Take Control from Upload to Production

The Electronic Discovery Reference Model (EDRM) is the industry-standard framework for managing electronically stored information (ESI) in litigation. It covers nine stages from information governance through presentation. Logikcull supports the core discovery workflow (collection, processing, review, analysis, and production) in a single self-service platform, eliminating the vendor handoffs and IT dependencies that slow teams down at each stage transition.

Electronically stored information (ESI) refers to any data created, stored, or transmitted in digital form that may be relevant in litigation. Logikcull processes 300+ ESI types including email and email archives (PST, EML, MSG), Microsoft 365 documents, Google Workspace files, Slack and Teams messages, PDFs, spreadsheets, images, audio and video files, and scanned or handwritten documents. All ESI is fully indexed, including dark data like embedded images and attachments, so every piece of evidence is searchable.

Logikcull's review workflow is built to cut time and cost at every step. Before review even starts, Culling Intelligence™ uses AI to eliminate 70–90% of unresponsive documents. Smart auto-tags automatically detect PII, privileged communications, inclusive emails, end threads, and near-duplicates, so reviewers arrive at a pre-sorted, pre-tagged set. Natural language search powered by ASK lets reviewers ask plain-English questions and get cited answers, rather than constructing Boolean queries. Reviewers can also use customizable tagging panels, batch coding, and keyword search to move through documents rapidly. The result: dramatically less time in linear review.

Culling is the process of reducing a raw document set to only those most likely to be responsive, cutting review time and cost dramatically. Logikcull's Culling Intelligence™ combines several AI-powered techniques: end-thread detection (removing duplicate email chains), inclusive email identification, near-duplicate grouping, and smart filters for date ranges, file types, custodians, and keywords. Together, these tools typically eliminate 70–90% of unresponsive data before a human reviewer sees a single document. One Fortune 400 company reduced its email data by 75% before paralegals even started review.

Technology-assisted review (TAR), also called predictive coding, uses machine learning to prioritize documents most likely to be responsive based on reviewer decisions, dramatically reducing the volume of documents that require human review. Logikcull's Culling Intelligence™ uses AI-driven document categorization and tagging to surface the most relevant documents and cut non-responsive data before linear review begins. Logikcull's ASK engine further accelerates this by answering natural language queries across the entire corpus with cited supporting documents.

Logikcull automatically detects potentially privileged communications through smart tagging, flagging documents that contain attorney names, legal domains, or privilege-related language before reviewers begin. Reviewers can apply and track privilege tags, redact privileged content, and withhold documents from production with a full audit trail. All privilege decisions are logged with timestamps and user attribution, supporting the creation of defensible privilege logs and protecting against inadvertent disclosure.

Logikcull performs both global deduplication (across an entire matter) and custodian-level deduplication automatically during processing. Exact duplicates are identified and grouped, eliminating redundant review of identical documents. Email threading further reduces noise by identifying the most inclusive version of an email chain so reviewers only code the thread once. These steps happen automatically in the background with no manual configuration needed, and are fully documented for defensibility.

Logikcull automatically scans and tags documents containing personally identifiable information (PII), including Social Security numbers, bank account numbers, credit card numbers, and other sensitive identifiers, using AI-powered detection. Identified PII can be redacted before production or used to filter documents for DSAR (Data Subject Access Request) responses. This eliminates the need to manually search for sensitive data across large document sets and reduces the risk of inadvertently producing protected information.

Logikcull produces court-ready document sets in a few clicks, from selecting the production set to generating the final output. Productions support Bates stamping, redactions, load files (DAT, OPT, LFP), native files, TIFF/PDF image output, and custom slipsheets. Every production is logged with a full audit trail, and Logikcull prevents over-production by flagging privileged or withheld documents before the production runs. What used to require a vendor and days of lead time now takes minutes.

Yes. Logikcull is built for the most sensitive legal data. The platform is hosted on AWS in a SOC 2 Type II-certified environment with 99.99% uptime, and meets HIPAA, GDPR, CCPA, ISO 27001, and NIST CSF requirements. All data is encrypted in transit and at rest with 256-bit AES encryption and backed up daily. Access is controlled through granular permissions, SSO, and two-factor authentication, and can be provisioned or revoked in under 5 minutes. Every access event is logged, giving counsel full visibility into who touched what and when.