eDiscovery Agents
Government, legal, and compliance teams are managing growing discovery and investigative obligations, including larger custodian populations, tighter regulatory and court-ordered deadlines, and review budgets that don't scale with data volume. AI can accelerate that work without sacrificing transparency, auditability, or defensibility.
The Relevance Determination Agent and the Issue Coding Agent run on the same controlled model. Each agent is scoped to a defined review task and tested against a sample of the review population before it's trusted with the full corpus. Every decision is logged and explained, and nothing advances without human sign-off, making the review record defensible to regulators, courts, or oversight bodies.
The Relevance Determination Agent evaluates whether each document in the scoped population is relevant to your matter.
Agents cross-check their own outputs using a proprietary multi-model process. They then validate performance on a sample set to confirm that minimum recall and precision thresholds are met before your team can run them across the scoped population.
Every relevance decision includes the agent's rationale, and every action is logged for auditability. Your team signs off before the agents run across the scoped population.
Reviewers have visibility into time and cost savings achieved, along with the confidence score breakdown across the review population.
Knowing a document is responsive doesn't tell you what it proves. Issue coding is where review slows down: reviewers read the same documents twice, apply codes inconsistently, and the issue picture stays incomplete until the last batch is done. The Issue Coding Agent codes every responsive document against your matter's issue list, so your team starts building the case while review is still underway.
Together, the two agents move a review team from sorting documents to reasoning about the evidence.
The Issue Coding Agent evaluates every document against the legal, factual, or investigative issues that matter to your case and applies matter-specific codes, with human oversight built into every step.
Evaluate documents against defined legal, factual, or investigative issues.
Code documents for issues specific to your matter.
Review sample results to assess performance and accuracy.
Approve the agent’s progression to the full document set.
Use optional post-run quality control to calculate final recall and precision for each issue code.
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