MiAi Law

Big Law Solutions
for All

Law Decoded

Pioneering a new era in AI-driven Legal Research.

An unparalleled leap in legal research with data transparency, a human-like expertly reasoned answer with 95% precision and up to 99.99995% database retrieval success at lightning speed.

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Legal AI Research Partner

At MiAi Law, we believe in the power of precise and efficient research. We bring complex legal issues back to first principles, simplifying the way users navigate through the intricate web of laws and regulations.

Our innovative product is an expert system designed to provide answers faster than any human can read, enabling users to access information at lightning speed.

Introducing Agentic Research AI, MiAi Law has inbuilt robots that are equipped with the ability to independently conduct searches across curated legal websites while you are researching your legal issues on our database. Subscribers to our total solution will be able to conduct their entire practice through the MiAi Law user interface.

MiAi Law is at the forefront of innovation, offering solutions that go beyond the ordinary. We are committed to empowering legal professionals and individuals alike with the tools they need to succeed in a fast-paced and dynamic legal environment.

Join us on this exciting journey as we reshape the future of legal technology with MiAi Law. Experience the difference that innovation and intelligence can make in your legal practice.

Pin point references

Each response produced by MiAi Law includes inline citations that are hyperlinked to their pinpoint references. You will also be able to download these source documents.

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Pose intricate queries across your documents comfortable in the knowledge that your data will be encrypted and protected. No other user will be able to access your data without your permission.

Research

Receive responses to detailed research questions spanning Australian Law. All responses are based on original source material with hyperlinks to pinpoint references.

  • Australian Law
  • Agentic AI
  • UK Law
  • Research Memos
  • US Law
  • Court documents

Our Commitment

Providing safe, secure, and trustworthy legal solutions in accordance with Australia’s privacy regulations. Our commitment is to ensure that we provide high trust research outputs that align with Australia’s privacy laws.

Trusted Advisors
Build and maintain the confidence of clients and stakeholders.

Legal Assurance
Reduce the risk of legal issues and regulatory penalties.

Reputation
Strengthen your organisation’s standing by adhering to best practices in legal compliance.

Governance

Safety:

  • We prioritise the protection of sensitive information
  • We implement rigorous security protocols to prevent data breaches
Security:
  • We use advanced encryption methods
  • We conduct regular security audits to ensure robust defenses

Compliance:

  • We adhere to Australia’s privacy laws and regulations
  • We ensure all practices and solutions meet legal standards

Trustworthiness & Security

We Encrypt Your Sensitive Information

  • Complete High Trust Legal Solutions Tailored to Meet the Unique Needs of the Legal Industry
  • Trust our legal research outcomes
  • Reliable Primary Source Materials

Founder’s Vision

Laina Chan, Founder and CEO, discusses the genesis of Miai Law Pty Ltd and its mission to revolutionise legal research with cutting-edge AI technology.

FAQ

Generative AI or GenAI are both short for generative artificial intelligence. These are software systems that create content as text, images, music, audio and videos based on a user’s ‘prompts’.

An expert system is an AI system that encapsulates knowledge provided by a human expert in a specific domain to infer solutions to problems.

An expert system consists of a knowledge base, an inference engine and a user interface. the knowledge base stores declarative knowledge of a specific domain, which encompasses both factual and heuristic information. the inference engine holds procedural knowledge: the set of rules and the methodology for reasoning. It combines facts provided by the user with information from the knowledge base.

Inference is done using predefined rules according to the expert and with logical statement evaluations. Classes of problems that can be solved using expert systems include classification, diagnosis, monitoring and prediction.

Trustworthiness refers to characteristics which help users understand whether the AI system meets their expectations. These characteristics can help users verify that:
  • AI systems have been properly designed and validated in conformance with state-of-the art rules and standards. This implies quality and robustness assurance;
  • AI systems are built for the benefits of the users who have aligned objectives. This implies awareness of the workings of AI algorithms and an understanding of the overall functioning by users. It also implies qualification or certification assurance of AI development and operation in conformance with legal requirements and sectorial standards when available;
  • AI systems are provided with proper identification with responsible and accountable parties;
  • AI systems are developed and operated with consideration for appropriate regional concerns.

Hallucination refers to AI models making up facts to fit a prompt’s intent. When a large language model processes a prompt, it searches for statistically appropriate words, not necessarily the most accurate answer.

Transparency of AI systems supports human centred objectives for the system and is a topic of ongoing research and discussion. Providing tranparency about an AI system can involve communicating appropriate information about the system to stakeholders (eg goals, known limitations, definitions, design choices, asumptions, features, models, algorithms, training methods and quality assurance processes). Additionaly, transparency of an AI system can involve informing stakeholders about the details of data used (eg what, where, when, why data is collected and how it is used) to produce the system and the protection of personal data along with the purpose of the system and how it was built and deployed. Transparency can also include informing users about the processing and level of automation used to make related decisions.

An agentic AI agent is an advanced artificial intelligence system engineered to function with significant autonomy, meaning it can make decisions and perform actions independently without continuous human oversight. These systems are designed to be self-directed, allowing them to navigate and respond to their environment based on pre-defined goals and objectives.

A key characteristic of agentic AI agents is their goal-oriented nature. They are programmed to achieve specific outcomes, which can range from routine tasks like managing schedules and sending reminders to more intricate and dynamic problem-solving scenarios. For example, in customer service, an agentic AI might autonomously handle inquiries and resolve issues, while in more sophisticated applications, such as autonomous vehicles, the AI would make real-time decisions to navigate safely and efficiently.

By combining autonomy and goal-orientation, agentic AI agents are capable of performing complex tasks with minimal human intervention, adapting to new information and changing circumstances to fulfill their objectives effectively.

Reinforcement learning is the process of training an agent(s) interacting with its environment to achieve a predefined goal. In reinforcement learning, a machine learning agent(s) learns through an interactive process of trial and error. The goal of agent(s) is to find the strategy (ie build a model) for obtaining the best rewards from the environment. For each trial (successful or not), an indirect feedback is provided by the environment. The agent(s) then adjusts its behaviour (ie its model) based on this feedback.

Episodic memory is a type of long-term memory that involves the ability to recall specific events or experiences from the past. Episodic memory allows individuals to mentally travel back in time to relive past experiences. It is distinct from semantic memory, which involves general knowledge and facts not tied to personal experiences.

No, your data will not be used to train the AI. MiAi Law understands the importance of client privilege and your data will remain personal to you. It will be segregated from the data of other subscribers in your personal server.
If you chose to react to the answers by giving MiAi Law the thumbs up or thumbs down or by asking for more detailed or less detailed answers then these reactions will be used to tailor MiAi Law’s future answers to your questions.

Every concept in our answers is footnoted and hyperlinked to the pinpoint reference of each source document.

MiAi Law has developed its AI tool using best practices to address and mitigate several responsible AI risks. These risks include the potential for bias and discrimination, where AI could inadvertently perpetuate existing prejudices in critical areas such as hiring and law enforcement. To counter this, MiAi Law employs rigorous bias detection and mitigation strategies.

Privacy violations are another concern, as AI systems often require large amounts of sensitive data. MiAi Law ensures robust data protection measures, including but not limited to encryption, to safeguard against misuse and unauthorized access.

The lack of transparency, often referred to as the “black box” problem, is addressed through detailed footnoting of our answers and hyperlinks to the source materials to make our answers more understandable and trustworthy.

Security threats, including hacking and adversarial attacks, are mitigated through advanced cybersecurity protocols.

Ethical considerations are also paramount. MiAi Law has adopted ethical guidelines that balance innovation with moral responsibility. For example, in building our database, we have not only used open source data from government and court websites but also paid license fees to publishers where appropriate.

To ensure accountability, clear governance frameworks are in place. Environmental impacts are minimized through sustainable AI practices that reduce energy consumption.

Lastly, MiAi Law is committed to equitable AI practices that prevent the exacerbation of global inequalities, ensuring the benefits of AI are inclusively distributed. For example, we have created affordable consumer guides to educate the consumer and small businesses of their rights and obligations.

Yes we do. At the moment, opportunities are available at our Tokyo and Sydney offices.

We believe that collaboration and continuous interaction between colleagues leads to innovation. However, we are open to consider hybrid working on a case by case basis.