NetDocuments and Epiq Agentic AI Legal Tech Updates

NetDocuments and Epiq are moving legal AI beyond document summarization and drafting. NetDocuments has added six AI-powered apps to ndMAX Studio for trademark prosecution and plaintiff-side litigation, while Epiq has announced early access to expanded Epiq AI Accelerate capabilities that can execute system-level eDiscovery actions from natural-language requests. The announcements were made in July 2026 and are relevant to firms and compliance teams evaluating whether AI can operate inside governed legal workflows.

The practical difference is workflow scope. NetDocuments is packaging repeatable tasks as connected, pre-built applications; Epiq is extending agentic execution across eDiscovery platforms. Neither release removes the need for attorney or litigation-support review, but both indicate that the buying question is shifting from “Can this model generate text?” to “Which controlled steps can it perform, and how are those actions checked?”

What NetDocuments added to ndMAX Studio

NetDocuments added six applications divided between trademark prosecution and plaintiff-side litigation. The company says the expanded ndMAX Studio now contains 39 pre-built legal AI apps that can be deployed without developers, with customization available through its ndMAX AI App Builder. These are company-reported product capabilities, not independent performance benchmarks, and should be assessed against a firm’s own documents, jurisdictions and review standards. NetDocuments’ July product announcement describes the six apps and their intended workflows.

The trademark group includes Trademark Pre-Filing Registrability & Risk Review, Trademarks USPTO Office Action Response and USPTO Trademark Prosecution Deadlines. The litigation group includes Medical Chronology, Demand Generator and Expert Witness Profile Builder. Together, they cover intake, analysis, deadline extraction, first-draft production and reuse of institutional knowledge.

That packaging matters because many firms do not need another general-purpose chat interface. They need a repeatable sequence that starts with a defined source document, produces a structured output and leaves a clear point for professional review. A pre-built app can reduce implementation work, but it does not automatically prove that the underlying workflow is accurate for every matter.

How the trademark apps change day-to-day work

Trademark prosecution workflow with risk review, Office Action response draft and verified deadlines

The trademark apps target three points where manual work and timing risk often converge. The pre-filing review app analyzes a draft application and produces a structured memo covering potential issues such as descriptiveness objections, disclaimer requirements and scope-drafting concerns. The Office Action app analyzes refusals and requirements and generates a structured draft response based on a prosecution playbook. The deadlines app extracts dates from USPTO correspondence and adjusts for weekends and federal holidays, while requiring human review before the result is saved, according to NetDocuments’ description.

For an IP team, the most useful feature is not any individual draft. It is the possibility of linking the stages: review the filing before submission, prepare a response when an Office Action arrives, and surface the resulting deadline from the source correspondence. That can make the workflow easier to standardize across attorneys and docketing staff.

There are still important boundaries. A risk memo is not a legal opinion, a generated Office Action response is not a filing-ready submission, and an extracted date should not enter a docket without verification. Teams should define who owns the review, what source files are authoritative and how corrections are recorded when the application misreads a document.

What the plaintiff-side litigation workflow includes

The plaintiff-side workflow begins with medical records and moves toward case evaluation and demand preparation. NetDocuments says Medical Chronology organizes records into a chronology by treatment event, provider and key clinical findings. Demand Generator can then extract damages from medical and financial records, calculate totals and draft a jurisdiction-appropriate demand narrative with a proposed range. The company also introduced Expert Witness Profile Builder, which creates searchable profiles from CVs, deposition transcripts and published works. The product documentation explains how the chronology and demand stages are intended to connect.

This is a more consequential design than using AI for a single summary because errors can propagate. If a chronology omits a treatment event, the omission may influence damages extraction and then appear in a demand draft. The appropriate operating model is therefore staged review: validate the chronology, validate the damages table, and only then use the narrative generator.

Expert profiling addresses a different problem: knowledge scattered across matters. A structured internal profile can make prior testimony and published work easier to locate, but it should be treated as a research aid rather than a definitive assessment of an expert’s credibility or admissibility. Firms need retention rules, access controls and a process for correcting outdated or disputed information.

What Epiq’s agentic update actually does

Governed eDiscovery workflow turning a natural-language request into approved system actions

Epiq announced early access to expanded capabilities in Epiq AI Accelerate for eDiscovery. The company says users can submit natural-language requests that are translated into system-level actions across workspace management, processing and imaging, search, summarization, review, export, production-set identification and conflict searches. Epiq’s announcement outlines the expanded agentic capabilities and supported process areas.

Epiq says the expanded functionality uses Anthropic’s Claude models together with a proprietary reasoning and execution layer. It also describes access through Epiq Service Cloud and the use of Model Context Protocol functionality to operate across Epiq Discover and other eDiscovery software platforms.

The governance layer is central to the announcement. Epiq lists platform-specific permissions, workflow approvals, data isolation, audit logs and traceability of AI actions as built-in controls. These features do not guarantee that an action is correct, but they create the operational evidence needed to review what the system was allowed to do, what it did and under whose authority.

Why system-level execution is different from legal chat

A chat assistant usually returns an answer or draft for a person to act on. An agentic workflow can select tools, change a workspace, launch processing or prepare an export. That makes it more useful for repetitive operations, but it also expands the consequences of a bad instruction, an ambiguous request or an incorrect interpretation of permissions.

For eDiscovery teams, the distinction is practical. “Summarize these documents” is primarily an analysis request. “Create a workspace, add a field, process the collection and prepare the production set” is a chain of operational actions. The second request needs authorization boundaries, approval gates and a reliable record of intermediate decisions.

Independent legal-technology coverage has also been tracking the broader shift from isolated AI features toward platforms, governance and workflow integration. Legal IT Insider’s July coverage places these launches within a wider legal-technology market focused on accountable AI adoption. That context is useful, but vendor announcements remain the primary source for the specific capabilities described here.

How law firms should evaluate the NetDocuments release

Start with a workflow inventory rather than a model comparison. Select one process with a clear input, measurable output and identifiable reviewer. Trademark teams might begin with Office Action triage or deadline extraction; plaintiff firms might begin with medical chronology review; litigation groups might test expert-profile search across closed matters.

Define the source documents and the expected output format.
Set a review checklist for omissions, unsupported conclusions, calculations and jurisdiction-specific requirements.
Run a controlled sample using historical matters that have already been reviewed by lawyers.
Record correction rates, escalation points and time spent validating the output.
Decide whether the app should be used as a drafting aid, a search layer or part of a connected workflow.

Do not evaluate only the quality of the final prose. For legal work, traceability, source linkage, permissions and the ease of correcting an error may matter more than stylistic fluency. The strongest candidate is usually the workflow that removes repetitive preparation while preserving professional judgment at the consequential steps.

How compliance and eDiscovery teams should evaluate Epiq AI Accelerate

For agentic eDiscovery, the first evaluation should concern authorization. Ask which actions can be initiated by natural language, which require explicit approval, whether permissions are inherited from the underlying platform and how the system handles a request that spans multiple workspaces or data custodians.

Teams should also require an action-level audit trail. The record should make it possible to reconstruct the request, the tools selected, the data affected, the approvals obtained and the final state of the workspace. Epiq says its expanded capabilities include audit logs and AI action traceability, but prospective users should confirm retention, exportability and access to those records in their contractual and technical review.

Test ambiguous instructions and conflicting permissions.
Verify that a failed or partial action is clearly reported.
Check how exports, production sets and generated fields are approved.
Confirm data-isolation and retention behavior for sensitive matters.
Define a rollback or remediation process before enabling broader access.

Early access also means availability and behavior may change. Procurement teams should document the tested release, supported platforms and any limitations communicated by the vendor rather than treating an early-access capability as a finished enterprise standard.

Common implementation mistakes

The most common mistake is treating an AI workflow as a substitute for process design. If a firm has inconsistent naming conventions, unclear matter ownership or incomplete source documents, automation can make the inconsistency faster without making it safer.

A second mistake is measuring only labor removed from the first draft. Review time, exception handling, training and governance all affect the business case. A workflow that produces a draft quickly but requires extensive verification may still be valuable, but its value should be measured as a complete process rather than as generation speed.

Finally, firms should avoid allowing broad access before testing edge cases. Sensitive medical records, privileged material, expert information and discovery exports each require different controls. Role-based access and human approval are operational requirements, not optional add-ons for a later phase.

What this means for legal-tech strategy in July 2026

The two launches point in the same direction from different parts of the market. NetDocuments is expanding a library of connected, practice-specific apps inside document management; Epiq is adding controlled execution across eDiscovery systems. In both cases, the strategic asset is the workflow context around the model: source data, permissions, playbooks, approvals and institutional memory.

For law firms and compliance teams, the next step is to choose one narrowly bounded workflow and define its evidence standard before purchase or deployment. If the system can save repetitive preparation while keeping source documents, reviewer responsibility and action history visible, it is a candidate for production. If it cannot explain what changed or who approved the change, keep it in a supervised pilot until those controls are in place.

NetDocuments and Epiq Push Legal Tech Toward Agentic Workflows