AI legal text summarizer for compliance clarity

Legislation is constantly evolving, and at Enhesa, we monitor regulatory changes across more than 400 jurisdictions, supported by over 160 in-house legal experts fluent in 34 languages. We keep our clients informed of the most critical changes, but the sheer volume of information can often feel overwhelming.

Adding to the challenge is the dense and technical language of legal text, particularly in Environmental, Health, and Safety (EHS) legislation. Understanding whether a certain chemical is now allowed in a jurisdiction for use in a product requires not only legal knowledge but also familiarity with the technical context. Similarly, new environmental regulations can have phased compliance schedules, requiring companies to meet specific targets over multiple years. Tracking these implementation deadlines manually requires extensive legal review to determine which obligations apply at each stage.

Translating technical legislation into simple, actionable insights carries the risk of misinterpretation or overlooking critical details. Ensuring accuracy in this process is essential, and it requires both advanced subject matter expertise and meticulous attention to detail.

The pace of regulatory change and the volume of information make it very hard for teams to manage the summarization process manually without significant resource constraint, creating a pressing demand for tools that streamline and support the process without sacrificing precision.

The good news is that solutions exist. By combining decades of regulatory data with the expertise of regulatory experts, our AI-powered summarizer tool significantly reduces the complexity and burden of summarizing legislation. This ensures our clients stay ahead of regulatory changes and remain compliant with confidence.

With the summarization processed automated, we ensure no detail is overlooked. However, AI doesn’t replace human expertise — it enhances it. Legal experts remain essential for interpreting nuances, assessing contextual relevance, and making judgment calls that AI alone cannot. This synergy allows them to assess new regulations, saving valuable time that can be allocated to other high-priority tasks — even before diving into detail reporting, which can then be approached with greater focus and efficiency.

To fully understand how our tool tackles these challenges, let’s delve into the technical features and capabilities to make accurate and efficient legislative summarization possible.

Read on to learn more from Enhesa AI technology experts Ana Sofia Rolim, Andrea Pennisi, and Rennan Valadares.

Text summarization: An overview

Text summarization is an important task of Natural Language Processing (NLP). It plays a critical role in making information more accessible and actionable in fields ranging from news aggregation to legal analysis and scientific research. Summarization methodologies can be categorized into extractive (e.g. BERTSUM) and abstractive (e.g. BART) approaches. Both methodologies have their own successes, benefits, and limitations.

Extractive summarization

Extractive summarization identifies and extracts the most relevant sentences or phrases from a document, maintaining their original structure and wording.

Extractive methodologies struggle to analyze a long text document due to their token limit (typically 512 tokens, a token is the smallest unit of text that the model can understand and process). So, they’re prone to sentence-level truncations (shortening a sentence by cutting off words or phrases to respect the limit of 512 tokens) making them unsuitable for processing lengthy text effectively.

Abstractive summarization

Abstractive summarization generates entirely new sentences, paraphrasing and restructuring the information to produce summaries that more closely resemble how a human might write. Abstractive models can produce hallucinated (when a method produces text that is factually and grammarly incorrect or the response is not correlated to the prompt) or inaccurate details because the training of such methodologies heavily depends on the quality and diversity of the datasets.

Both methodologies require extensive fine-tuning for specific domains, limiting their adaptability and scalability in diverse applications.

Large Language Models (LLMs)

The introduction of LLMs like GPT-4 addressed the limitations of the previous methods. Unlike traditional summarization models, LLMs can understand and generate human-like answers and handle nuanced tasks like summarizing legal, scientific, or technical content while maintaining accuracy and coherence. They’re pre-trained on vast, diverse datasets, enabling them to process and summarize long documents without significant truncation or loss of context. This eliminates the need for extensive fine-tuning on specific domains. LLMs can also understand specific instructions or examples provided during inference, further enhancing their versatility in many applications.

However, LLMs are not without challenges. Their significant computational requirements and susceptibility to generating verbose or overly generic summaries remain areas for improvement. Nonetheless, their ability to outperform traditional methods in scalability, adaptability, and performance make them suitable for our use case.

Introducing SUM-IT: Enhesa’s AI-powered summarization tool

Keeping up with evolving regulations is no small task. With new legal text constantly being published across multiple jurisdictions, manually summarizing them is time-consuming and resource intensive. That’s why we built SUM-IT — an AI-powered assistant designed to help Enhesa consultants process regulatory updates faster and more efficiently.

At Enhesa, 65 consultants produced nearly 15,000 legal summaries in 2024 — a testament to the sheer scale and complexity of global regulatory monitoring. Given this workload, automation is essential. SUM-IT automates the “first-pass” summarization process, ensuring that legal experts receive structured, standardized summaries that adhere to Enhesa’s strict formatting requirements. By combining advanced AI capabilities with human oversight, SUM-IT helps consultants navigate complex legal text with greater speed and accuracy. Instead of spending hours reading dense regulations, our experts receive an AI-generated draft that already highlights key obligations, compliance deadlines, and regulatory changes — allowing them to focus on refining insights rather than formatting content.

How SUM-IT works behind the scenes

SUM-IT does more than just condensing text. It understands, structures, and organizes legal content to ensure every summary is clear, actionable, and aligned with Enhesa’s compliance standards.

Here’s a breakdown of the process it follows…

1. Processing the input

SUM-IT is built to process legal information in multiple formats, whether it comes from PDFs, legal websites, or raw text. Instead of manually extracting key information from lengthy documents, consultants can put the content into SUM-IT for automated processing.

For regulations published online, consultants simply copy and paste the link into SUM-IT, which then extracts, cleans, and structures the text. The system removes irrelevant elements like headers, footnotes, and formatting artifacts, ensuring only the legally relevant sections are processed for summarization.

2. Breaking down complex legal text

A legal document often comprises longer texts and contains multiple sections, clauses, and references. Summarizing everything at once could compromise quality, leading to overlooked details or lack of clarity.

To ensure accuracy, SUM-IT breaks down documents into concise pieces before processing. It also categorizes obligations by:

• Who’s affected
• What actions are required
• When compliance is needed

This provides structured, consistent, and actionable summaries.

3. LLM-powered summarization with Enhesa’s formatting standards

Consistency is key when summarizing legal text. With regulations varying across jurisdictions and industries, every summarized text must follow a structured, standardized format to ensure clarity and compliance. Without a uniform approach, summaries could become inconsistent, making it harder for consultants and businesses to quickly interpret and act on regulatory changes.

To eliminate these challenges, SUM-IT applies state-of-the-art LLMs to compile the right information, while strictly adhering to Enhesa’s formatting standards. This ensures that every text summary is concise, actionable, and aligned with our compliance reporting requirements, reducing manual effort and maintaining a high level of precision.

Once the text is structured, SUM-IT generates summaries with a high level of accuracy and consistency. Unlike generic AI tools, it’s specifically optimized to identify and extract obligations, clearly outlining whether companies need to act. It also highlights compliance deadlines, ensuring businesses are aware of when new regulations take effect.

SUM-IT follows Enhesa’s structured format, producing summaries that are well-organized and ready for consultant review. By adhering to Enhesa’s predefined reporting standards, SUM-IT eliminates inconsistencies and significantly reduces the need for consultants to manually reformat AI-generated content.

 

Example of how SUM-IT extracts and structures information

Human expertise still matters

While AI accelerates the process, human expertise is still crucial. SUM-IT generates a structured first-pass draft, but Enhesa consultants thoroughly review and refine each summary to ensure no critical legal details are overlooked. The final output must be accurate, actionable, and aligned with Enhesa’s compliance standards — something that cannot be achieved by AI alone.

Despite the rapid advancements in AI, an AI-only solution would be rife with errors, misinterpretations, and omissions — challenges that are unacceptable in a field like law, where precision is non-negotiable. Legal texts are complex, nuanced, and often ambiguous. AI models, no matter how sophisticated, struggle with distinguishing between legally binding provisions and advisory guidelines, interpreting conditional clauses, or identifying subtle variations in enforcement across jurisdictions.

For example, new regulations frequently come with phased compliance schedules, requiring companies to meet different obligations at multiple enforcement dates. An AI-only solution might misinterpret these deadlines and mistakenly consolidate them into a single requirement, or fail to recognize the sequence of compliance steps. Similarly, AI might overlook jurisdictional variations in legal language, treating regional interpretations as universally applicable, leading to incorrect conclusions that could put businesses at risk.

At Enhesa, we recognize these risks, which is why SUM-IT is designed to complement, not replace, legal expertise. Our AI-powered tool ensures efficiency, but our consultants provide the essential legal judgment, contextual understanding, and meticulous validation that AI cannot replicate. This combination of automation and human oversight allows us to deliver summaries that are not just faster, but also consistently accurate, reliable, and legally sound.

Ultimately, the goal of SUM-IT is not to replace human experts but to empower them — reducing the burden of manual summarization while ensuring that every regulatory update is assessed with the highest level of precision and care.

Responsible AI: Privacy, ethics, and sustainability

At Enhesa, we’re committed to developing AI solutions that not only enhance efficiency but also uphold the highest standards of privacy, ethics, and sustainability. Unlike some AI applications that rely on vast amounts of customer data, SUM-IT is designed with a fundamentally different approach — one that doesn’t require or process confidential client information. Instead, our AI text summarization tool strictly focuses on legal texts, ensuring compliance with copyright laws while respecting jurisdictional intellectual property rights.

In an era where AI models are sometimes trained using questionable datasets, we take a principled stand: SUM-IT is built on transparent, legally obtained regulatory data. Our commitment to responsible AI means we avoid questionable data practices, ensuring our clients can trust that their compliance insights are generated ethically and securely.

The future of legal summarization with SUM-IT

In an ever-evolving regulatory landscape, efficiency, accuracy, and consistency are essential. SUM-IT empowers Enhesa consultants to process complex legal updates faster, extract key obligations with precision, and deliver structured summaries that align with our compliance standards. This means more consistent, swift, and reliable intelligence being delivered to our clients regularly.

By automating the most time-consuming aspects of legal summarization while preserving expert oversight, SUM-IT enhances productivity without compromising the quality of analysis.

Enhesa consultants can stay ahead of regulatory changes with greater efficiency and confidence, which means our customers can do the same. By blending AI-powered automation with human validation, we ensure compliance remains structured, concise, and actionable — no matter how complex the legal landscape gets.