportunities to refine our technology into a robust solution ready for the rigors of real-world usage. With diligent data governance, expert collaboration, and our sophisticated core AI, we are confident any risks can be properly addressed. Our team believes strongly in taking measured technical risks, as pioneering innovation requires it.
Incubation/Acceleration programs accomplishment
Product Development Achievements: We have initiated the crafting of a sophisticated customer-facing UI, a collaborative effort undertaken by our proficient design team. This step marks a crucial milestone in enhancing user experience and engagement.
Market Validation Milestones: We are excited to announce that we have secured commitments from an additional 14 law firms, poised to become paying customers upon the beta product's launch. This development stands testament to the growing market validation and the anticipation surrounding our product launch.
Investment Relations Progress: Our journey towards securing substantial financial backing is gathering momentum. Currently, we are engaged in fruitful discussions with several funds, having received a Letter of Intent (LOI) from a seed fund, and fostering a deep-rooted relationship with a potential Series A lead investor. This progression augments our financial stability and growth trajectory.
Network Building Accomplishments: Our network expansion has seen significant success with the inclusion of vital advisory board members, some of whom are prospective candidates for executive roles in the near future. Furthermore, we have engaged two partner-level attorneys who are actively involved in product testing, cementing our credibility and industry connections.
Business Skills Acquisition Progress: In a move to strengthen our business acumen and strategy, we are bringing on board a Sales Director, a significant addition that promises to catalyze our market penetration and customer acquisition efforts.
Partnerships and Collaborations Achievements: We have forged a strategic alliance with one of the top three technology consulting firms, a collaboration that paves the way for co-production and distribution synergies for our product. This partnership harbors the potential to blossom into a lucrative joint venture with a prominent brand, broadening our market reach and influence.
Awards and Recognitions: In a proud moment that underscores our product's innovative edge, we clinched the second place in a prestigious AI hackathon. This accolade reflects our commitment to excellence and innovation in the technology landscape.
Won the competition and other awards
In a proud moment that underscores our product's innovative edge, we clinched the second place in a prestigious AI hackathon at IBM. This accolade reflects our commitment to excellence and innovation in the technology landscape.