OptoJury tests your case story against a statistically modeled panel from your state and county. See where the story creates confidence, where it creates doubt, and what you should strengthen before trial.
A preparation tool, not a prediction of an actual jury or trial outcome.
Start with the question
Live mock juries are valuable because they show you what real people question, which facts they remember, and where a case story becomes difficult to follow. But they are expensive to convene and often leave you with a broad answer: what did this particular room think?
OptoJury is built for the work between those sessions. Pressure-test alternate stories, isolate the fact that moves a holdout, and turn uncertainty into a concrete preparation list. It does not replace live mock-jury research; it helps you decide what to test next and arrive better prepared.
| The question lawyers ask | OptoJury | Real mock jury | Asking GPT |
|---|---|---|---|
| How quickly can I test a case theory? | Run a structured panel read when the story changes, without scheduling a room. | Requires recruiting, briefing, scheduling, and facilitating participants. | Usually immediate, but the answer depends heavily on how the prompt is framed. |
| Can I compare two credible narratives? | Yes. Test both stories against the same case record and compare where reactions diverge. | Yes, but each version takes more time to prepare and control in the room. | It can compare text, but it does not provide an independent panel response. |
| Does it reflect the place where the case will be heard? | Uses state and county population context to shape the modeled panel. | Depends on who is recruited and how closely the group matches the venue. | General knowledge is not a statistically modeled local jury. |
| What kind of signal do I get? | Recurring concerns, holdouts, proof gaps, narrative movement, and what could change a view. | Rich live discussion, questions, body language, and unexpected group dynamics. | Drafting help, issue spotting, and a fast outside perspective on the material provided. |
| Can I repeat the test as the case develops? | Yes. Re-run after new evidence, a revised opening, or a different narrative. | Possible, but each session adds recruiting and facilitation cost. | Yes, though responses can vary with the prompt and model context. |
| What does a first pass cost? | One case credit for a 10-juror panel, about $150 at $15 per juror. | For 10 people, roughly $750–$1,000 for a half day or $1,500–$2,000 for a full day, before other logistics. | Often included in a general AI subscription, but it is not a recruited or modeled jury panel. |
| When is it the strongest fit? | Between major research sessions, when you need a concrete next preparation move. | When you need deep live qualitative research and can support the logistics. | When you need to organize facts, draft language, or explore an early question. |
Illustrative comparison based on a 10-person panel and the stated participant rates; recruiting, venue, moderation, and other mock-jury costs vary. These tools answer different questions. OptoJury is designed to help lawyers decide what to test, strengthen, or prepare next; it is not a substitute for live research or legal judgment.
Illustrative report example
The panels below demonstrate the report structure: where a narrative leads, which jurors hesitate, what evidence could move them, and what to prepare next.
This is an illustrative product example based on a separate sample matter, Varela v FCA US LLC. It is not a prediction, an actual jury, or an actual case outcome.
A clearer way to see the product
OptoJury does not ask a model to invent a random juror. It gives the simulation the case facts, the venue, a modeled response pattern, and the history of the discussion.
Full Panel Simulation
OptoJury builds a modeled jury panel from your state and county. It gives each juror a defined set of traits and tests your case through several rounds. You can do this before trial.
Each round shows who changed position and what caused the change. You see the discussion that led to the final vote.
Read the result in context
Six of ten modeled jurors preferred the notice story.
The timeline gave the panel a clearer way to evaluate responsibility.
Check the inspection time, camera timestamp, and witness foundation.
The simulation does not identify the legally correct theory or predict an actual jury. It gives you a structured prompt for preparation.
Built on Jury Science
OptoJury builds juror types from weighted public survey data and county population data. It uses published attitude measures as model inputs, then adjusts the panel to match the selected venue.
These are modeled jurors, not real people or generic personas. Each one has modeled tendencies, such as institutional trust, damages sensitivity, reactance, and authority deference. Those tendencies shape how the simulation reads your evidence.
The panel is adjusted to a venue profile, then each juror receives a different response pattern.
The model uses weighted public survey data and county population data. It is exploratory. It does not predict any specific juror, jury, or case outcome.
Narrative Testing
Test your negligence theory against strict liability. Test your damages story against your liability story. OptoJury shows which version moves more jurors and why.
The same story can land differently with a different panel. Compare the results and see which juror types respond to each version. Use that result when you write your opening.
| Compare | Theory A · Negligence | Theory B · Strict liability |
|---|---|---|
| What it asks | Did the defendant fail to act reasonably? | Was the product defective when it left the defendant’s control? |
| Evidence that carries it | Notice, warnings, conduct, and what a reasonable actor would do. | Design, manufacturing, instructions, and the product’s condition. |
| Where it can break | The panel sees shared responsibility or too many steps between conduct and harm. | The panel sees misuse, alteration, or a defect that is not proven. |
Narrative A/B Results
Two modeled jurors remained uncertain on strict liability. Negligence framing created the clearer path.
Case Management Integration
Connect Clio. Import supported matter details, then send the simulation summary back as a note.
You can also enter case details directly when needed.
A careful way to use AI
AI is entering legal work. You do not have to hand over your judgment. OptoJury helps you learn where simulation can support your preparation.
We send the case details and structured juror context needed for each model request. OptoJury uses Anthropic for juror simulation and OpenAI for selected intake and report-analysis tasks. OpenAI and Anthropic state that API inputs and outputs are not used to train their models by default.
Provider retention and safety rules still apply. Read the OpenAI business data policy and Anthropic commercial data policy.
Questions before you start
You should know where the simulation helps, where it stops, and what happens to your case information.
No. OptoJury uses a modeled panel to help you test a case story, find concerns, and decide what to prepare next.
The model uses weighted public survey data and county population data. The result is exploratory and requires lawyer review.
No. It gives you a faster way to test questions and stories before deciding where live research would help most.
The service sends the case details and structured context needed for each model request. Provider retention and safety rules still apply.
No. They are analytical constructs that summarize modeled response patterns. They are not psychological diagnoses or descriptions of actual jurors.
Early Access
OptoJury is in early access for plaintiff trial attorneys. Join the list and we'll notify you when your spot opens.