Automations
This pillar addresses litigation workflows that search, synthesize, classify, and summarize massive document sets with retrieval-backed reasoning rather than linear manual review. The content should explain how a custom e-discovery workflow lowers review cost, improves case preparation speed, and combines vector search, legal review logic, and defensible audit trails.
This page details a custom, production-grade architecture for implementing retrieval-augmented generation (RAG) and autonomous review in litigation. It explains how to combine vector search, multi-agent orchestration, and defensible audit trails to cut first-pass review costs by 60-80% while improving case strategy speed and consistency across massive document sets.
This page outlines a custom agentic workflow that ingests collected documents, applies issue-specific classifiers, and routes them into relevance, privilege, and responsiveness buckets automatically. It covers the orchestration logic, confidence scoring, and human-in-the-loop escalation gates required to replace linear manual review with a scalable, defensible triage system.
This page explains how to build a custom workflow that identifies privileged communications, drafts log entries with proper descriptions, and applies redactions consistently across document families. It details the integration of privilege detection models, rule-based validation, and attorney review queues to slash the manual labor and risk associated with privilege review.
This page describes a custom architecture where specialized agents parse email metadata, infer conversational flow, and reconstruct fragmented threads into coherent narratives for review. It shows how this workflow eliminates manual stitching, improves context understanding for reviewers, and integrates with e-discovery platforms like Relativity or Everlaw.
This page details a custom workflow that extracts dates, events, and entities from document sets to automatically construct litigation timelines. It covers the multi-step architecture for entity resolution, event sequencing, and narrative summarization, delivering a tool that accelerates case strategy development and witness preparation.
This page explains how to implement a custom scoring and retrieval system that surfaces the most case-critical documents based on legal arguments, witness relevance, and case law. It details the agentic workflow for continuous re-ranking, alerting, and integration with review platforms to ensure legal teams never miss pivotal evidence.
This page outlines a custom automation layer that goes beyond hash-based deduplication to cluster conceptually similar documents and email families. It explains the architecture for semantic similarity analysis, parent-child relationship mapping, and batch presentation to reviewers, drastically reducing redundant review effort.
This page details a custom workflow that analyzes deposition transcripts, identifies referenced documents, and automatically batches them as exhibits with proper linking and tagging. It covers the NLP extraction, document retrieval, and quality control steps needed to save paralegals hours of manual exhibit preparation per deposition.
This page describes a custom, secure workflow for autonomously reviewing documents in sensitive internal investigations. It explains the architecture for controlled data ingestion, anomaly detection, whistleblower report correlation, and privileged communication handling, enabling faster, more consistent investigations with stronger audit trails.
This page outlines a custom build for automating the high-stakes process of responding to regulatory subpoenas. It details workflows for parsing request scope, identifying custodians, collecting responsive data, applying legal holds, and preparing production sets with mandatory metadata, reducing response time and compliance risk.
This page explains a custom automation architecture for locating, redacting, and compiling personal data across enterprise systems in response to privacy requests. It covers the integration with data maps, PII detection models, and review gates to fulfill DSARs accurately and within mandated timelines, avoiding regulatory penalties.
This page details a custom workflow that automates the extraction and analysis of key terms, obligations, and risks from thousands of contracts during merger due diligence. It explains how to build a system that summarizes findings, flags deal-breakers, and generates diligence reports, accelerating transaction timelines and improving decision quality.
This page describes a custom system for automatically finding and abstracting relevant contracts within a large discovery corpus. It outlines the workflow for clause identification, obligation mapping, and breach analysis, providing litigation teams with instant, searchable insights into contractual relationships central to the case.
This page explains how to build a custom workflow for extracting key financial and operational terms (rent, CAM, renewal options) from real estate leases at scale. It details the architecture for OCR, NLP extraction, data normalization, and reporting, enabling rapid portfolio analysis for litigation, bankruptcy, or corporate restructuring.
This page outlines a custom RAG-based workflow that searches internal technical documents and external databases to identify potential prior art. It describes the multi-agent system for query generation, technical passage retrieval, relevance scoring, and evidence compilation, drastically reducing the time and cost of prior art research.
This page details a custom automation architecture for analyzing source code repositories in software copyright or trade secret cases. It explains how agents parse code structure, detect similarities, flag proprietary algorithms, and generate plain-English summaries for expert witnesses and attorneys.
This page describes a custom workflow to automate the validation and categorization of thousands of creditor claims in bankruptcy proceedings. It covers the architecture for ingesting claim forms, cross-referencing against debtor books, detecting duplicates or inaccuracies, and routing exceptions, improving the efficiency of claims administration.
This page explains a custom build for automatically extracting and monitoring financial covenants, default triggers, and material adverse change clauses from loan agreements. It details the workflow's role in litigation or restructuring by providing instant visibility into breach status and creditor rights across a debt portfolio.
This page outlines a custom, privacy-aware workflow for reviewing communications and access logs following a potential HIPAA breach. It explains the architecture for identifying PHI disclosures, assessing scope, and compiling evidence for regulatory reporting, ensuring a faster, more defensible investigation process.
This page details a custom automation system for reviewing site correspondence, patient records, and lab data to detect potential fraud or misconduct in clinical trials. It covers the sensitive data handling, anomaly detection logic, and case-building workflows needed to support litigation or regulatory actions.
This page describes a custom workflow designed to analyze claims files, internal communications, and policy documents for patterns indicative of bad faith. It explains how to build agents that flag coverage denials, delays, or inconsistent handling, creating a powerful tool for plaintiff or defense counsel in insurance disputes.
This page outlines a custom, high-volume workflow for ingesting and categorizing medical records, exposure histories, and claimant forms in mass torts. It details the orchestration logic for standardizing data, linking plaintiffs to master complaints, and routing documents to appropriate review teams, managing scale impossible with manual methods.
This page explains a custom build for analyzing project emails, change orders, inspection reports, and BIM data in construction defect cases. It details the workflow for correlating timelines, identifying responsible parties, and extracting technical specifications, turning fragmented project data into a coherent litigation narrative.
This page details a custom workflow that parses deeds, surveys, easements, and chain-of-title documents to identify gaps, overlaps, or encumbrances. It explains the architecture for entity resolution, temporal mapping, and issue flagging, providing attorneys with a clear, automated analysis of complex title histories.
This page describes a custom automation system for government agencies to search, redact, and compile responsive records for FOIA requests. It covers the integration with records management systems, exemption code application, and workflow routing to reduce backlog, ensure compliance, and lower processing costs.
This page outlines a custom build for rapidly analyzing RFP documents, bid submissions, and evaluator notes in government contract protests. It details the workflow for comparing technical proposals, identifying evaluation errors, and compiling evidence packets, giving legal teams a decisive speed advantage in tight-filing deadlines.
This page explains a custom workflow that automates the document review necessary for data breach response, including analyzing system logs, internal communications, and forensic reports. It details how to build a system that helps determine breach scope, identify affected individuals, and support the creation of legally mandated notifications.
This page details a custom architecture for reviewing contracts, purchase orders, and software deployment data during license compliance audits or related litigation. It explains the workflow for matching entitlements to usage, identifying potential violations, and generating settlement analysis reports for in-house counsel.
This page describes a custom, ethically scoped workflow for collecting, preserving, and analyzing social media posts, comments, and metadata for litigation. It covers the architecture for targeted collection, authenticity verification, sentiment analysis, and integration into the broader discovery review platform.
This page outlines a custom workflow that analyzes deposition transcripts to automatically suggest designations (video clips) for use at trial or in motions. It explains the NLP-driven logic for identifying key testimony, the counter-designation response system, and integration with video deposition platforms like CaseNotebook or TrialPad.
This page details a custom build that aggregates all documents related to a specific witness—emails, memos, prior testimony—into a coherent, searchable file. It explains the RAG-based workflow for generating summaries, timelines, and potential examination topics, saving attorneys days of manual file compilation.
This page describes a custom automation system that parses RFAs, retrieves relevant documents and facts, and drafts proposed responses for attorney review. It covers the workflow's role in reducing the manual burden of RFA response, improving consistency, and ensuring responses are well-supported by the evidence.
This page explains a custom workflow designed to identify documents that support or undermine key factual assertions in a motion for summary judgment. It details the architecture for legal argument mapping, evidence retrieval, and gap analysis, helping attorneys build stronger, faster-moving motions.
This page outlines a custom system that automates the final steps of trial preparation: selecting key documents, applying exhibit stickers, generating lists, and linking exhibits to witness outlines. It details the integration with trial management software and the QC steps needed for error-free courtroom deployment.
This page details a custom workflow that analyzes an initial document set to provide a rapid, data-driven assessment of case merits, exposure, and potential cost. It explains the architecture for thematic analysis, hot document identification, and predictive modeling, enabling smarter, faster decisions about litigation strategy and settlement.
This page describes a custom pre-processing workflow that automatically filters out system files, duplicates, and irrelevant data (de-NISTing) from collected datasets before they enter review. It explains the orchestration of file-type analysis, hash matching, and content sampling to reduce dataset size and associated hosting costs by 30-50%.
This page outlines a custom architecture for automatically translating non-English documents within a discovery set and analyzing them for relevance and privilege. It covers the workflow for selecting translation engines, preserving legal nuance, and integrating translated content into the main review stream, removing language as a barrier to efficient discovery.
This page explains a custom build for ingesting and analyzing complex spreadsheets, financial models, and ledger data common in fraud, securities, or bankruptcy litigation. It details the workflow for formula tracing, anomaly detection, and data visualization, turning opaque financial documents into clear, actionable evidence.
This page details a custom workflow that transcribes audio/video evidence (e.g., meetings, calls, bodycam footage), synchronizes the text with the media, and performs the same RAG-based analysis as text documents. It covers the architecture for speaker diarization, sentiment analysis, and clip generation for depositions or trial.
This page describes a custom system designed to handle the unique challenges of reviewing collaborative chat data from platforms like Slack or Microsoft Teams. It explains the workflow for reconstructing channels and threads, identifying key participants, and applying legal holds and review protocols to this informal but critical communication source.
This page outlines a custom workflow for extracting metadata and textual annotations from engineering drawings, CAD files, and technical schematics in product liability or IP litigation. It explains how to build agents that compare design revisions, identify specifications, and link drawings to related documents like test reports or emails.
This page details a custom orchestration layer that intelligently batches documents for human reviewers based on complexity, issue code, and reviewer expertise. It also covers the automated QC workflow that checks for consistency, flags reviewer drift, and re-routes problematic batches, ensuring higher quality and more defensible review outcomes.
This page describes a custom workflow that continuously monitors regulatory publications, maps new requirements to internal policies and past communications, and flags potentially non-compliant documents for review. It positions this as a proactive e-discovery architecture for compliance teams in heavily regulated industries.
This page explains a custom automation system for managing the end of the discovery lifecycle: analyzing case closure, determining which held data can be released, and executing defensible disposition workflows. It covers the integration with legal hold platforms and records management systems to reduce storage costs and compliance risk post-litigation.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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