A professional and scholarly guide by Deniss Gladkihs that follows digital evidence from event and capture to courtroom presentation, human perception, and decision — and asks whether the entire path from source to conclusion can be understood, tested, reproduced, and challenged.
A digital file can be perfectly preserved and still tell an incomplete story. A screenshot can be genuine and still mislead. A machine-generated score can be calculated correctly and still be used to support the wrong conclusion.
Evidence now passes through cloud platforms, forensic software, artificial-intelligence systems, video enhancement, automated transcription, proprietary tools, and algorithmic sensors before a court ever sees it. Knowing who held a file is no longer the whole question.
The book extends the chain of custody into a chain of truth: one that follows operations as well as objects — what measured the event, what was preserved and what was unavailable, which function produced each output and how it was tested, what context was omitted, and what the courtroom actually received. It does not promise certainty. It makes disagreements smaller and reviewable.
The book gives readers a vendor-neutral way to take any piece of digital evidence apart and ask the right questions in the right order.
Every step is an operation with its own history. The chain follows operations, not only custody.
Integrity · Authenticity · Attribution · Meaning. A finding can be accepted on one and disputed on another — the book separates them instead of forcing an all-or-nothing verdict.
Evidence provenance, method provenance, and competence provenance — recorded together, because a result is only as good as the method and the person who ran it.
Each answer states its basis, its uncertainty, and the competing explanation.
Practical forms — a transformation manifest, an AI-use record, and a courtroom display check — and a recurring fictional case file, the Corridor File, that carries one stipulated event through the whole book.
The Evidence Lab works five problems end to end: an edited body-camera recording, a screenshot and phone at the scene, a voice clone and an AI-enhanced face, an automated violation with rival presentations, and the artifact the parser did not know.
Judges, litigators, investigators, forensic practitioners, students, and technically informed readers.
Judges and litigators may begin with Parts VI–VIII and the Evidence Lab. Examiners may begin with Parts II–V and Part IX. Students may read in sequence, following the Corridor File.
Topics include metadata and timestamps, forensic imaging, mobile and cloud evidence, body-worn cameras, license-plate and facial recognition, automated decision systems, AI-assisted legal work, deepfakes and voice cloning, validation, expert testimony, courtroom presentation, and cross-border evidence.
The author leads the Academy's evidence-integrity and practice labs. The book's method shapes the parts of the curriculum where evidence and AI meet.
The book argues that a credential is evidence about competence, not competence itself, and that what it proves weakens as tools, law, and threats move on (chapters 33–34). That is why Academy certificates are dated, independently verifiable, and renewed — see Certification.
Integrity, authenticity, attribution, and meaning are taught as separate questions — the discipline behind the Academy's evidence-integrity work in the product labs.
Deepfakes, voice cloning, and the liar's dividend (chapters 35–36) are the ground covered by authentication in the deepfake era in Level IV, Advanced Systems & Trial Simulation.
The book is vendor-neutral. In its own words, Lawnova is “an implementation context, not the evidentiary authority for the vendor-neutral method developed here.” The author is Software Architect & Forensics Lead for Lawnova and participates in developing Lawnova platforms and training.
| Title | Chain of Truth |
|---|---|
| Subtitle | Digital Evidence and the Future of Proof |
| Author | Deniss Gladkihs |
| Format | Paperback · illustrated interior · US Trade 6 × 9 in |
| Length | 300 pages |
| ISBN-13 | 978-0-557-86714-1 |
| Published | 2026 · research cut-off 10 September 2026 |
| Available from | Lulu |
Chain of Truth is a scholarly and professional work, not legal advice or a case-specific expert report. Legal status, standards, products, pricing, and platform behavior are time-sensitive and must be verified before use.
Director of Digital Forensics, Evidence Integrity & Practice Labs at Lawnova Academy, and the software architect behind the Lawnova platforms, with more than twenty-five years in digital forensics, data recovery, and systems engineering. Faculty profile →
An illustrated work of literary nonfiction about what happens when law, human error, institutional design, and artificial intelligence meet inside the systems that judge our lives — and the case for a system that is auditable rather than automated.