How FrameQuery Compares to Other Video Search and Management Tools

We get asked a lot how FrameQuery compares to tools like Frame.io, Iconik, Descript, and others. Fair question. The video tooling space is crowded and there are products with years of polish and massive teams behind them.

We are a small team. We are in early access. We are not going to pretend we are better than everyone at everything. But we do think we are building something that fills a real gap. Let us walk through the landscape honestly.

The short version

Most video tools fall into one of two camps. Either they have strong AI-powered search but require you to upload everything to the cloud, or they work locally with your files but have no intelligence built in. FrameQuery tries to sit in the middle: AI-powered indexing with local-first search.

That said, every tool on this list does something well that we do not. Here is where things stand.

Frame.io

Frame.io (now part of Adobe) is the gold standard for video review and collaboration. Frame-accurate commenting, version control, Camera to Cloud from RED cameras, deep Premiere Pro integration. Their recently launched semantic search is impressive.

Where Frame.io is stronger: Collaboration workflows, NLE integrations, and sheer maturity. If your primary need is review and approval with clients and stakeholders, Frame.io is hard to beat. It comes bundled with Creative Cloud subscriptions, so many teams already have access.

Where FrameQuery differs: Frame.io is cloud-native. Your footage lives on their servers, and search requires connectivity. FrameQuery keeps your index local. Search works offline, costs nothing per query, and your data stays on your machine. Frame.io is a collaboration tool first and a search tool second. We are focused entirely on search and discovery.

Iconik

Iconik is a cloud-based media asset management platform with AI tagging, speech-to-text in 36 languages, and a "bring your own storage" model that connects to S3, Google Cloud, or Azure. Their consumption-based pricing (pay for what you use, unlimited users) is genuinely clever.

Where Iconik is stronger: If you are a mid-to-large media organization that needs centralized asset management with flexible cloud storage, Iconik is mature and well-designed. The unlimited-users model is unusual and attractive for big teams.

Where FrameQuery differs: Iconik's AI features are cloud-dependent. Even with their Storage Gateway, search and analysis happen in the cloud. FrameQuery processes in the cloud but searches locally. Once your index is built, you never need to phone home again. Iconik also requires more infrastructure to set up (storage gateways, cloud configuration), while FrameQuery is a desktop app you just install.

Descript

Descript pioneered the "edit video by editing text" paradigm. Delete a word from the transcript and it disappears from the video. They have impressive AI features: filler word removal, voice cloning, noise cleanup, background removal. For podcast and YouTube workflows, it is genuinely great.

Where Descript is stronger: Video editing. Descript is an editor. FrameQuery is not. If you need to produce and edit content, Descript does things we do not even attempt. Their transcript-based editing is a different product category entirely.

Where FrameQuery differs: Descript does not support cinema camera formats (no R3D, no BRAW, MP4 export only) and is not designed for managing large video libraries. It is a creation tool for content creators. FrameQuery is a search and discovery tool for people who already have footage and need to find things inside it.

Kyno

Kyno is probably the closest thing to a direct comparison. It is a desktop media management app that works locally, supports R3D and BRAW natively, and costs a one-time $159. It does preview, tagging, metadata logging, transcoding, and offloading with checksum verification.

Where Kyno is stronger: Kyno has been around longer, supports more metadata workflows (sidecar XML, NLE integration with Resolve and Avid), and the one-time pricing is very attractive. For DITs and camera assistants who need to organize and offload media on set, Kyno is purpose-built for that job.

Where FrameQuery differs: Kyno has no AI-powered search. You cannot type "red car at sunset" and find matching clips. Tagging is manual. FrameQuery automatically builds a searchable index with transcription, object detection, face recognition, and scene descriptions. The trade-off is that FrameQuery requires cloud processing (and a subscription) for the indexing step, while Kyno is entirely self-contained.

Kyno was also acquired by Signiant in 2021 and went through a long period with no updates, which worried its user base. A new version shipped in late 2025, but the long-term roadmap is uncertain.

Silverstack

Silverstack is the industry standard for on-set data management. Checksum-verified offloading, dailies creation with LUT support, audio sync, RAW development settings. If you are a DIT on a film set, you probably already use it.

Where Silverstack is stronger: On-set workflows, data integrity, and dailies. Silverstack is deeply specialized for the production phase of filmmaking, and it does that job extremely well. Their RAW format support (R3D with GPU-accelerated decode, BRAW, ARRI) is excellent.

Where FrameQuery differs: Silverstack is not a search tool. It helps you wrangle and organize media during production, but it does not analyze content or make it searchable by what is inside the footage. It is also Mac-only and uses project-based licensing ($99-319 per project duration). FrameQuery is cross-platform and subscription-based.

Cloud APIs (Google Video Intelligence, AWS Rekognition)

Both Google and AWS offer video analysis APIs that can detect objects, transcribe speech, recognize faces, and moderate content. Google recognizes 20,000+ entities. AWS can process live streams.

Where the cloud APIs are stronger: Raw analytical power. Google and AWS have massive model libraries trained on enormous datasets. If you are building a custom video analysis pipeline for a specific enterprise use case (content moderation, surveillance, broadcast automation), these APIs give you the building blocks.

Where FrameQuery differs: These are APIs, not products. You need engineering resources to build anything usable on top of them. They charge per minute per feature (Google is $0.10/min per feature, and the costs stack). They do not support cinema formats (AWS only handles H.264 in MP4/MOV, with a 10 GB file limit). And everything is cloud-only with no concept of a persistent local index.

FrameQuery uses large-scale vision models for object detection, scene description, and content analysis that rival what these cloud APIs offer in terms of entity recognition and visual understanding. The difference is that we package it as a ready-to-use desktop application. No API keys, no cloud infrastructure, no development work. You get comparable analytical depth without building and maintaining a custom pipeline.

Where we are honest about our gaps

FrameQuery is in early access. We are not pretending otherwise. Here is what we do not have yet:

No cloud storage ingestion. You cannot point us at an S3 bucket or a Google Drive folder yet. That is coming.
No public API. If you want to integrate FrameQuery into an automated pipeline, you cannot yet. This is shipping alongside cloud ingestion as part of the same release.

And here is what we do have that is worth calling out:

Index sharing. You can share your search index with collaborators so they can search your footage without re-processing it. This works across machines and keeps the original media on your storage.
FCPXML export. Search results and subclip selections export directly to FCPXML 1.11, so you can bring clips straight into Final Cut Pro or DaVinci Resolve with frame-accurate timings preserved.
Clip sharing. We are shipping a share clip feature that uses the same subclip selection UI as FCPXML export. Select a range, generate a temporary link, and send it to someone for review. It is a first step toward broader collaboration, and it works without the recipient needing a FrameQuery account.

We are a small team building something we think is genuinely missing from the market. Every tool listed above does things we cannot. But none of them combine AI-powered visual and transcript search with native cinema RAW support and a local-first architecture. That specific combination is what we are building toward.

The gap we are trying to fill

If you are a video editor or producer with terabytes of footage on local drives, your options today are:

Upload everything to a cloud platform and pay for storage and search (Frame.io, Iconik)
Use a local tool with no AI search and tag everything manually (Kyno, Silverstack)
Build a custom pipeline on cloud APIs and maintain it yourself (Google, AWS)

FrameQuery is trying to be option four: process your footage once, get an AI-generated local index, and search it forever for free. We are not there yet on every feature, but the core pipeline works and we are shipping fast.

Join the waitlist if that sounds like what you have been looking for.