Opposing counsel rarely attacks momentum conservation — they attack the numbers you fed it. The assumed drag factor. The perception-reaction time "everybody uses." The EDR data you weighed less than your crush analysis. This AI examiner runs that cross out loud, in your voice workflow, and scores every answer against the post-2023 FRE 702 standard — before the real deposition does.
Start a free accident reconstruction mock deposition → How the expert trainer worksReconstruction is one of the most frequently challenged disciplines under Daubert — not because the physics is weak, but because the opinions rest on selected inputs: friction coefficients, stiffness values, perception-reaction times, occupant kinematics. Every assumed (rather than measured) input is a cross-examination door.
The examiner in this trainer is built to walk through those doors: it locks you into your point estimate, then makes you defend every input, one at a time, the way a prepared defense or plaintiff attorney will.
Drag factor pulled from a published table — no site testing, no exemplar skid, no surface documentation from the scene date.
Delta-V from the event data recorder disagrees with your crush analysis — and you stayed with the number that favors the retaining side.
A 1.5-second PRT applied without justifying it for darkness, curvature, expectancy, or the driver population at issue.
PC-Crash / HVE run on default stiffness and restitution values — and no sensitivity runs to show the answer survives input variation.
Opinion built from photographs alone; crush measurements scaled from images with unquantified error.
"The occupant's injuries are consistent with…" — an injury-causation opinion from a reconstructionist invites a scope objection and a Daubert motion.
The examiner locks you into your single-value speed opinion, then walks the inputs one at a time until the point estimate is standing on unmeasured assumptions.
Why this lands: If you never ran a sensitivity analysis, your "reasonable degree of engineering certainty" is a point estimate built on selected inputs — and the jury just watched you admit it. If you did run one, this is where you say so, cleanly. The trainer makes sure you know which witness you are before the transcript does.
You tell it your discipline and the case posture, and a realistic AI examiner cross-examines you out loud — attacking input selection (friction, PRT, stiffness values), EDR-vs-crush conflicts, inspection scope, and any drift into biomechanics. After every session you get a 5-axis FRE 702/Daubert scorecard showing where you over-answered, guessed, or exceeded your scope. Unlimited private reps.
Unvalidated inputs (assumed friction coefficients and perception-reaction times), reliance on simulation software without sensitivity analysis or stated error rates, opinions from photographs without vehicle or scene inspection, and scope creep into injury causation. The post-2023 FRE 702 amendment sharpened the "reliable application to the facts" prong — the exact prong input-selection attacks target.
It helps on qualifications, but qualifications are only the first prong. Most reconstruction exclusions and impeachments come from methodology-application attacks — the inputs and the fit to this crash — which accreditation does not answer. The trainer drills exactly those prongs.
Your first full AI mock deposition is free — no credit card. After that: a $99 one-time 30-day pass with unlimited sessions before a specific deposition, or Expert Pro at $39/mo if you are deposed regularly.
Yes. Sessions are private by default and are not shared with retaining counsel, opposing counsel, or anyone else. This is educational deposition practice, not legal advice — always follow the guidance of retaining counsel, and don't enter confidential case identifiers.
Your first full AI mock deposition is free — no credit card. Enter your field, get cross-examined out loud, and read your Daubert scorecard in about ten minutes.
Start your free mock deposition → Compare training options