SliceSeeker

Self-hostable semantic search inside long-form video

What

Semantic search inside long-form video. Ask in plain text and get near-exact moments back — a line in a talk, a slide, a take you need. Transcript, frame, and multimodal embeddings fused with weighted Reciprocal Rank Fusion; collections keep each search space focused.

Why

Drop-in semantic video search as an internal service — precise timestamps without owning the indexing stack, with workers you can scale to your workload.

Where

Gallery

Hybrid search

person explaining a chart next to a whiteboard…Search
  • 1:121:28
    RRF 0.0421videospeech

    clip-01.mp4

    segment 7 · 1:12–1:28
Hybrid search
RRF search field, modality weights, and video-segment result skeletons.

Library

Upload

clip-01.mp4

1.2 GiB

Demos

clip-02.mov

840 MiB

Research

clip-03.mp4

2.4 GiB

Demos

clip-04.mp4

318 MiB

Archive
Library
Video library table with file icons, collection reassignment, and upload CTA.

Usage & Costs

Cost vs Video Length

clip-01…clip-02…clip-03…clip-04…clip-05…clip-06…clip-07…clip-08…clip-09…
Cost Length

Per-file Breakdown

clip-01.mp4

$0.0100

clip-02.mp4

$0.0042

clip-03.mp4

$0.0140

clip-04.mp4

$0.0088

clip-05.mp4

$0.0035
Costs
Cost-vs-length chart with per-file spend breakdown table.

Upload Video

Drag & drop videos here

clip-01.mp4

Uploading

clip-02.mov

Paused
Upload panel
Collection organization strip, dashed dropzone, and resumable file progress rows.

Technicals

Async workers (BullMQ + Valkey) with idempotent jobs, pgvector for embeddings, TUS for long uploads, RustFS object storage, and Vercel's AI Gateway for embedding and transcription.

Upcoming

  • Kubernetes and Helm charts for HA deploys
  • Multimodal queries — image, video, or speech in, not just text
  • Worker stress-testing toward metric-based autoscaling