Products / The Evidence Orchestrator
The Evidence Orchestrator
Court-ready evidence preparation for every law office working with multi-format discovery. The platform reads the MP4. Body cameras, dash cameras, interview audio, surveillance video, CCTV from a private investigator, recorded depositions. Google’s Gemini transcribes, captions, and indexes every file in the matter folder. Silence is captioned, not skipped. The reading has to be exhaustive, because body-camera archives have grown past 100 petabytes of video that mostly goes unwatched.1 Court-bound output passes three-AI consensus review before the attorney signs. This is the part of the platform that does not exist anywhere else for defense work.
01 The World You Walk Into
A Matter Folder With A Reader Inside It.
You are a defense attorney, a paralegal, a legal assistant, a private investigator, a discovery clerk. You handle matters where the evidence arrives in multiple media: video, audio, photo, text, document. The Evidence Orchestrator was built for the day you actually have. The platform’s posture is defense-side. The presumption of innocence is in the vocabulary. The audit trail is in the architecture. The attorney work-product doctrine is honored by design.
Drive is the source of truth. The canonical path is Client Files / Client / Matter / Evidence. The Orchestrator reads from that source, never from a copy stored elsewhere. The chain of custody stays clean because the file never leaves the folder it arrived in.
02 The AI Reads The MP4
The Headline Capability, In Plain Language.
Most legal software treats a video file as opaque. You open it, you watch it, you write a paragraph about it, you move on. The Evidence Orchestrator treats the MP4 as readable.[1] Google’s Gemini transcribes the audio, captions the visual content, and indexes the file by what is actually in it. The body camera now lives in the matter the same way a deposition transcript does. You filter by phrase. You filter by timestamp. You filter by speaker. You filter by what is on screen.
Silent files are not skipped. Every silent stretch gets a descriptive caption (“[engine idling, no audible speech, two figures cross the frame at 00:01:43]”). The ratio of silence to interaction becomes part of the case story, not a gap in the record.
Three-AI consensus reads every court-bound document before the attorney signs.[2] OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini all read the draft. All three have to agree before the document is treated as final. Disagreement surfaces back to the attorney as a question, never as a silent override.
03 What It Does, In Plain Language
The Capabilities In The Matter Folder.
Multi-Media Transcription
Body Cam, Dash Cam, Interview, CCTV.
Google’s Gemini transcribes the audio and captions the visual content. Timestamps run in three formats: D:HH:MM:SS, plain language, and the wall-clock window the recording was happening.
Silent File Captioning
Silence Is Documented, Not Skipped.
Every silent file gets descriptive captions. “Engine idling.” “Officer approaches the driver-side door.” “Vehicle parked, no movement, three minutes.” Silence becomes part of the case.
Book-Formatted Worksheets
Identical Numbering Across Viewer, PDF, And DOCX.
The evidence worksheet exports with hyperlinked table of contents and jumpable index. Q1 through QN per media type, numbered the same way in the in-app viewer, the PDF, and the DOCX. Indexed legal reference book.
Three-AI Consensus On Court Docs
Three Models Have To Agree Before The Attorney Signs.
Court-bound output passes through OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini. Disagreements surface as questions, not silent edits. Defensibility posture.
Drive-Backed Source Of Truth
Files Stay In Drive. The Orchestrator Reads From Drive.
Canonical path: Client Files / Client / Matter / Evidence. The Orchestrator never holds a copy somewhere else. Chain of custody is intact because nothing moves. And the reading is never trusted to one model, since general-purpose AI hallucinates on up to 88% of specific legal questions.2
Wall-Clock Time Reporting
Every Duration Shows Three Formats.
Running time (D:HH:MM:SS), plain language (“one hour, forty minutes”), and the wall-clock window the recording was happening. Jury-facing presentation, always.
04 A Day Inside The Orchestrator
Two Stories About Working With AI-Read Evidence.
Scenario
Tuesday, 7:30 AM. A Criminal Defense Paralegal.
You arrive to find that the state produced ninety-eight minutes of body-camera footage from two officers last night, plus a thirty-minute interview audio with the complainant. You drop the four files into the matter folder. By the time the attorney walks in at 8:15, the Orchestrator has transcribed both videos, captioned the silent stretches, and indexed every spoken sentence with a timestamp and a speaker tag.
You filter the body-cam transcript by “consent” and find one return. You read the surrounding ninety seconds in plain text. You flag the moment for the attorney’s review. By 9 AM the attorney has the issue, the timestamp, and the verbatim. The platform hands back the hours a lawyer normally loses, in work where only about 38% of the day is billable.4 The motion to suppress drafts itself from the matter record.
Scenario
Thursday, 3:14 PM. A Private Investigator In A Family Law Matter.
You just finished a six-hour surveillance on a school-pickup pattern, including a forty-minute interview with the maternal grandmother. You upload the surveillance video and the interview audio to the matter folder. The Orchestrator transcribes the interview, captions the surveillance footage (license plates, time of day, who exits the vehicle), and indexes both alongside the text-message threads already in the matter.
By 5 PM the attorney has the fact pattern, the timestamps, the photos, the transcript, and the captioned video. The temporary-orders draft updates with three new facts. Three-AI consensus reads the language. The attorney edits one paragraph and signs.
05 Buddy Inside The Orchestrator
Buddy Reads Your Matter. Buddy Reads Your Evidence.
Buddy is the voice layer of the platform. Inside the Orchestrator, Buddy knows your matter folder, your transcripts, your captions, your chronology, and your motion drafts. Ask in plain language.
- “Buddy, when did Officer A first mention Miranda on the body cam?”
- “Buddy, how much silence is on this dash cam relative to interaction?”
- “Buddy, draft the chronological timeline of this matter from the existing evidence.”
- “Buddy, summarize the surveillance video in plain language for the temporary orders draft.”
06 Sources And Citations
Where The Specific Claims On This Page Come From.
- Google’s Gemini. The multimodal AI used by The Evidence Orchestrator for transcription, captioning, and indexing of MP4 evidence files. gemini.google.com
- Three-AI Consensus Posture. The platform’s requirement that every court-bound document pass review by OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini before the attorney signs.
- Texas Disciplinary Rules of Professional Conduct, Rule 1.05. Confidentiality of client information. Texas Center for Legal Ethics. legalethicstexas.com
- Texas Code of Criminal Procedure, Article 39.14 (the Texas rule requiring the State to hand over its evidence to the defense). Discovery. The Texas defense-side discovery statute, including the Michael Morton Act amendments. statutes.capitol.texas.gov / CR.39.14
Sources are current as of May 23, 2026. None of this page is legal advice. The named attorney on any matter bears the final responsibility for the discovery posture and the motion practice.
Evidence Orchestrator
A Matter Folder With A Reader Inside It.
Body cam, dash cam, interview audio, document files. Indexed in your matter folder, signed by your attorney, ready for court.
AI-assisted drafts are proposed for human review, not finished or filed work product. Adding to cart means you agree to the Terms and the AI Policy.
The Case In Numbers
The Reading Has To Be Read, And Read Again
Body camera video now arrives by the terabyte, and almost none of it is ever watched. The Orchestrator reads all of it, then refuses to trust a single machine with what it found.
of body-camera video sat in one vendor’s archive by 2024, most of it stored and never seen by anyone.1
of specific legal questions where general-purpose AI returns a fabricated answer, the reason nothing here runs on one model.2
answers from even purpose-built legal research AI can be wrong; the best tool tested was accurate just 65% of the time.3
A defense lawyer bills about three hours of an eight-hour day. The rest disappears into work like watching discs of footage no one has time for.4 The Orchestrator gives that day back. Google’s Gemini transcribes, captions, and indexes every file, including the silent stretches, so the attorney opens a searchable record instead of a pile of unwatched video. Then every court-bound document passes a three-model consensus, OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini, and any disagreement returns to the attorney as a question, never a silent override. The researchers who measured those error rates reached the same conclusion this platform is built on. AI is a first reader. The lawyer is still the lawyer.
Ready To Open A Matter In The Orchestrator?
The Evidence Orchestrator is the evidentiary backbone. It pairs with The Issue Spotter on the motion side. Both share the same matter folder. The evidence you index is the evidence your motion cites.
Buy The Evidence Orchestrator
The Whole Evidence Lane, From Subscription To Per-Matter Pilot.
From a single-matter pilot at $750 to per-attorney firm subscriptions. Plus the integrations, onboarding, and three-AI quorum reviews that make it work.
See How It Works
The Evidence Orchestrator Explainer
Open the public explainer for this product, then continue through the full Learn library.
Open the explainerReferences
Where These Numbers Come From
- ProPublica, “Police Departments Are Turning to AI to Sift Through Millions of Hours of Unreviewed Body-Cam Footage,” 2024. propublica.org
- M. Dahl, V. Magesh, M. Suzgun & D. E. Ho, “Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models,” Stanford RegLab, Journal of Legal Analysis, 2024. academic.oup.com
- V. Magesh et al., “Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools,” Stanford RegLab, 2024. reglab.stanford.edu
- Clio, “Legal Trends Report,” 2025. clio.com
