Why Your eDiscovery Provider Needs a Thoughtful TAR Protocol and a Thorough Understanding of Generative AI
When you choose an eDiscovery partner, don’t settle for one who simply “uses AI.” The real differentiator comes from how thoughtfully the provider designs and executes a thoughtful and flexible Technology Assisted Review (TAR) approach. Leveraging continuous active learning (CAL) and Generative AI allows all matters to benefit from the best of all available technology. A hybrid approach helps balance speed, defensibility, and insight. Every matter requires its own strategy; a “one-size-fits-all” approach doesn’t work. Effective eDiscovery demands thoughtful collaboration and careful consideration to determine the best AI approach for each case.
A Defensible Approach to TAR
At Sandline, we begin every project with a matter kickoff call. During this conversation, we align with clients on data sources, specifications, workflows, timelines, and deadlines. Our analytics experts also consult on analytics strategies, including guiding clients on when and how to deploy various tools. We built our TAR protocol to be flexible and case specific. Each matter is individually assessed and consulted on. We leverage a tailored mix of structural analytics, conceptual analytics, and active learning tools to develop effective workflows. The basic workflow requires:
- Culling and Preparation – Remove incompatible files and normalize datasets for analysis.
- Richness Sampling – Estimate the proportion of relevant content to guide strategy.
- Iterative Training – Use custom workflows to refine models continuously.
- Validation & Quality Control – Apply elusion testing and QC checkpoints to ensure accuracy and defensibility.
This structured approach delivers efficiency and defensibility, giving clients confidence that review decisions will withstand scrutiny. Depending on the matter’s details, timelines, and requirements, we may use CAL for prioritization and QC alone or extend it for culling and statistical sampling. We may also deploy generative AI for classification and summarization to help review efficiencies and gain broader insights into the data set.
The Role of Generative AI
While TAR provides a proven, defensible framework for managing large datasets, generative AI opens new opportunities to accelerate insights and strengthen case team decision-making. At Sandline, we integrate generative AI tools into our workflows to:
- Classify and Summarize Documents – Cut reviewer time with context-rich overviews.
- Spot Emerging Themes Early – Help case teams identify issues sooner and adjust strategy proactively.
- Enhance Consistency – Support reviewers by aligning AI-driven predictions with case objectives.
We treat generative AI as a complementary layer, not a replacement for TAR. TAR ensures rigor and defensibility, while generative AI adds speed, flexibility, and strategic depth. Combined, they deliver results that are faster, more cost-effective, and fully defensible.
Why It Matters
Providers without a robust TAR protocol risk leaving your review process open to challenges. Providers who ignore generative AI miss opportunities for faster insights and efficiencies.
Sandline’s consultative, case-specific approach delivers the best of both worlds: a defensible TAR foundation combined with innovative generative AI enhancements through thoughtful prompt engineering and validation workflows.
When you work with Sandline, you gain efficiency and peace of mind, supported by expert guidance and a defensible AI protocol.