How to Buy (or Not Buy) Legal Tech Whitepaper

Legal tech solutions are essential to powering well-performing legal teams; finding the right partner can often feel like an uphill battle. Choosing the wrong vendor drains resources and creates costly disruptions to daily operations.

Alignment with internal teams is crucial when exploring legal technology purchases. Scalability and the potential to foster long-term vendor partnerships also have immense benefits that last long past signing your SOW.

Navigating the buying process is not always easy. This whitepaper gives you tools, questions to ask, and best practices to:

  • Keep your firm or departments flexible, both cost and tech-wise.
  • Create mutually beneficial partnerships.
  • Support larger organizational initiatives.
  • Measure success.
  • Adapt to industry changes.
  • Ensure your team has the support resources needed.

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Making Business Moves That Matter: How Contract Management Enables Business Growth

In today’s fast-paced world, efficient contract lifecycle management (CLM) is crucial for growth and operational success. However, many organizations hesitate to implement CLM solutions, often worrying about the time required, the learning curve, and whether the investment will pay off in the long run. These concerns can hold companies back from unlocking the significant benefits that CLM automation offers.

Docubee’s new white paper “Making Business Moves That Matter: How Contract Management Enables Business Growth” tackles these concerns directly. It shows how modern CLM tools have evolved to meet the diverse needs of today’s businesses, regardless of how unique or complex they might be.

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Docubee: A Better Way to Handle Legal Contracts

Cut down on non-billable hours without a painful software integration that requires lengthy retraining. Docubee intelligent contract automation gives you an all-in-one platform that fits your legal processes, not the other way around.

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The Current State of Contract Automation for Legal Professionals

Among the most avoided conversations for legal professionals is that of technology and the role it plays in legal contract and document management. Due to the fear of complicated implementations or additional work getting added to the table, automation for law firms gets put as an afterthought.

Docubee partnered with leading Legal media company, ALM, to survey legal professionals across various practice areas to get a picture of the current state of contracts and technology used in firms and where the industry is headed.

This whitepaper looks to uncover common trends, address challenges and best practices, and glean insights on contract automation for law professionals.
Continue reading for vital info on automation for your firm.

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Role of Data Solutions for AI Deployment

Great AI products need to solve the data woes of enterprises reliably and consistently. Sudeep George, VP of Engineering at iMerit, deep dives into the importance of high-quality data in building effective machine learning models on the I M Possible podcast with Eddie Avil.

Watch iMerit’s VP of Engineering, Sudeep George, discuss:

  • How to ensure that data is high-quality
  • The role of ML DataOps and how it helps with AI model performance
  • How enterprises can accelerate their AI development and deployment
  • How AI can be made more accessible
  • Cutting-edge AI innovation & its social impact

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Vision-Language-Action Model For Autonomous Mobility

To support a cutting-edge demo in autonomous mobility, a leading AI company partnered with iMerit to power its Vision-Language-Action (VLM) model with high-quality, expertly curated training data. iMerit’s team of domain specialists rapidly annotated real and synthetic driving scenarios, improving model accuracy, explainability, and safety—while delivering a 50% boost in task efficiency.

This case study highlights how iMerit’s tailored data annotation and VLM expertise enabled the client to surpass demo goals, enhance model transparency, and accelerate innovation in autonomous vehicle technology.

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Improving Retrieval-Augmented Generation For Healthcare Chatbot

To ensure accurate and safe generative outputs from its healthcare chatbot, a leading U.S. tech company partnered with iMerit to evaluate and refine a new medical dataset using Retrieval-Augmented Generation (RAG). Leveraging a team of nurses and a board-certified physician, iMerit developed a scalable, expert-driven workflow to audit medical definitions for accuracy, safety, and usefulness—achieving 99% consensus and over 72% in project cost savings.

This case study highlights how iMerit's domain-specific RLHF and human-in-the-loop evaluation helped the client reduce risk, improve quality, and scale responsibly in a high-stakes healthcare environment.

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RLHF For AI Co-Pilot

A leading professional social networking platform partnered with iMerit to enhance its AI-powered co-pilot through Reinforcement Learning from Human Feedback (RLHF). The goal was to ensure that the co-pilot delivers accurate, coherent, and responsible responses tailored to users' job-related queries. iMerit provided expert annotation and response evaluation services, helping align the assistant’s output with the platform’s values and professional tone.

By leveraging a skilled team and customizable tools, iMerit improved the assistant’s conversational quality, boosted user satisfaction, and upheld ethical standards. The collaboration led to measurable gains in responsiveness, relevance, and user engagement—making the AI co-pilot a more effective and trusted digital assistant.

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Leveraging Consensus Logic and Escalations to Improve RLHF

In the evolving world of AI development, ensuring alignment between machine behavior and human intent is critical. This blog explores how consensus logic and escalation workflows can significantly enhance the effectiveness of Reinforcement Learning from Human Feedback (RLHF). By aggregating multiple human judgments and escalating ambiguous cases to expert reviewers, these strategies reduce bias, increase reliability, and improve the overall trustworthiness of AI systems.

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Unlocking the Potential of In-cabin Solutions: Emerging Use Cases & Evolving Data Needs

As vehicles advance toward autonomy, in-cabin monitoring systems are becoming essential for enhancing safety, comfort, and compliance. These AI-driven systems track driver alertness, passenger behaviour, and environmental factors—transforming the driving experience and meeting growing regulatory demands. With the market projected to soar past $3.2B by 2031, the need for smart, reliable monitoring has never been greater.

iMerit supports this evolution with high-quality data annotation via its Ango Hub platform, combining predictive AI with expert oversight. This ensures automotive companies can train accurate, bias-free models for use cases ranging from driver fatigue detection to child safety—driving innovation in next-generation vehicle intelligence.

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Generative AI Chatbots in Healthcare

Generative AI chatbots are reshaping the healthcare industry by streamlining operations, enhancing patient care, and offering round-the-clock support. From symptom checking and appointment scheduling to chronic disease management and mental health assistance, these AI-powered assistants provide scalable, accessible solutions for patients and professionals alike. As technology evolves, so does their potential—integrating with wearables, delivering personalised care, and supporting complex diagnoses with impressive accuracy.

Despite the promise, challenges like data privacy, regulatory compliance, and the need for expertly annotated medical datasets remain. iMerit addresses these issues head-on with secure, HIPAA-compliant data solutions, expert-driven annotation services, and domain-specific reinforcement learning support. With its proven track record and deep expertise in healthcare AI, iMerit is empowering organisations to build accurate, ethical, and scalable AI chatbots that are shaping the future of patient-centred care.

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