Omission behavior
Does the tool flag a missing fact, clause, record, or authority?
Legal AI buyer guide
Which legal AI tools fit a personal injury firm?
Start with one workflow, the failure that carries the largest legal cost, and the person who will review the output. A brand list without those 3 facts gives every firm the same wrong answer.
Decision guide
The same tool can be a good fit for one workflow and a bad fit for the next.
Answer 3 questions. Your result appears on the page. No email required.
No generic winner
Choose the workflow, failure, and available reviewer. The result will give you the next test, not a paid placement.
The 6-risk screen
Score what happens when the output is wrong, incomplete, or hard to supervise.
Reproducibility
Can the firm reproduce an earlier output and identify the model version?
Privilege and data handling
Are retention, training, storage, and subprocessors stated in writing?
Supervision fit
Do citations, diffs, and surfaced uncertainty support attorney review?
Operability
Can the intended user run the workflow without a systems person?
Exit cost
Can the firm export matters, prompts, history, and usable work product?
Stop rule: a 0 on axes 1 through 4 stops adoption. Those axes cover liability and supervision. Axes 5 and 6 cover operating cost.
Evidence before score
A high score with weak evidence is still a weak decision.
Observed
A first-hand test with saved input, output, version, date, and reviewer notes.
Documented
A current agreement, policy, security document, product screen, or vendor document.
Reported
A verified user report or third-party source with enough context to inspect.
Unverified
A claim that is ambiguous, inferred, old, or unsupported.
Grade D evidence cannot support a main recommendation. Data handling and other stop-rule claims need Grade A or B evidence.
3 tests worth running
Break the input before a live matter breaks the output.
Remove one known record
Run a medical chronology with one expected record missing. Check whether the tool calls out the gap or writes around it.
Plant one unsupported claim
Put an unsupported damages statement in a demand draft. Check whether the tool repeats it, qualifies it, or asks for support.
Create a source conflict
Give the tool 2 documents that disagree on a material fact. Check whether the conflict appears in the output and source trail.
The review-capacity test
A tool can pass every product test and still fail inside the firm.
Someone still has to inspect sources, resolve exceptions, and approve the work. If that person has no protected time, compare capacity models before adding another tool to the queue.
FAQ
Questions firms ask before the first test.
Which legal AI tool is best for a personal injury firm?
There is no universal winner. The right short list depends on the workflow, the failure the firm needs to control, and the review capacity available after the tool produces an answer.
Why does this guide avoid a ranked vendor list?
CounterbenchAI has not completed the same first-hand test set across enough vendors to publish a defensible ranking. The guide gives firms the method and routes them to current directory entries without presenting paid placement as research.
What score should disqualify a legal AI tool?
A score of 0 on omission behavior, reproducibility, privilege and data handling, or supervision fit should stop adoption until the issue is resolved. A low operability or exit-cost score creates a cost decision rather than the same legal stop.
Can software solve a paralegal-capacity problem?
Software can reduce work inside one repeatable task. It still creates exceptions, source checks, and final review. A firm with no reliable review owner has a capacity decision to make before a software decision.