AI Document Review That Follows Your Case Logic at Any Scale

Our AI-powered document review platform adapts to your specific litigation strategy and processes volumes from thousands to millions of pages. Whether analyzing a targeted batch or conducting comprehensive case-wide review, the system applies customized logic to tag documents according to your taxonomy and case theories.

Tailored Intelligence for Complex Litigation

Law firms, in-house legal teams, and litigation support providers rely on our platform to execute sophisticated document review strategies. The system handles initial document culling, thematic analysis, fact-finding missions, and targeted searches for monetary amounts, key personnel, email threads, critical dates, and document versioning patterns.

Beyond Generic Search Tools

Standard e-discovery platforms offer keyword searches and basic categorization. Our approach centers on custom logic made for your specific case or case portion that mirrors your theories of the case and addresses specific questions raised by opposing counsel or regulatory bodies. The platform supports sequential questioning with dependency-based filters, where follow-up queries build upon previous findings. Documents receive tags according to your established taxonomies, with complete transparency through detailed logs, analytical reports, and representative document examples.

Processing Pipeline Overview

Intake and Scoping Project managers collaborate with your team to define review objectives, identify data sources, establish volume parameters, and set relevance criteria specific to your matter.

Ingest and Normalization The system processes diverse file formats including PDF, DOCX, XLSX, MSG, PST files, and images. OCR technology extracts text from scanned documents while deduplication algorithms identify and flag near-duplicate content. Where available, metadata extraction captures technical and administrative properties for downstream analysis.

Baseline Markup Automated processes identify document languages, flag potential personally identifiable information, and apply privilege screening using established heuristics and rule-based patterns common to attorney-client communications.

Custom Logic Application Your case-specific rules and questions are encoded into the review workflow. Boolean operators, threshold values, and contextual queries address the unique aspects of your litigation strategy or investigation scope.

Sequential Analysis Passes Stage one filters apply broad categorization and initial screening criteria. Stage two processing executes targeted follow-up questions based on findings from earlier passes, creating sophisticated decision trees that mirror human review logic.

Tagging and Grouping Documents receive structured tags covering dispute themes, chronological events, participant roles, monetary values, document types, and procedural status markers according to your specified taxonomy.

Quality Control Statistical sampling protocols guide human review of AI-tagged documents. Attorney feedback refines rule parameters and addresses edge cases identified during spot-checking procedures.

Output and Delivery Results export in multiple formats including structured data files, narrative reports, load files for downstream platforms, and interactive dashboards. Integration capabilities support major e-discovery platforms when required.

Custom Logic and Multi-Step Questioning

Review rules operate through Boolean conditions, threshold parameters, and contextual analysis patterns. The system supports branching logic where subsequent questions depend on earlier findings.

"Tag all documents containing monetary amounts equal to or exceeding certain dollar amounts, or falling within the range of certain dollar amounts."
"Collect correspondence mentioning specified individuals and email domains into designated review folders for priority analysis."
"When contracts contain limitation-of-liability clauses, query for related amendments or addenda and capture execution dates."
"For medical records, flag instances where hemoglobin levels dropped by X percent or more within Y days."
"Identify document versions containing conflicting signature dates or inconsistent party information."
"Mark documents as 'possible privilege' when containing terms like 'legal advice,' 'privileged,' or addressing known attorney email domains."

Tagging and Taxonomies

Custom categories address the specific structure of your case including dispute themes, chronological milestones, participant roles, financial elements, document classifications, and procedural status markers. Tag versioning maintains historical records while batch application updates ensure consistency across document collections.

Scale and Performance

The platform processes document collections ranging from thousands to millions of pages. Parallel processing architecture supports concurrent analysis streams while incremental update capabilities accommodate rolling productions.

Quality and Reproducibility

Performance metrics track precision and recall rates alongside false positive and false negative indicators. Human-in-the-loop protocols establish sampling plans, capture attorney feedback, and enable rule refinement.

Engagement Models and Pricing Framework

Projects typically begin with pilot phases using limited document sets to validate logic and refine parameters before full-scale deployment. Common pricing structures include fixed fees for pilot projects, hourly rates for custom logic development, and volume-based charges for processing phases. Service level agreements establish response timeframes for rule modifications and typical delivery windows based on collection size and complexity requirements.

Typical Use Cases

Antitrust and commercial litigation matters requiring analysis of pricing communications, market allocation discussions, and competitive intelligence documents. Internal investigations focusing on policy violations, financial irregularities, or regulatory compliance issues. Medical malpractice cases involving treatment timelines, diagnostic protocols, and care standard documentation. Intellectual property disputes including technology tutorials, claim construction materials, and prior art references. Compliance audits addressing regulatory requirements and corporate governance documentation.

Next Steps

Schedule a pilot project or demonstration to evaluate the platform's capabilities against your specific document review requirements. Prepare a preliminary logic outline or question list reflecting your case theories and information needs. Compile a list of available data sources and formats. Identify a representative document subset for initial testing and validation purposes. Contact our team at Cases@CaliforniaTechnicalMedia.legal to discuss your litigation support requirements and establish a customized review strategy that combines AI efficiency with expert legal oversight.