Custom AI agent · Legal & Compliance
AI e-Discovery Document Tagging Agent
Bring structure to document review with source-linked tags and defensible human checkpoints.
Organize discovery documents with source-linked relevance, privilege, confidentiality, and review tags while keeping legal decisions with humans.
- Group discovery documents by relevance, privilege, confidentiality, issue, custodian, and review status using configured rules.
- Reduce repetitive sorting while preserving the original source, tag rationale, and unresolved questions for reviewers.
- Create a consistent review queue that helps teams prioritize without treating an automated tag as a legal conclusion.
Starting at $300 USD/month
Starting price for a tailored solution. Scope, integrations, usage, hosting, and ongoing support are defined before work begins.
What is an AI e-discovery document tagging agent?
The AI e-Discovery Document Tagging Agent helps litigation and investigation teams organize large document sets for review. It applies a configured tagging scheme to authorized documents, records source and provenance, surfaces possible relevance or privilege signals, and routes uncertain items to reviewers who remain responsible for legal decisions.
Make document review more organized and traceable.
Configured review tags
Apply matter-specific labels for relevance, issue, custodian, privilege, confidentiality, responsiveness, and review status.
Provenance-preserving intake
Keep each tag connected to the source file, collection context, version, custodian or source, and review history.
Prioritized review queues
Surface possible responsive, privileged, duplicate, or uncertain documents according to configured triage rules.
Human correction and audit trail
Let reviewers confirm, change, or reject tags while preserving the reason, reviewer, timestamp, and unresolved exception.
Where it can help
Litigation document review
Organize collected files by matter, issue, custodian, relevance, and privilege before detailed review or production decisions.
Internal investigations
Create a controlled review queue for emails, files, messages, and reports while limiting access to authorized reviewers.
Regulatory and response projects
Tag records against requests, topics, time periods, and confidentiality rules with clear provenance and escalation.
How it works
A step-by-step workflow your team can review before launch.
1. Collect
Ingest authorized documents with matter, custodian, source, time-period, and access context.
2. Tag
Apply the configured taxonomy and identify possible duplicates, relevance signals, privilege indicators, or uncertain items.
3. Prioritize
Build review queues by issue, risk, confidence, and deadline while preserving the original record.
4. Confirm
Human reviewers correct or approve tags, record exceptions, and decide what may proceed to the next review or production step.
Built around your business
What we configure
- Matter-specific tag taxonomy, issue codes, privilege and confidentiality categories
- Custodian, source, date range, duplicate, family, language, OCR, and document-type handling
- Review platform, storage, legal-hold, ticketing, collaboration, and export integrations
- Access controls, redaction, retention, audit history, reviewer roles, and escalation rules
What we need from you
- Authorized document sources, matter context, legal-hold or collection rules, and review scope
- Approved tagging taxonomy with human owners for privilege, relevance, and production decisions
- A supported review or storage destination and controlled access for sensitive material
- Defined correction, escalation, retention, and audit requirements
Clear boundaries before launch
What it will not do
This agent does not make final privilege, relevance, responsiveness, collection, legal-hold, or production decisions. It must not expose restricted documents or invent tagging reasons; qualified reviewers remain responsible for interpretation, corrections, and legal conclusions.
How success is measured
Measure tagging coverage, reviewer correction rate, queue turnaround, duplicate detection, source-link completeness, uncertain-item volume, privilege-review exceptions, and time to reviewer-ready set.
Frequently asked questions
What does the AI e-Discovery Document Tagging Agent do?
It applies configured tags to authorized documents, preserves provenance, prioritizes review queues, and routes uncertain items for human confirmation.
Can it tag documents for relevance and privilege?
It can surface configured signals and apply draft tags, but qualified reviewers must confirm privilege, relevance, responsiveness, and production decisions.
Does it change or delete original documents?
No. The workflow should preserve source records and store tags, context, and review history separately or through the approved review system.
Can it handle duplicate documents and document families?
It can support duplicate, family, source, and version signals subject to the available systems, file quality, and configured rules.
How is confidentiality protected?
Access, retention, redaction, reviewer roles, and integrations are configured around your matter policies. The agent should only expose authorized material.
What happens when the tag is uncertain?
The item can be placed in a human review queue with its source context and reason for uncertainty rather than being treated as a final legal classification.
What is the starting price?
Custom implementations start at $300 USD/month. Final pricing depends on scope, integrations, usage, hosting, and support.
