The Hearing Transcripts Washington Actually Trusts.
Waiting hours or a full day for transcripts while the hearing is still fresh. By the time the transcript arrives, the window for action has closed.
Generic transcription tools can't handle cross-talk, interruptions, or overlapping speakers. When it matters who said what, guessing is worse than useless.
AI summaries with no way to check claims against the source. You get text, but no proof it's right — and no way to quickly confirm.
Applied ML end-to-end — from speech recognition to speaker identification to quality verification. No human bottleneck. Transcripts are ready in 15-30 minutes, while the hearing is still fresh.
A proprietary machine-learning pipeline fuses audio, visual, and contextual signals to identify every speaker — including during the cross-talk, interruptions, and talk-overs that define a real Congressional hearing.

Every line in the transcript links to the exact moment in the source video. Click any line to hear the speaker, see the context, and verify the text yourself. No trust required — just proof.

Every plan includes the full suite of congressional intelligence tools — so the context around any hearing is one click away.
Ask any question about a hearing in plain English. Get answers with timestamp-linked citations. Click a citation to jump to the exact moment in the video.
AI-drafted hearing memos in your firm's voice. Upload writing samples and get first drafts that match your structure, tone, and language — with every claim cited.
Search legislation by intent, not just keyword. Ask a policy question in plain English and get the bills that match — semantic search that surfaces what keyword search misses.
Profiles for every member of Congress and every committee. Voting records, campaign finance, press releases, and nominations — all cross-linked to hearings and legislation.
HillGenius transcribes every Congressional hearing — including subcommittee hearings, oversight panels, and markups. No gaps in coverage, no waiting to see if a hearing makes the cut.

Built by Zack Dareshori, a former legislative clerk on the House Energy & Commerce Committee turned machine learning engineer, to solve the transcript problem he lived every day on the Hill.
“It’s probably like a three-to-five-hour difference per hearing. This is truly saving me at least five hours a day.”
— GOVERNMENT AFFAIRS ASSOCIATE, NATIONAL LAW FIRM
15-30 minutes after the hearing ends, with 99% speaker attribution accuracy.
Every Congressional hearing, every committee, every subcommittee, and markups.
A proprietary ML pipeline fuses audio, visual, and contextual signals to identify every speaker at 99% accuracy — including during cross-talk and interruptions.
Yes. Every line links to the exact moment in the source video. Click any line to hear the speaker and verify the text yourself.
Tell us about your team and we’ll set up a 14-day trial. The first transcript is on us.