AI Deposition Summary: Automated Transcript Analysis and Document Creation

The Deposition Summary Problem

A single deposition can generate 200-400 pages of transcript. Complex litigation involves dozens of depositions.

Attorneys need summaries that:

• Identify key testimony by topic
• Highlight admissions and contradictions
• Include page-line references for citations
• Support trial preparation and cross-examination
• Organize chronologically or by issue

Manual summarization: 4-8 hours per deposition.

AI summarization: 15 minutes processing + 30 minutes review.

How AI Deposition Summarization Works

The Processing Pipeline

1. Transcript input (PDF, TXT, or word processor format)
2. Speaker identification and diarization
3. Topic classification and segmentation
4. Key testimony extraction
5. Admission/contradiction detection
6. Page-line reference preservation
7. Summary generation in requested format

What AI Extracts

Factual testimony:

• Who did what, when, where
• Sequences of events
• Relationships between parties
• Document references

Key admissions:

• Statements against interest
• Acknowledgments of facts
• Concessions on disputed points

Contradictions:

• Internal inconsistencies
• Conflicts with other testimony
• Differences from prior statements

Topics and themes:

• Liability facts
• Damages evidence
• Credibility issues
• Technical explanations

Sample Output

DEPOSITION SUMMARY
Witness: John Smith, VP Operations
Date: January 15, 2026
Duration: 4 hours, 15 minutes
Pages: 187

TOPIC: Knowledge of Product Defect

pp. 34-38: Smith testified that he first learned of customer
complaints in March 2024. "We started seeing returns come in,
maybe around March." (34:12-14) However, admitted receiving
an email from QC department in January 2024 flagging
potential issues. (Exhibit 7, referenced at 36:4-8)

KEY ADMISSION: Smith acknowledged that the company continued
shipping product after receiving QC's warning: "We wanted to
investigate further before stopping production. That takes time."
(37:22-38:3)

TOPIC: Decision-Making Authority

pp. 52-61: Smith described the approval process for product
recalls. Stated he "would have been involved" in any recall
decision (54:8) but could not recall specific meetings or
communications regarding the product at issue. Deferred to
CEO Williams on "final decisions." (58:14-17)

CREDIBILITY NOTE: Smith claimed not to remember key meetings
on 14 separate occasions during this section.
...

Types of Deposition Summaries

Page-Line Summary

pp. 23-24: Describes first meeting with plaintiff (23:8).
           States meeting occurred "sometime in late 2023" (23:15).
           Cannot recall exact date (24:2-4).

pp. 25-28: Discusses contract negotiations.
           Admits plaintiff raised safety concerns (26:12-18).
           States concerns were "addressed" but cannot specify how (27:8-11).

Best for: Trial preparation, cross-examination planning.

Topical Summary

CONTRACT FORMATION
- Initial discussions: pp. 15-22
- Key terms negotiated: pp. 34-41, 67-72
- Plaintiff's understanding: pp. 45-48

PERFORMANCE ISSUES
- First complaint: pp. 89-94
- Company response: pp. 95-103, 112-118
- Subsequent problems: pp. 124-140

DAMAGES
- Claimed losses: pp. 156-162
- Documentation provided: pp. 163-168
- Mitigation efforts: pp. 171-175

Best for: Issue organization, brief writing.

Chronological Summary

MARCH 2023
- Contract signed (pp. 34-36)
- Initial payment made (pp. 37-38)

APRIL 2023
- First delivery received (pp. 45-47)
- Plaintiff inspection (pp. 48-52)

MAY 2023
- Defect discovered (pp. 67-72)
- Plaintiff notification to defendant (pp. 73-78)

Best for: Timeline construction, fact patterns.

AI Deposition Tools

Dedicated Legal Platforms

CaseText/Parallel

• Legal-trained AI
• Citation formatting
• Case law integration
• Brief integration

Everlaw

• eDiscovery platform
• Transcript analysis
• Timeline visualization
• Review workflows

Relativity/Reveal

• Large-scale document review
• Transcript processing
• AI-assisted coding
• Enterprise deployment

General AI with Legal Prompting

Claude/ChatGPT with Prompts

• Flexible summarization
• Custom formatting
• No legal-specific training
• Requires careful prompting

Limitations of general AI:

• No page-line preservation without explicit formatting
• May miss legal significance
• Requires legal professional to prompt effectively
• Output is text, not formatted document

The Document Gap

Most AI tools produce text summaries. Legal practice requires:

• Formatted Word documents
• Specific citation styles
• Table of contents for lengthy summaries
• Track changes for collaborative editing
• Court-compliant formatting

From Summary to Court-Ready Document

The Workflow Challenge

AI produces: Plain text summary
You need: Formatted DOCX for:
  - Filing with court
  - Sharing with co-counsel
  - Client distribution
  - Trial notebook

Document-Level Solution

from docxagent import DocxClient

def create_depo_summary_document(summary_text, witness_name, case_info):
    client = DocxClient()

    # Start from template or blank
    doc_id = client.create_blank()

    # AI structures the summary into proper document format
    client.edit(
        doc_id,
        f"""Create a formatted deposition summary document:

        Case: {case_info['case_name']}
        Court: {case_info['court']}
        Witness: {witness_name}

        Summary content:
        {summary_text}

        Format as:
        1. Title page with case caption
        2. Table of contents
        3. Witness information section
        4. Summary organized by topic
        5. Page-line citations in proper format
        6. Index of key admissions

        Use professional legal document formatting.""",
        author="Legal Document AI"
    )

    output_path = f"depo_summary_{witness_name.replace(' ', '_')}.docx"
    client.download(doc_id, output_path)
    return output_path

# Create court-ready document from AI summary
summary = """
[AI-generated summary text from transcript analysis]
"""

case = {
    "case_name": "Smith v. Acme Corp",
    "case_number": "2025-CV-12345",
    "court": "Superior Court of California, County of Los Angeles"
}

document = create_depo_summary_document(summary, "John Smith", case)

Collaborative Editing

def review_summary_with_changes(summary_doc, reviewer_notes):
    client = DocxClient()
    doc_id = client.upload(summary_doc)

    # Apply reviewer's changes with track changes
    client.edit(
        doc_id,
        f"""Review this deposition summary and apply these changes:

        {reviewer_notes}

        Make all edits with track changes so the original
        author can see modifications.""",
        author="Senior Associate Review"
    )

    output_path = summary_doc.replace('.docx', '_reviewed.docx')
    client.download(doc_id, output_path)
    return output_path

# Senior attorney reviews AI summary
notes = """
- Add cross-reference to Smith's earlier testimony at pp. 23-25
- Flag contradiction with Williams deposition regarding March meeting
- Strengthen language on key admission re: knowledge of defect
- Add note about demeanor during questioning about emails
"""

reviewed_doc = review_summary_with_changes("depo_summary_smith.docx", notes)

Accuracy and Verification

What AI Gets Right

• Factual extraction (who, what, when, where)
• Page-line references (if properly formatted input)
• Topic organization
• Basic admission identification

What Requires Human Verification

• Legal significance of testimony
• Strategic implications
• Credibility assessments
• Context that AI may miss
• Connections to other evidence

Verification Workflow

AI Summary Generated
       ↓
Associate spot-checks key sections against transcript
       ↓
Attorney reviews critical admissions
       ↓
Paralegal verifies page-line citations
       ↓
Final attorney approval

Rule of thumb: AI handles 80% of the work; humans verify 100% of the output.

Cost-Benefit Analysis

Manual Summarization

200-page deposition
Time: 6 hours average
Cost: $300/hour (associate time)
Total: $1,800 per deposition

20 depositions in case
Total: $36,000 for summarization

AI-Assisted Summarization

200-page deposition
AI processing: 15 minutes
Review and editing: 45 minutes
Cost: $300/hour × 0.75 hours = $225
Tool cost: ~$25 per deposition

Total: $250 per deposition

20 depositions in case
Total: $5,000 for summarization
Savings: $31,000 (86%)

Beyond Cost

• Speed: Same-day summaries vs week-long delays
• Consistency: Every deposition summarized same way
• Completeness: AI doesn't skip pages
• Searchability: Structured output enables better search

Building a Deposition Summary Workflow

Phase 1: Transcript Processing

Receive transcript from court reporter
       ↓
Convert to machine-readable format
       ↓
AI summarization with topic organization
       ↓
Initial summary document generated

Phase 2: Review and Refinement

Associate reviews AI summary
       ↓
Checks key sections against transcript
       ↓
Adds legal analysis and strategy notes
       ↓
Document edited with track changes

Phase 3: Integration

Summary integrated with:
  - Case management system
  - Trial preparation database
  - Brief writing reference materials
  - Client reporting

Phase 4: Trial Use

Summary indexed for quick access
       ↓
Key admissions flagged for cross-examination
       ↓
Contradictions noted for impeachment
       ↓
Page-line citations ready for real-time lookup

The Bottom Line

AI deposition summarization transforms a time-consuming task into a manageable one. Hours become minutes for initial processing.

But legal work requires more than summarization:

• Formatted documents for court and clients
• Track changes for collaborative review
• Integration with trial preparation workflows

The best approach combines:

1. AI for initial transcript analysis and summarization
2. Document-level tools for formatting and collaborative editing
3. Human review for legal judgment and strategy

AI summarizes. Documents deliver. Humans decide.