Pre-Hearing Decision Research

Prepare for a hearing with the judge’s relevant decision history

When a hearing or motion argument is approaching, you need to understand how the judge has handled the issue before you, which prior decisions matter most, and which factual distinctions appear repeatedly in the relevant rulings.

With the Docket Navigator MCP, you can give your organization’s AI provider platform the same assignment you would give another member of the case team. The AI platform can use Docket Navigator’s structured patent litigation data, editorial annotations, and source material to build a focused briefing around the event you are preparing for.

Note

Important: The Docket Navigator MCP connects Docket Navigator data and research tools to your organization’s AI provider platform. The AI platform you use interprets your request, decides how to use those tools, and generates the response you see. Results may therefore vary depending on the AI provider and model your organization uses. Review important results for factual, doctrinal, and procedural relevance, and use the Docket Navigator citations and links to verify the underlying source material.

When to use this workflow

Use Pre-Hearing Decision Research when you have a specific litigation event approaching and need the assigned judge’s relevant history quickly.

The workflow can support preparation for motion hearings, claim construction, transfer disputes, stays, damages or remedies arguments, and other events where prior rulings may help the case team understand the judge’s approach.

You can ask about the motion or issue, the posture of your case, facts that may distinguish prior rulings, the judge’s historical outcomes, recent changes, and the decisions the arguing attorney should read before the hearing.

Who can use this workflow

The primary user is an attorney with a date on the calendar.

A senior or mid-level associate can use the workflow to prepare the partner who will argue the motion. A partner can use it directly to identify the rulings most relevant to the upcoming hearing. Research attorneys, librarians, and knowledge management professionals can use the same workflow when preparing judge-specific research for a case team.

Experienced patent litigators can begin with the practical assignment and let the AI provider platform translate it into the Docket Navigator research needed to answer it.

How it works

Your AI provider platform can use the Docket Navigator MCP to connect the hearing-preparation question to Docket Navigator’s structured patent litigation data.

Depending on the assignment, that may include the judge, motion type, procedural posture, motion result, decision date, related PTAB activity, editorial annotations, and underlying source documents.

That structure makes it possible to move from a broad historical view to the rulings that most closely match the case team’s current posture. The AI platform can compare facts and reasoning across decisions, identify favorable and contrary history, and explain why a particular order belongs in the briefing.

Example: Preparing for a motion to stay pending IPR before Judge Connolly

Assume you are a senior associate representing a defendant in a District of Delaware patent case before Judge Connolly. Your client and the plaintiff are direct competitors. Your client has filed an inter partes review (IPR) petition, institution is still pending, and the partner will argue a motion to stay the district court case later that week.

You want to know how Judge Connolly has handled comparable stay requests, which rulings matter most to your posture, and what factual distinctions the partner should be ready to address.

Example prompt

I have a hearing this week before Judge Connolly on our motion to stay a Delaware patent case pending IPR. We represent the defendant, the parties are direct competitors, and the PTAB has not decided institution yet. Show me how Connolly has handled comparable stay motions, which rulings matter most for our posture, and what facts the partner needs to be ready to address.

What the MCP can help identify

The request brings together several parts of the judge’s decision history:

• rulings on motions to stay pending IPR;
• the result of each motion;
• whether institution had occurred;
• who moved for the stay;
• the stage of the district court case;
• the relationship between the parties; and
• reasoning available in Docket Navigator’s editorial annotations or the underlying orders.

In testing of this workflow, the AI provider platform found 38 coded stay rulings signed by Judge Connolly, including 27 grants, nine denials, and two orders for further briefing.

The platform then narrowed that history to decisions matching the user’s posture and compared the facts associated with those rulings.

Compare the decisions that match your posture

The tested workflow identified three pre-institution rulings as especially relevant.

One of the most important was Beckman Coulter v. Cytek, No. 1:24-cv-00945-CFC (D. Del. July 30, 2025). Judge Connolly denied the stay. The case involved direct competitors, a petition awaiting institution, and a defendant seeking the stay. The underlying order showed that the case had already progressed through substantial document production, infringement contentions, and Markman briefing, with the hearing close at hand.

The AI provider platform also identified Allergan v. Prollenium, No. 1:20-cv-00104-CFC (D. Del. July 16, 2020), as a useful grant from the pre-institution set. Docket Navigator’s editorial information reflected a petition filed shortly before the stay order and a concession that immediately narrowed issues in the district court case.

A third pre-institution decision, HIP v. Hormel (D. Del. May 16, 2019), added another denial in which petition timing and the advanced stage of the district court case were important to the analysis.

Comparing those rulings allowed the AI provider platform to identify petition timing and stage of litigation as especially useful facts for the partner to investigate before the hearing. The comparison also highlighted the potential significance of a concrete concession that would narrow the district court case while PTAB review remained pending.

The judge’s historical outcomes become a set of factual comparisons the attorney can use to prepare for the specific hearing.

Compare the rulings to your own facts

Once the key decisions are identified, you can ask the AI provider platform to organize them around the facts that matter to your case.

For example:

Put the denials in a table for me, with a column for each of the circumstances you identified, so I can see at a glance which ones our facts line up with.

In the tested workflow, that comparison included institution status, who moved, petition timing, stage of litigation, the plaintiff’s competitive posture, and any concession offered by the movant.

The result gave the attorney a practical hearing-preparation checklist. The case team could fill in the corresponding facts from the current matter and see which prior rulings offered the closest comparisons.

Check whether the judge’s pattern has changed

You can also ask the AI provider platform to examine the judge’s history over time:

Show me how his stay rulings have gone year by year, so I can see whether anything has shifted recently.

In testing, the year-by-year results did not support a meaningful recent change in Judge Connolly’s disposition of these motions.

The composition of the historical record added important context. A large share of the rulings in 2021 and 2022 arose in cases where the parties were not direct competitors. That made the cases with a closer competitive posture more useful for the upcoming hearing.

You can continue testing the result when something looks unusual:

Recheck Docket Navigator for the rulings in the years that look unusually quiet.

That kind of follow-up lets the AI provider platform investigate the apparent pattern and return to the underlying Docket Navigator data before the attorney relies on it.

Verify the source behind an important distinction

Pre-hearing research often turns on the reasoning inside a small number of orders.

In the tested workflow, the AI provider platform reviewed the Beckman Coulter order and used the source to explain the discussion of petition timing and the stage of the case.

The Allergan example raised a different verification question. The available PDF did not provide extractable text, so the AI provider platform identified Docket Navigator’s editorial annotation as the available support for its description and recommended reviewing the source before quoting the reasoning in work product.

You can ask for that verification directly:

Show me the source for the timing distinction you identified in Beckman Coulter. What did the court actually say?

You can also ask:

Which parts of your summary come from the order itself, and which parts come from Docket Navigator’s annotation?

The AI provider platform can use the Docket Navigator information associated with the decision to explain the finding and direct you to the underlying source material.

Refine or continue the work

The same research can support increasingly specific preparation as the hearing approaches.

For example:

Put the denials in a table for me, with a column for each of the circumstances you identified, so I can see at a glance which ones our facts line up with.

Show me how his stay rulings have gone year by year, so I can see whether anything has shifted recently.

Which two orders should the partner read first, and what should we be prepared to distinguish in each one?

Show me the recent Delaware decisions from other judges that address the same timing issue.

Each question continues the same assignment while changing how the existing decision history is organized and evaluated.

Save and share the research in Docket Navigator

When the research is ready to circulate, you can ask your AI provider platform to save it to a Docket Navigator binder.

For example:

Save all of this to a Docket Navigator binder I can send the team, with the denials in their own tab.

In the tested workflow, the saved binder organized the judge’s full stay history alongside separate tabs for denials, grants, the pre-institution rulings, a District of Delaware benchmark, and recent Delaware decisions from other judges.

Save the research to a Docket Navigator binder so you can return to it and review current results that match the saved search criteria.

As new Docket Navigator data matches those saved search criteria, the binder reflects the current matching results. This makes the binder useful as a continuing research artifact for the case team after the AI conversation ends.

Creating or editing a binder changes saved Docket Navigator content, so your AI provider platform performs that action when you ask it to save or modify the research.

Tips for better Pre-Hearing Decision Research

Give the AI provider platform the facts that make prior decisions more or less useful to the upcoming event. For a stay motion, that may include the status of PTAB institution, petition timing, the stage of the district court case, whether the parties compete directly, and any concession the movant is prepared to make.

Ask for the decisions the arguing attorney should read first, then ask why each one matters.

When a historical rate looks important, ask the platform to show the decisions behind it and examine whether the underlying cases match your posture.

Use verification questions for reasoning that will appear in a hearing outline, brief, client communication, or other work product.

Verify important results

Before relying on an important proposition:

1. Review the cited Docket Navigator source.
2. Confirm that the source supports the AI platform’s description.
3. Check the procedural posture and factual distinctions that make the decision relevant.
4. Confirm the date period and denominator behind any historical statistic.
5. Review the underlying source material before quoting judicial reasoning in work product.

Docket Navigator provides the structured patent litigation data, annotations, saved research, and source links available through the MCP. Your organization’s AI provider platform uses that material to generate the briefing and analysis you see.

Use the attached Judicial Motion Analytics skill

If your organization’s AI provider platform supports skills, use the Judicial Motion Analytics skill attached to this article.

The skill is designed to help the platform:

• recognize a request for how a judge or court has ruled on a motion type;
• resolve the judge, motion, and result values before searching;
• establish the denominator of coded rulings and keep grant rates reconcilable;
• retrieve and verify the court’s language against the source order;
• benchmark the judge against the court;
• derive postures the data does not code, such as PTAB institution status as of a stay-order date; and
• save the research to a Docket Navigator binder when requested.

The skill does not replace legal review. It helps your organization’s AI provider platform use the Docket Navigator MCP more consistently for this particular workflow.

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The key idea

Start with the hearing you are preparing for, then use the judge’s structured decision history to identify the rulings and factual distinctions that matter most.