Artificially Intelligent lawyer. (Ailawyer). AI Legal Assistant

Question Answering (QA) system. Ailawyer.

Question Answering (QA) system. Artificially Intelligent lawyer. Ailawyer. Artificial intelligence answers common legal questions. You can write a question in text or use the microphone recording function if your smartphone allows it. General topics, application forms, lawsuit, compensation for damages, drafting complaints, contracts, arbitration, appeals procedure, car accident law, criminal law, inheritance law, immovables. Artificial intelligence in law. Lawyer bot. Artificially-intelligent attorney. Neural network online. Machine learning.

Legal services for individuals:

Legal assistance of a lawyer.
Lawyer consulting.
Drafting pleadings and other legal documents.
Representation in courts of general jurisdiction.
Land law.
Housing law.
Inheritance law.
Consumer rights Protection.
Labor law.
Family law.
Pension law.
Compensation for damage caused by damage to health.
Establishment of legal facts.
Personal, family lawyer.
Enforcement proceedings.
Drawing up cassation, supervisory complaints.

Legal protection in case of an accident:

Appeal against the actions and decisions of the traffic police, traffic police.
Return of driver’s license.
Compensation for damage from an accident.
Resolving disputes with insurance companies.

Defense in criminal cases:

Protection at the stage of preliminary investigation.
Defense in the courts of the 1st instance, at the stage of appellate cassation and supervisory instance.
Drawing up appeals, cassation and supervisory complaints.
Representing the interests of victims at any stage of the criminal process.
Handling private prosecution cases.

Legal services for legal entities:

Registration of legal entities and individual entrepreneurs.
Lawyer consulting.
Representation in arbitration court.
Statement of claim to the arbitration court.
Arbitration law.
Subscriber service.
Transaction support.
Tax law.
Preparation of draft local regulations.
Preparation of draft contracts on all issues of the organization’s activities.
Challenging decisions of tax authorities in court.

The Immediate Prospects for the Development and Application of Artificial Intelligence and Neural Networks in Jurisprudence

The integration of Artificial Intelligence (AI) and neural networks into the legal field heralds a transformative era in jurisprudence. As these technologies evolve, their applications within law are expanding, offering both opportunities and challenges. This article explores the immediate prospects for the development and application of AI and neural networks in jurisprudence, emphasizing their potential to revolutionize legal research, contract analysis, litigation prediction, and beyond.
Legal Research and Document Analysis

One of the most immediate applications of AI in law is in legal research and document analysis. AI systems, powered by sophisticated algorithms and neural networks, can process and analyze vast quantities of legal documents at speeds unattainable by human researchers. These systems can identify relevant case law, statutes, and legal precedents, significantly reducing the time lawyers spend on legal research. Furthermore, AI can help in the analysis of contracts and other legal documents, identifying potential issues and suggesting revisions based on legal standards and precedents.
Predictive Analytics in Litigation

AI and neural networks are making strides in predictive analytics, offering lawyers insights into the potential outcomes of litigation. By analyzing historical data on court decisions, these systems can assess the likelihood of a case’s success, helping lawyers and clients make informed decisions about pursuing litigation. This capability not only aids in strategic planning but also in risk assessment, potentially saving clients time and resources.
Automating Routine Tasks

The automation of routine legal tasks is another area where AI is making an immediate impact. Tasks such as document review, due diligence, and even some aspects of legal drafting can be automated using AI technologies. This not only increases efficiency but also allows lawyers to focus on more complex and nuanced aspects of legal work. However, the adoption of such technologies must be carefully managed to address concerns about accuracy, privacy, and the potential displacement of legal jobs.
Ethical and Privacy Considerations

As AI and neural networks become more integrated into jurisprudence, ethical and privacy considerations come to the forefront. The use of AI in legal decision-making and the potential for bias in AI algorithms are significant concerns. Ensuring that AI systems are transparent, accountable, and free from biases is paramount. Moreover, protecting the privacy of sensitive legal information processed by AI systems is a critical challenge that must be addressed through robust data protection measures.
The Road Ahead

The immediate prospects for AI and neural networks in jurisprudence are promising, with potential benefits including increased efficiency, improved accuracy, and enhanced decision-making capabilities. However, the successful integration of these technologies into the legal field requires careful consideration of ethical, privacy, and regulatory issues. Continuous collaboration between technologists, legal professionals, and policymakers is essential to harness the benefits of AI in jurisprudence while mitigating its risks.

In conclusion, AI and neural networks are set to play a crucial role in the future of jurisprudence. Their ability to process information rapidly, predict outcomes, and automate routine tasks can significantly benefit the legal field. However, realizing these benefits while addressing the associated challenges will be key to the successful and ethical integration of AI technologies in law. As we move forward, the legal profession must adapt to these changes, ensuring that the application of AI in jurisprudence aligns with the principles of justice, fairness, and the rule of law.

As AI continues to infiltrate the legal landscape, both exciting benefits and substantial challenges are on the horizon. Here’s a breakdown of the key points:


    Enhanced Efficiency and Productivity: AI excels at automating tedious tasks like document review, legal research, and due diligence, freeing up lawyers’ time for complex analysis and client interaction.

    Improved Access to Justice: AI-powered chatbots and virtual assistants can provide basic legal information and guidance to underserved communities, potentially bridging the gap in legal access.

    Data-Driven Insights and Predictions: Machine learning algorithms can analyze vast amounts of legal data to uncover patterns and predict outcomes, aiding lawyers in case strategy and judges in sentencing decisions.

    Cost Reduction: Automating administrative tasks and streamlining processes with AI can lead to significant cost savings for law firms and clients.


    Bias and Discrimination: Algorithms trained on biased data can perpetuate discriminatory outcomes in legal proceedings. Mitigating bias requires careful data selection, algorithmic auditing, and diverse development teams.

    Transparency and Explainability: The «black box» nature of some AI models makes it difficult to understand how decisions are made, raising concerns about accountability and fairness. Explainable AI initiatives are crucial to address this.

    Job Displacement: Automating tasks with AI could lead to job losses in the legal sector, particularly for paralegals and legal assistants. Reskilling and upskilling initiatives will be necessary to manage this disruption.

    Data Privacy and Security: Integrating AI with legal systems necessitates robust data security measures to protect sensitive personal information. Strong privacy regulations and ethical data handling practices are vital.

    Ethical Considerations: Using AI in legal settings raises numerous ethical questions, such as the erosion of human judgment, the potential for manipulation, and the implications for legal professionals’ roles. Open discussions and ethical frameworks are needed to navigate these issues.


    There’s a potential for increased access to justice through affordable legal tech solutions.

    Regulation and oversight are needed to ensure responsible AI development and implementation in the legal sphere.

    Continuous education and training for legal professionals will be crucial to adapt to the changing landscape and effectively utilize AI tools.

The future of AI in law is a complex tapestry woven with exciting opportunities and significant challenges. Navigating this path requires a comprehensive approach that prioritizes ethical development, transparency, and human oversight to ensure that technology serves the best interests of justice and fairness.

Accompanying cases in the European Court of Human Rights.

The intellectual system of legal services includes:

  • Development of a question-answer system to automate the processing of customer requests.
  • Creation of a tool for generating legal documents such as contracts and lawsuits.
  • Development of a legal research assistance system that can automatically find and analyze lawsuits and laws.
  • Development of a legal compliance system that can automatically check documents for compliance with legal requirements.
  • Create a document collaboration interface that allows lawyers and clients to interact and discuss documents.
  • Development of a mobile application for access to legal information and services anytime and anywhere.
  • Integration with other systems such as court case databases or electronic file systems for efficiency and ease of use.
  • Development of a system for monitoring changes in legislation and notifying clients of important changes.
  • Using artificial intelligence and machine learning to analyze and predict trends in legal practice.
  • Development of a decision support system in court cases that can automatically generate arguments and evidence based on the analysis of existing legal literature.
  • Development of a system for automating the management of legal cases, which can track and update the status of cases, remind you of deadlines and automatically generate reports.
  • Development of a system for automating accounting and taxation, which can automatically generate and submit tax returns.
  • Development of an intelligent consulting system that can offer practical solutions for various legal situations.
  • Development of a system for generating audit reports and analyzing financial data from a legal point of view.
  • Development of a system for managing confidential information that can automatically classify and encrypt documents to ensure the security and confidentiality of information.
  • Integration with blockchain technology to provide secure and reliable audit and legal services.
Artificial intelligence in jurisprudence and legal practice

Artificial intelligence (AI) is rapidly changing the legal environment. AI-powered tools are used to automate tasks, improve efficiency, and provide new insights. Here are some of the benefits of using AI in the legal profession:

  • Increased efficiency. AI can automate many of the labor-intensive tasks typically performed by lawyers, such as document review and legal research. This can free up lawyers to focus on more complex and strategic work.
  • Increased Accuracy: AI can be used to identify patterns and trends in data that would be difficult or impossible for humans to see. This can help lawyers make more informed decisions and avoid costly mistakes.
  • New Ideas: AI can be used to generate new ideas on legal issues. This can help lawyers develop new strategies and arguments.
  • Cost reduction: AI can help lawyers cut costs by automating tasks and providing new ideas. This can make legal services more accessible to clients.

AI is still in its early stages of development, but it has the potential to revolutionize the legal profession. By automating tasks, increasing efficiency and providing new information, AI can help lawyers deliver better services to their clients at a lower cost.

Here are some specific examples of how AI is being used in law:

  • Viewing documents. AI-based tools can be used to view large volumes of documents quickly and accurately. This can save a lot of time for lawyers, who can then focus on more important tasks.
  • Legal Research: AI can be used to search and analyze large databases of legal information. This can help lawyers quickly and easily find relevant precedents and legislation.
  • Predictive Analytics: AI can be used to predict the outcome of court cases. This can help lawyers make a more informed decision about whether to take the case to court.
  • Negotiation: AI can help lawyers negotiate dispute resolution. This can help lawyers reach agreements that are fair to both parties.
  • Dispute Resolution: AI can be used to resolve disputes out of court. This can help lawyers save time and money.

These are just a few examples of how AI is being used in the law. As AI technology continues to evolve, we can expect even more innovative ways to use AI in the legal profession.

Here are some of the challenges of using AI in law:

  • Accuracy: AI is still in its early stages of development and is not always accurate. Lawyers must be careful when relying on AI-based tools and should always double-check results.
  • Bias: AI algorithms can be biased, which can lead to unfair results. Lawyers need to be aware of the potential for bias in AI-based tools, and they need to take steps to mitigate it.
  • Ethics: The use of AI in law raises a number of ethical issues. Lawyers should be aware of these concerns and take steps to address them.

Despite the challenges, the benefits of using AI in law are clear. AI has the potential to revolutionize the legal profession by making it more efficient, accurate and accessible. As AI technology continues to evolve, we can expect even more innovative ways to use AI in the legal profession.

Based on our evaluation of legal companies and offerings, current AI applications appear to fall into six main categories:

  • Due diligence  – due diligence is performed by bailiffs using AI tools to disclose background information. We decided to include contract verification, legal research, and e-discovery in this section.
  • Prediction Technology  . Artificial intelligence software generates results that predict the outcome of a trial.
  • Legal Analytics  . Lawyers can use data from past case law, win/loss ratios, and referee history to use to identify trends and patterns.
  • Document automation  . Law firms use software templates to create completed documents based on the data entered.
  • Intellectual property  . AI tools help lawyers analyze large IP portfolios and extract valuable insights from content.
  • Electronic Billing  — Billable lawyer hours are calculated automatically.
due diligence 

One of the main tasks that lawyers perform on behalf of their clients is to confirm facts and figures, as well as to carefully assess the legal situation. This due diligence process is necessary to reasonably advise clients on what options they have and what actions they should take.

While comprehensive due diligence can improve shareholder returns in the long run (according to a study by the City University of London), the process can also be very time consuming and tedious. Lawyers must conduct a comprehensive investigation for meaningful results. Thus, lawyers are also prone to errors and inaccuracies when conducting spot checks.

Kira Systems

Noah Weisberg, a former M&A lawyer who founded software development company Kira Systems, believes that due diligence errors by junior lawyers often occur for a number of reasons. These include working very late at night or on the eve of the weekend, forgetting to do due diligence before the end of the workweek, and not acting when the deal structure is being completely revised.

He adds: “Many employees are negative about the effectiveness of manual due diligence. Lawyers, being human beings, get tired and fussy, which backfires on extensive M&A due diligence.”

Kira Systems claims that its software is capable of more accurate verification of due diligence contracts by searching, highlighting, and extracting relevant content for analysis. Other team members who need to complete multiple content reviews can search the extracted information with links to the original source using the software. The company claims that its system can complete a task up to 40 percent faster on first use and up to 90 percent for those with more experience.


LEVERTON, a branch of the German Institute for Artificial Intelligence, also uses AI to extract relevant data, manage documents and draft leases in real estate transactions. The cloud tool is said to be able to read contracts at high speed in 20 languages.

In 2015, IT firm Atos sought help from real estate firm Colliers International, which used LEVERTON to conduct due diligence on a company it was about to acquire. Through the use of LEVERSON artificial intelligence, information such as payable rent, maintenance costs and expiration dates was extracted from thousands of documents and then collated into a spreadsheet.


However, lawyers can be burdened with reviewing multiple contracts and they may miss important changes that lead to legal problems later on. This is the same problem that Ned Gannon and Adam Nguyen, co-founders of eBrevia, faced when they were still junior lawyers. They formed a startup in partnership with Columbia University with the intention of cutting down on the document review process.

eBrevia claims to use natural language processing and machine learning to extract relevant textual data from legal contracts and other documents to help lawyers with analysis, due diligence, and lease abstraction. The lawyer will have to set up the type of information to be extracted from the scanned documents, and then the software will convert it into searchable text. The software summarizes the extracted documents into a report that can be shared and downloaded in various formats.

Here is a brief introduction to how eBrevia collects content and displays relevant information to users.

Another short demo presentation of the user interface was posted online by ABA magazine (however, the video was not accompanied by sound).

On its website, eBrevia claims it can analyze over 50 documents in less than a minute, which is 10 percent more accurate than a manual review process. The company also offers customized solutions by training its software to customize the specific requirements of firms that require thousands of documents to quickly review. Baker McKenzie deployed the software to 11 offices across Asia, Europe and North America in August 2017. However, the financial implications of this technical innovation for the law firm are still unknown, as the company has yet to publish its findings.


Other organizations, such as JPMorgan, tapped into artificial intelligence in June 2016 by developing their own legal technology tools. JP Morgan claims that their program called COIN (short for Contract Intelligence) extracts 150 attributes from 12,000 commercial loan agreements and contracts in just a few seconds.

According to the company , this is equivalent to 36,000 hours of legal work by its lawyers and loan officers . COIN was developed after the bank noticed an average of 12,000 new wholesale contracts per year with egregious errors.


Other players in the AI ​​industry include ThoughtRiver, which does contracts, portfolio reviews, and investigations to improve risk management. Its Fathom contextual interpretation engine was developed in collaboration with machine learning experts at the University of Cambridge.

The company says it has developed a product to automate summary reports for high-volume contract reviews. While users are reading excerpts from the content, they can also read the meanings of sentences provided by the AI. It is also reported that the system is able to automatically flag risky contracts. The company provides a brief overview of its product in the 3-minute video below, including a detailed overview of the user interface and the main features of the software:


LawGeex claims that its software verifies contracts if they comply with predefined policies. If they don’t meet the standards, the AI ​​makes suggestions for editing and approval. According to the company, this is achieved through a combination of machine learning, text analytics, statistical indicators and legal knowledge of lawyers.

How can lawyers use AI in law firms?

The legal industry is currently using AI in many aspects of their work. Artificial intelligence in law firms may be invisible, but it helps lawyers and paralegals do their jobs better. In particular, AI in law firms is helping lawyers transform their practice by putting clients first in an unprecedented way.

Here are just a few of the ways lawyers can take advantage of artificial intelligence in their firms:

Electronic opening.
The simplest and most common form of AI in law is electronic discovery: the process of scanning electronic information to obtain non-privileged information relevant to a case or lawsuit. Electronic discovery software allows lawyers to scan documents using search terms or specific parameters such as dates or geographic location. As a result, lawyers receive almost instant responses, much faster than scanning paper copies. This extra time allows lawyers to find more up-to-date information.

Legal research.
Similar to electronic search software, AI-powered legal research software allows lawyers to quickly scan and search large databases of regulations, statutes, practice areas, jurisdictions, case law and more. With legal research software, lawyers can collect data and help them understand case law. Conducting more comprehensive research at a faster rate saves lawyers time and saves clients money. Tools that integrate with practice management software, such as Casetext and Fastcase, allow users to conduct research and link it directly to relevant case details.

Learn more about how to conduct quality legal research.

Document management and automation.
While law firms continue to move away from paper documents, storing electronic documents has the same challenges as storing paper documents. Electronic records take up less physical space, but sorting and searching for documents is still difficult.

Using tagging and profiling features, AI-based document management software stores and organizes legal files, including contracts, case files, notes, emails, and more. This method of storing and organizing digital files, along with full-text search, makes documents varied and easier to find.

Document management solutions also allow you to use the document ID and check-in and check-out privileges for version control and security. In addition, document management software can connect to other systems such as Microsoft Office to easily share files with others.

Document automation helps law firms create documents using smart templates; legal professionals can auto-populate form fields directly from case records into templates, saving time and effort. Legal document automation provides a centralized and efficient process for preparing letters, agreements, motions, pleadings, invoices, invoices, and other legal documents.

Due diligence.
Conducting due diligence often requires lawyers to review a large number of documents, such as contracts. As with other document-related issues, AI can help lawyers review documents faster. An AI-based due diligence solution can retrieve certain documents required for due diligence, such as documents containing a specific item. AI due diligence software can also detect deviations or changes in documents. The best part? AI can view documents in seconds. While we recommend that human data verification continue, lawyers can benefit from a drastic reduction in the manual work of document verification.

Forensic analysis.
Determining the viability of a litigation or quantifying the cost of a lawsuit requires extensive analysis of precedent-setting cases. An AI lawyer can quickly review these cases and help lawyers draft more accurate and appropriate documents based on this data.

How can an AI lawyer be useful to the firm and the client?

The use of AI in law firms empowers lawyers to do their jobs. Overall, AI is helping to reduce time spent on manual tasks, freeing up more time for relationship building and customer-centric activities. Law firms can realize numerous benefits for both clients and profits:

Increase productivity.
Using AI to automate routine manual tasks helps improve the efficiency of the entire firm. AI-driven processes eliminate time-consuming and time-consuming activities to improve productivity, whether it’s searching for a contract, performing due diligence, or creating an invoice. As lawyers become more efficient, they can devote more time to their clients while increasing the time spent on paid work.

Improve access to justice.
Artificial intelligence and machine learning can reduce barriers to justice, most notably the high cost of accessing legal aid. By saving time on manual and routine legal work, lawyers can reduce estimates and costs for clients. For example, lawyers can pass these savings on to clients if a study that used to take 20 hours now takes two hours. In addition, lawyers can spend the time saved on tedious research helping more clients. While the legal industry has not yet fully realized these benefits of using AI, the potential is there.

Provide the best customer-centric experience.
The benefits of using AI in law firms boil down to one main benefit: Lawyers and attorneys have more time. With AI-powered tools that save time and labor, lawyers can spend more time directly with clients to develop meaningful relationships. Ideally, lawyers can go beyond simply helping clients solve their legal problems. Lawyers can get to know their clients better and truly understand how and why they need legal help with more free time.

By becoming a trusted consultant who takes the time to get to know your clients and provide efficient and timely service, your reputation will get ahead of you. By increasing customer trust in you, you will receive more referrals and better quality online reviews. This approach can ultimately lead to more clients and more revenue for your law firm.
Ethical aspects of the use of AI in law firms
Legal AI is part of a complex, rapidly evolving technology industry with new applications and discoveries emerging almost daily. We do not yet fully understand the full impact or potential use of such tools. And for a compliance-focused profession like law, that means taking a cautious approach is best.

Rules of the ABA model.
The first rule of the American Bar Association concerns «competence» and the duty of the attorney to provide «competent representation of the client.» In 2012, a commentary was added to the rule noting that the ability to practice law competently includes an understanding of the «benefits and risks associated with the relevant technology».

Are the benefits and risks of artificial intelligence, especially machine learning, understood enough to enable lawyers to use AI in their daily legal practice? For research and database queries, we have enough evidence to answer yes. But as legal AI and machine learning move into the realm of predictive analytics, we need to find more answers.

Implicit offset.
One of the biggest risks inherent in artificial intelligence and machine learning is implicit bias. Humans make machines, and no matter how hard we try to be objective, humans are inherently biased. There is evidence that facial recognition technology, for example, has difficulty accurately identifying females, blacks, and those aged 18 to 30. People blame the creators and early subjects of the technology for this discrepancy, since they were predominantly white males. Since law enforcement agencies make extensive use of such technologies to identify criminal suspects, the discrepancy is worrisome.

If similar biases were found in the tools lawyers use to predict the outcome of cases, it would be no less worrisome. We often see our current legal systems as biased. Since the data used by these systems is drawn from our current legal system, the danger of such biases in the predicted outcomes of our legal system seems all too real.

AI lawyer and legal liability.
The danger of bias is exacerbated by concerns about legal liability. If an AI-driven system produces a result that turns out to be incorrect or otherwise biased, who is responsible: the lawyer or the tool being used (and therefore the supplier of the tool being used)? For example, imagine if the accuser uses an AI solution, but the defender does not. If an AI-based solution helps the prosecutor win, is the lawyer liable because he did not use all available tools to competently defend his client? Conversely, if the lawyer’s artificial intelligence solution does not work, is the prosecutor responsible for using it?

We have yet to answer these and other questions. For now, these questions support the idea that AI lawyers have a long way to go before they start replacing lawyers.

What are some examples of the use of AI in the field of legislation or legal practice?

The biggest use case for AI today in legal practice is in electronic data discovery through machine learning. This method can result in significant savings in attorney time, which can be passed on to the client and ultimately consumers.

Every lawsuit requires the collection and consideration of evidence from the other side. This is called opening. Much of the evidence today consists of documents. When documents had to be created using handwriting, there were few of them, but with the help of copiers, then word and e-mail, the volume of documents increased exponentially.

Traditionally, a large defense law firm hired many new lawyers to do this. These lawyers will read documents from the lawsuit and receive $120,000 a year just to read the paper and mark relevant documents and sections. In a large lawsuit, there may be gigabytes of emails that need to be read. Their bosses would charge their clients $400 an hour to read documents, making a fortune. New lawyers burn out after a couple of years and move on to other, more interesting areas.

Verification will be required both for documents from the other party upon request, and for the provision of documents for transmission to the other party upon request.

Today, some firms are hiring a predictive coding company. The company has special software to which documents are connected. Documents are randomly assigned to a training set, which is given to the legal team for reading and marking. Instead of reading 100% of documents, a smaller percentage of documents can be read and flagged. The software company uses the tagged documents and identifies the patterns in the documents to find out what makes the corresponding document relevant. After the template is created, it reads the remainder of the documents, removes unnecessary parts and fragments, and presents the smaller, machine-labeled part for the supervisor to read.

Using a computer to read most documents can result in significant time savings. Theoretical studies should provide a possible time saving of 90%, but more realistically, a saving of 75%. For example, in the study below, a large lawsuit may contain 700,000 documents and require 5,600 hours to review, costing the attorney $280,000. With a computer available to assist, the review time is $20,000 per attorney and maintenance costs $50,000.

So far, this is not very common, because it takes more time to set up. In addition, its use may lead to lower profits for law firm partners who own law firms. The law firm industry is somewhat monopolistic and uses hourly rates, which is similar to the cost plus accrual model. Law firm clients are gradually pushing owners to adopt this technology, and some are even moving closer to a bonus invoicing model.