S.N.R-IQ / Digital Evidence Interrogator
S.N.R-IQ — AI-Assisted Digital Forensic Evidence Review
S.N.R-IQ is an AI-assisted digital evidence review system designed to help legal professionals examine forensic expert reports, identify potential gaps between technical findings and expert conclusions, and formulate the questions necessary for meaningful evidentiary scrutiny.
Developed around the principles of the Judicial Digital Evidence Assessment Framework (J-DEAF).
S.N.R-IQ is currently in beta development. The public demonstration uses illustrative sample outputs and does not perform live forensic analysis.
The recorded information.
What examination establishes.
The meaning attributed to the findings.
What the evidence can legally establish.
The critical question is not merely whether the technology worked, but whether the expert's conclusion is supported by what the technology actually established.
Six proposed review functions, illustrated in the public prototype. These descriptions outline the intended review structure, not validated production capabilities.
Examine whether forensic findings support the propositions attributed to them. Identify potential inferential gaps, hidden assumptions, alternative explanations, and missing evidentiary foundations.
J-DEAF: Source · Interpretation · Evidentiary Significance
View illustrative reviewBreak a factual proposition into individual elements and distinguish supported, conditionally supported, inferred, disputed, unsupported, and unknown claims.
J-DEAF: Interpretation · Evidentiary Significance
View illustrative reviewExamine timestamp origins, clock settings, time-zone interpretation, automated activity, and the limits of temporal attribution.
J-DEAF: Source · Methodology · Interpretation
View illustrative reviewIdentify additional forensic records, acquisition documentation, logs, validation materials, and tool settings required for meaningful review.
J-DEAF: Acquisition · Methodology · Transparency
View illustrative reviewExamine acquisition scope, evidence preservation, hashing, integrity verification, and the limitations of technical authenticity claims.
J-DEAF: Acquisition · Integrity · Transparency
View illustrative reviewReview forensic methods, tool suitability, software versions, validation, configurations, limitations, and independent cross-checking.
J-DEAF: Methodology · Transparency
View illustrative reviewComing Soon
Designed to examine whether factual allegations in legal pleadings extend beyond the supporting forensic evidence. Not an active capability.
Prototype · Fixed sample outputs · No live analysis · No document uploads
Hypothetical sample record
A server log records a successful account login at 02:14. The report attributes the activity to a named individual and alleges deliberate disclosure.
A login record supports account activity, not necessarily the identity of the person using it.
Question for independent professional review
What independent evidence connects the session to the identified person?
The Judicial Digital Evidence Assessment Framework (J-DEAF) is a proposed structured methodology developed by Dr. Shani Roffeh, Adv to support the critical assessment of digital forensic evidence and expert conclusions.
What is the origin of the digital information, and what does the record actually establish?
How was the evidence collected, what was excluded, and what may be missing?
Was the evidence preserved, and what can integrity verification legitimately establish?
Were the tools and methods appropriate, documented, and adequately validated?
Do the expert's conclusions logically follow from the underlying technical findings?
Can the examination be meaningfully reviewed, reproduced, and independently challenged?
What can the evidence establish, and where are the boundaries of the proposed legal conclusion?
J-DEAF is a proposed research framework. It is not an officially adopted forensic standard or an independently validated judicial assessment instrument.
Identifying a digital event does not necessarily establish who caused it or why. Each step requires its own evidentiary foundation.
A record or file exists. Its presence alone does not establish its cause or meaning.
Forensic applications may filter, classify, exclude, or omit information before an examiner begins substantive interpretation. Acquisition scope, filtering settings, processing limitations, and transparency may affect the interpretation of findings. Not every filtering decision is improper; its purpose and consequences should be documented and understood.
Outside the collection scope.
Present in the acquisition, absent from examination.
Reviewed, but omitted from the final report.
Identify potential weaknesses in opposing expert reports and develop focused expert examination and disclosure questions.
Support structured review of methods, assumptions, technical limitations, and evidentiary reasoning.
Explore systematic approaches to understanding digital evidence and forensic interpretation.
Examine methods for distinguishing technical observations from expert interpretations and legal conclusions. No judicial endorsement or court adoption is implied.
Dr. Shani Roffeh, Adv
Dr. Roffeh's research examines the knowledge gap between law and technology, particularly the evaluation of digital forensic evidence and the reasoning connecting findings to legal conclusions. S.N.R-IQ is intended as a structured review aid, not a general-purpose legal chatbot.
S.N.R-IQ does not provide legal advice, issue forensic expert opinions, determine admissibility, or replace independent professional examination.
Inquire about future beta participation. An inquiry does not grant immediate access or guarantee availability. Please do not send case files or confidential evidence.
Email a beta inquiryS.N.R-IQ is an AI-assisted digital forensic evidence review system designed to help legal professionals examine expert reports and identify potential gaps between technical findings and expert conclusions.
J-DEAF is a proposed seven-domain framework for systematically assessing digital evidence and the reasoning underlying forensic expert conclusions.
No. It is intended to support professional review and does not replace independent forensic examination or legal judgment.
No. Admissibility and evidentiary weight remain legal determinations for the appropriate decision-maker.
S.N.R-IQ is in beta development. The public demonstration currently uses illustrative outputs and does not provide live forensic analysis.
S.N.R-IQ's review structure is organized around the seven domains of J-DEAF, which examine source, acquisition, integrity, methodology, interpretation, transparency, and evidentiary significance.
Interrogate the Evidence. Challenge the Inference.