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Legal AI workflow guide ยท Relativity aiR ยท B07-038

Reviewing E-Discovery Documents with Relativity aiR

An investigation team needs to classify a large document population for relevance and privilege considerations. Explore how to assess the workflow, verify original information and keep important decisions under professional review.

Understand the taskCheck important exceptionsKeep people accountable

Independent educational guide. Product features and access conditions can change; confirm them with the relevant provider. No affiliation or hands-on performance testing is implied.

Third-party product research, not a TechCorpLegal service announcement. Source-linked claims require final review; product access varies.

1. What problem does this solve?

An investigation team needs to classify a large document population for relevance and privilege considerations. The practical challenge is not merely preparing an AI-generated answer. Someone must determine which documents are operative, which information can be shared, whether the result is complete, and what it means for a legal or business decision.

For e-discovery counsel and litigation support, the starting question is whether the proposed task has a defined scope. An organized answer may still be unreliable if its source was outdated, if the system lacks access to an important amendment, or if a professional judgment was treated as a clerical task. This guide explores the boundary for reviewing E-Discovery Documents with Relativity aiR, not a generic assurance about AI performance.

Warning sign: Relevant documents containing handwriting are missed by the configured process. The proposed evaluation should deliberately include this failure case rather than only a neat demonstration.

2. What a better process could look like

For this scenario, start with permissioned relativity air workspace, example tagged documents, review protocol and accuracy test set. Use those records to prepare e-discovery review protocol and sampling audit sheet, with an explicit owner for every step. If something fails, keep the original file alongside the working copy so the team can recover the factual starting position.

For this task, the useful outcome to assess is e-discovery review protocol and sampling audit sheet.. That is a proposed sample output, not a product guarantee or a deliverable TechCorpLegal has committed to provide. The important question is whether the team can verify the facts and explain any exception to its normal rule.

3. What Relativity aiR may contribute โ€” and what it does not establish

Relativity aiR is discussed here as a third-party product. The cited provider documentation describes relevant functions, but it does not establish that any particular workspace has the required access, that a suggested workflow has been tested, or that TechCorpLegal is affiliated with the provider.

The relevant official source for this assessment is Relativity โ€” September 2026 aiR product update. It describes a wider product or legal-work capability. The use case in this guide is a proposed evaluation of that capability, not confirmation that the product performs the complete workflow in an unattended manner. Permission levels and source availability must be verified for the actual workspace.

The essential functional distinction here is: Relativity aiR's review classifications and controlled corpus analysis. A vendor's feature description does not prove that a model is accurate on a customer's own documents, or that a draft is legally sufficient. A successful evaluation therefore requires original records, human checks and a pre-agreed definition of failure.

4. A practical example to test

Example situation: An investigation team needs to classify a large document population for relevance and privilege considerations.

Documents and information to prepare: Permissioned Relativity aiR workspace, example tagged documents, review protocol and accuracy test set. Do not use a real client's confidential or personal information unless access, lawful purpose, technical safeguards and confidentiality obligations have been approved. A synthetic or properly anonymized sample is suitable for preliminary evaluation.

Suggested evaluation sequence:

  • Confirm which aiR features are generally available.
  • Define a precise classification task.
  • Sample machine outputs against review labels.
  • Escalate exceptions.

At each stage, document the input and the proposed answer separately. Do not allow an AI-generated finding to overwrite the original record. For any ambiguous output, mark it as requiring professional review. The expected test artifact is e-discovery review protocol and sampling audit sheet., with source references sufficient for another person to reproduce each material finding.

5. What to check before relying on a result

The acceptance question should be specific: Does the test compare the extracted evidence with the full underlying record? Use a short checklist before progressing from a demonstration to routine work:

  • Source: Can every material assertion be traced to the document, date or authority that supports it?
  • Coverage: Is the complete operative version of the input present, including amendments or later changes where relevant?
  • Permissions: Was access to any confidential or restricted item genuinely authorized?
  • Failure test: Does the workflow detect, flag or escalate this example: Relevant documents containing handwriting are missed by the configured process.
  • Reviewer: Who will approve the output, correct an error and decide whether it may be shared?

A polished response about reviewing e-discovery documents with relativity air can still miss the decisive issue. Test this precise exception: Relevant documents containing handwriting are missed by the configured process. Log the source, output, reviewer finding and correction. Comparative performance statements need repeatable test evidence rather than a single successful example.

6. Where this approach is different

Relativity aiR's review classifications and controlled corpus analysis. That distinction matters because a generic assistant may produce a summary that is useful for orientation but unsuitable for a legal filing, client advice or contract acceptance. Here the task is not complete until the underlying record has been inspected and open questions are explicitly assigned.

For Relativity aiR, the vendor documentation is evidence of described features, not proof that e-discovery review protocol and sampling audit sheet can be produced in every workspace. Validate the exact user rights, document connections and supported workflow. Relativity aiR's review classifications and controlled corpus analysis. If the access conditions are not met, use the scenario as an evaluation checklist rather than treating it as a working product instruction.

7. Who should consider it โ€” and who should pause

Potential readers: E-discovery counsel and litigation support. A suitable first experiment uses records the team is allowed to handle and a question for which it can independently verify the right answer. Compare the proposed result with a reliable manual reference or existing professional method.

Reasons to pause: For this workflow, the test is not ready when access to permissioned relativity air workspace, example tagged documents, review protocol and accuracy test set is unclear or no reviewer can check whether does the test compare the extracted evidence with the full underlying record?. Legal jurisdiction, data rights and product entitlements must be resolved before using actual matter records. Before trying this with real matter files, confirm the applicable plan, authorized settings, confidentiality controls, professional obligations and human decision owner. Relativity distinguishes generally available functions from advanced-access and 2027 roadmap features.

This Relativity aiR guide is independent educational research. It provides no evidence of a TechCorpLegal partnership or of TechCorpLegal performing reviewing E-Discovery Documents with Relativity aiR for clients. The example must be checked by an authorized lawyer before use in a real matter.

8. Questions to ask during an evaluation

  1. What exact decision is e-discovery review protocol and sampling audit sheet. supposed to support, and who signs off?
  2. What material input was providedโ€”permissioned relativity air workspace, example tagged documents, review protocol and accuracy test setโ€”and which versions were left out?
  3. Can the proposed workflow follow all four steps while recording the supporting evidence?
  4. What happens if relevant documents containing handwriting are missed by the configured process?
  5. How can the team repeat the test when the vendor updates its product or access rules?

For a Relativity aiR demonstration, ask the provider to show how the system would confirm which air features are generally available, including any restrictions and log entries. Then test whether the team can escalate exceptions. Keep confirmed current functionality separate from planned features, partner integrations and illustrative examples.

9. Useful next step and published evidence

A small, controlled trial can start with the scenario in this guide. Build e-discovery review protocol and sampling audit sheet., have a knowledgeable reviewer check the source material, and log the outcome of the failure test. If that process cannot be reproduced or the product cannot provide the required functions with approved permissions, record the gap and consider a narrower workflow.

Source 1: Relativity โ€” September 2026 aiR product update โ€” https://relativity.com/blog/its-all-here-whats-new-in-relativity-air/

Source 2: American Bar Association โ€” Formal Opinion 512 (2024) โ€” https://www.americanbar.org/content/dam/aba/administrative/professional_responsibility/ethics-opinions/aba-formal-opinion-512.pdf

Editorial limitations: Published vendor materials support general product descriptions only. They do not establish TechCorpLegal implementation capability, independent testing, confirmed buyer search volume or conversion results. Product and brand names identify third parties; no affiliation is implied. Search intent is an unmeasured hypothesis. Final source-link permissions, SEO metadata, public CTA destination and canonical URL await approval.

Local page action: Return to the practical checklist.

Quick questions about this use case

What should I prepare first? Start with permissioned relativity air workspace, example tagged documents, review protocol and accuracy test set. and ensure the materials are approved for the test.

What would count as a serious mistake? Relevant documents containing handwriting are missed by the configured process.

What should the reviewer verify? Does the test compare the extracted evidence with the full underlying record?