Describe any shot, moment, or line of dialogue. Niravi finds it across your entire library — every frame, every word, every face. On your hardware, in seconds.
Your team uses ChatGPT and Gemini for scripts and briefs. Your actual footage — the asset you've spent years building — is still locked in folders named COMP_v14_FINAL_FINAL.mov.
Finding a reference shot from 3 projects ago takes an afternoon of scrubbing. Your archive of award-winning composites, simulations, and plates is invisible to your team.
260,000+ hours of content and no way to find the right clip for a promo, recap, or compilation without a junior editor spending two days looking.
Shift handoffs are verbal. QC supervisors scrub manually. Artists re-search for the right frame every single project. The knowledge in your shots is lost the moment delivery happens.
Three input modalities. One library. Instant results.
Describe any shot, dialogue, person, or sound in plain language. Niravi searches every frame and word across your entire library.
Drop a reference frame. Niravi finds visually similar shots — same composition, lighting, or scene type — across all your projects.
Every track in your footage is automatically identified — title, artist, timestamp. Find cleared and uncleared music across your entire library instantly.
Every studio burns hours on tasks that should take seconds. Here's what that looks like.
Niravi reads video the way a human expert would — but across your entire archive, simultaneously, in minutes.
Not filename search. Not tag search. Real semantic understanding — like describing a scene to a colleague who's watched everything.
Find reference shots by visual description. Track every composite across projects.
Search 500,000+ hours of archive by content. Auto-clip promos from any episode.
Find any archive clip for a breaking story. Search by spoken word across all recordings.
Make every delivered project searchable. Shift handoffs become instant, not verbal.
Find the right take from any shoot. Repurpose unused B-roll across client libraries.
Find any play or athlete across seasons. Search commentator audio for any keyword.
The best editors, supervisors, and producers shouldn't spend their day scrubbing timelines. They should be creating.
Tasks that used to take a day now take minutes. Not because you work faster — because Niravi already watched everything.
Scan your entire cut before delivery. Flag problematic scenes, spot unapproved takes, surface anything that needs a second look — in one pass.
Niravi identifies every track, every timestamp, across your entire library. Know exactly what's uncleared before your OTT delivery deadline hits.
No script on file? Niravi reconstructs it from the footage — dialogue, scene descriptions, shot headings — in industry format, ready to use.
ChatGPT is brilliant. But it can't see inside your videos. Connect Niravi via MCP and suddenly it can — search every frame, read every word, identify every track. One connection. Unlimited power.
The same unit Twelve Labs uses — so you can compare directly. We're 7–15× cheaper because we run on Apple Silicon, not GPU cloud.
Runs entirely on your Mac. Unlimited processing, forever. No subscription.
Cloud processing for studios without Mac infrastructure. Pay per minute processed.
Higher throughput, dedicated capacity, and faster turnaround for production pipelines.
On-premise deployment, custom integration, volume pricing, and dedicated support.
Analyses 1 minute of video in 15 seconds — 4× faster than realtime — using Apple Silicon Neural Engine, MPS, and MLX.
Every model runs locally. Unreleased footage never touches a cloud server. No account. No upload. Nothing leaves your studio.
Twelve Labs charges Rs.70+/min. Niravi starts at Rs.5. Desktop is a one-time purchase with zero running cost.
Bring a project — a rough cut, an archive reel, anything. We'll run it through Niravi live and show you what it finds. No setup required on your end.
Runs entirely on your hardware · No data leaves your studio · No account required for desktop