26 February 2025
Introduction
Imagine searching for a crucial conversation in a sea of endless chat messages—messages filled with greetings, status updates, and casual banter. The reality of modern enterprise communication is an overwhelming flood of fragmented, highly unstructured data. Compliance teams, legal departments, and security professionals are challenged to sift through this digital noise to find what truly matters. Traditional eDiscovery tools attempt to tackle this challenge but often fall short, applying AI to entire 24-hour chat transcripts without distinguishing between valuable discussions and meaningless chatter.
This approach results in massive amounts of unnecessary data processing, increased review time, and skyrocketing costs. Gen AI offers a smarter alternative—analyzing and refining conversations in real time to cut through the noise, highlight key discussions, and significantly reduce eDiscovery expenses.
Drowning in digital chatter: the rising challenge of managing chat data
The rise of workplace communication tools has changed corporate interactions from email-based to real-time messaging.
A 2022 study by Spiceworks Ziff Davis reveals that 51% of end users prefer real-time business chat apps (e.g., Slack, Microsoft Teams) over email for internal communications.In fact, short message data is on track to surpass email as the dominant source of communication in the near future.
Unlike emails, chat messages are frequent, short, and informal, creating massive volumes of fragmented data. Regulatory bodies increasingly demand full audit trails of corporate communications, making it imperative for legal teams to efficiently review conversations for litigation, investigations, and compliance violations. Security teams are also concerned about internal sensitive data exposure when handling eDiscovery requests.
Traditional eDiscovery falls short because emails and documents are structured, whereas chat data is highly unstructured and redundant.
Applying AI post-facto to massive chat transcripts is expensive and inefficient, and companies end up paying for processing and reviewing vast amounts of irrelevant data.
Is your eDiscovery tool wasting time and money on useless chat data?
Most eDiscovery tools handle chat data the same way they process emails—by analyzing entire 24-hour channel data rather than identifying meaningful conversations. This leads to significant inefficiencies, as a large portion of chat data consists of routine greetings, status updates, bot messages, and casual discussions.
When AI processes entire transcripts indiscriminately, organizations face higher storage and processing costs, prolonged review times, and increased legal exposure.
The hidden costs of traditional eDiscovery tools extend beyond direct expenses. The need to store and process vast amounts of unnecessary (chat) data results in inflated cloud computing costs. Even when AI is involved, legal teams must manually sift through large volumes of irrelevant information, slowing down the review process. Additionally, sending full chat transcripts to third-party eDiscovery providers increases the risk of data breaches and compliance violations.
That said, before selecting or continuing with an eDiscovery solution, organizations should evaluate whether their current tool is effectively meeting their needs. The following ten questions can help determine if an upgrade is necessary:
If the answer to all 10 questions is “no”, it may be time to consider an AI-powered eDiscovery solution that offers smarter data filtering, reduced costs, improved compliance, and greater efficiency.
How Gen AI tools will change the game for chat data
What is Gen AI?
Generative AI (Gen AI) refers to a type of artificial intelligence that can create new content, including text, images, audio, video, and even code, by learning from vast amounts of existing data. While generative AI is primarily designed to create new content, its capabilities can also be leveraged for complex classification tasks, such as assessing relevance.
Moving beyond linear review
Traditional eDiscovery tools process entire chat logs as if they were email threads, failing to differentiate between key discussions and irrelevant messages. This results in excessive noise, forcing legal teams to sift through routine greetings, scheduling updates, and fragmented conversations.
Gen AI changes this approach by identifying meaningful discussions rather than analyzing full transcripts indiscriminately. It recognizes patterns, understands context, and groups related messages into coherent threads, ensuring that conversations are reviewed in their true context, not as isolated snippets.
Filtering out the noise
One of the biggest challenges in chat eDiscovery is filtering legally significant messages from the flood of daily workplace chatter. Traditional keyword-based searches often pull in vast amounts of irrelevant data, making manual review inefficient and costly.
Gen AI automates intelligent filtering, distinguishing between routine small talk and important discussions. It elevates messages based on case relevance using strong semantic capabilities, helping legal teams focus on what truly matters while minimizing wasted time and effort.
Reducing eDiscovery costs
Processing unstructured chat data is expensive, especially when entire channels are stored and analyzed without filtering. Retaining and reviewing unnecessary chat logs drives up storage costs, AI processing expenses, and legal review hours.
Gen AI optimizes cost efficiency by reducing data volume before review. By filtering out unnecessary content at the outset, organizations can save on storage, processing, and manual review costs, making eDiscovery more sustainable and cost-effective.
Uncovering hidden meaning with sentiment and behavioral analysis
Keyword searches alone often fail to capture intent, tone, and context, making it difficult to detect compliance risks in informal chat conversations. Employees frequently use abbreviations, emojis, or coded language, which traditional tools struggle to interpret.
Gen AI goes beyond keyword matching, leveraging strong semantic capabilities to detect nuanced language patterns, contextual relevance, and potential indicators of misconduct. By offering deeper insights into communication behavior, it helps legal teams identify risks proactively rather than reactively.
Seamless integration with modern chat platforms
Many legacy eDiscovery tools struggle to integrate with platforms like Slack, Microsoft Teams, and Zoom, leading to time-consuming and manual data extraction.
Many legacy eDiscovery tools struggle to integrate with platforms like Slack, Microsoft Teams, and Zoom, leading to time-consuming and manual data extraction. Hanzo goes beyond simple Gen AI applications by using optimized clustering methods to structure chat data before AI processing.
Instead of analyzing isolated messages that lack context or full 24-hour transcripts that dilute meaning, Hanzo groups related conversations to strike the right balance of message relevance and context. This ensures that Gen AI is applied efficiently, capturing, analyzing, and reviewing chat data dynamically—reducing delays and improving compliance with regulatory requirements.
Spotlight AI: the future of eDiscovery
The future of eDiscovery is here—powered by precision, efficiency, and automation. As enterprises grapple with an explosion of chat data and unstructured content, traditional review methods can no longer keep pace. Generative AI (Gen AI) is transforming eDiscovery, enabling legal teams to move beyond slow, manual processes and embrace real-time, intelligent filtering to surface the most critical information with unprecedented speed and accuracy.
Introducing Spotlight AI: Hanzo’s award-winning legal AI tool
Designed to redefine eDiscovery, Spotlight AI leverages cutting-edge language models to analyze, prioritize, and extract the most relevant messages, emails, and files—allowing legal teams to focus only on what truly matters. By eliminating data noise and reducing manual review time from weeks to hours, Spotlight AI unlocks new levels of productivity while cutting costs.
How Spotlight AI works
Built for transparency and user-driven control, Spotlight AI follows a simple yet powerful workflow:
- Smart case definition – Users may provide case descriptions from complaints, subpoenas, etc., enabling the AI to generate highly targeted, legal-focused queries.
- Optimized conversation clustering – Before AI analysis begins, the system intelligently groups related messages and conversations to provide the optimal level of context. This ensures that relevancy assessments are more precise, reducing noise from scattered or disconnected messages.
- AI-powered analysis – The system scans vast datasets in real time, automatically identifying, tagging, and prioritizing relevant content—from key conversations in chat logs to crucial evidence buried in documents.
- Transparent decision-making – Unlike “black-box” AI models, Spotlight AI provides full transparency throughout the workflow, including the questions being asked of the dataset and clear explanations for its selections, ensuring trust, accuracy, and auditability.
Why legal teams choose Spotlight AI
- Smarter, faster eDiscovery – Spotlight AI enables legal teams to quickly filter out irrelevant data and focus on critical evidence with AI-driven precision.
- Hybrid workflow approach for enhanced precision – By combining AI-driven tagging with traditional keyword searching, Spotlight AI allows legal teams to elevate the most relevant data to the top of the review stack. This approach follows a structured process:
- After Spotlight AI runs its initial analysis, chat data is automatically tagged based on legal relevance, identifying key conversations that may require further review.
- Users can apply traditional keyword searches within the tagged dataset to refine the results further, ensuring that the most important content is surfaced.
- The most relevant content, identified through both AI tagging and keyword refinement, can then be reviewed in Illuminate or optionally exported to a dedicated review platform for first-pass analysis.
- Seamless integration with enterprise platforms – Spotlight AI works effortlessly with collaboration tools such as Slack, Microsoft Teams, and Zoom while maintaining full compliance with GDPR, CCPA, and other data privacy regulations.
- Increased efficiency and cost savings – By significantly reducing the need for manual review, Spotlight AI helps legal teams save time, resources, and storage costs, leading to a more efficient eDiscovery process.
- Built-in security and data governance – Developed with IBM Watsonx security protocols, Spotlight AI ensures end-to-end encryption, in-tenant AI processing, and strict data governance measures to protect sensitive information throughout the eDiscovery process.
In an era where data is both an asset and a challenge, Spotlight AI empowers legal teams to make informed decisions faster, smarter, and with greater confidence.
Ready to see Spotlight AI in action?
Discover how Hanzo’s next-gen legal AI tool can revolutionize your eDiscovery process. Visit the product page or book a quick 20-minute demo with our eDiscovery expert today.