Frametail

Video-native observability for generative AI

Traces, benchmarks, and evaluations for teams running AI-powered video applications in production. Compare outputs, catch regressions, and keep scored runs your team can link in review.

Book a demo

exp_8a3f2b9c4e1d

completed
Motion comparison test · Compare camera movements across fixed subject
A/B dimension
Configuration
Aspect ratio
16:9
Model
veo-3.1-fast
Run progress
6 / 6 cells (6 ok)
Results
One row per input; columns follow task order.
InputA: Subject closeupB: Wide shotC: Low angle
A ballet dancer performs a pirouette in a sunlit studio.
completed
8.2s
completed
8.1s
completed
8.3s
The dancer extends one arm gracefully while spinning.
completed
7.9s
completed
8.0s
completed
8.1s
The problem

Generative video fails differently than conventional releases. Motion, fidelity, and timing shift when models or prompts change, often with no failing test and little signal in text-first observability.

Regressions surface in production or in manual clip review, not in a shared record the org can cite. Release reviews stall on whether quality improved because evidence still lives in threads and spreadsheets instead of comparable runs.

Frametail is built for AI product and engineering teams who ship generative video and need the same question answered every release: will this change actually help?

Why Frametail

Turn opinion into something you can ship against

Frametail gives teams a shared place to score video outputs, compare runs, and point at evidence when the release train is already moving.

Comparable runs

Pin the dataset once. Argue about the diff, not the setup

Benchmarks stay tied to rows, scorers, and model settings so "better" means the same contract as last week.

-|-Immutable artifacts beat screenshots.

motion-quality-suite

completed

Benchmark · Compare runs on a pinned dataset

Pinned · dataset_ballet_v3 · 240 rows · sha 8a3f…
Scorerv1.4 (last week)v1.5 (today)Δ
prompt_adherence0.880.92+0.04
motion_smoothness0.910.89-0.02
audio_sync0.940.94±0.00
Aggregate0.910.92+0.06
Production adjacent

Read traces next to the clip, not three tools away

Spans and timing sit beside the generation so on-call engineers can answer what changed without rebuilding the story from memory.

-|-Observability that respects the artifact.

trace_91ce4a2f

OK
1.84s · veo-3.1-fast · fal

"A ballet dancer performs a pirouette in a sunlit studio."

frame 24 / 192

Spans
provider.fal.generate1.42s
frame.interpolate220ms
audio.lipsync120ms
score.prompt_adherence48ms
score.motion_smoothness36ms
Your existing stack

Work with the tools your team already uses

Frametail SDKs wrap fal, OpenRouter, and more so tracing and benchmarks attach to the clients and pipelines already in production. No rip-and-replace inference layer.

-|-Provider-agnostic instrumentation.

fal, OpenRouter, and Vercel AI SDK orbit as example integrations in your existing stack.

fal
OpenRouter
Vercel
What you get

Evals that survive a release week

Frametail is for teams shipping generative video who are tired of debating quality from memory. Same inputs, same scorers, scored runs you can link in a PR.

Comparable benchmarks

Pin a dataset, attach scorers, and keep an immutable record you can diff against next week. No more "trust me, it got better."

Traces you can read

Follow generations through spans and timing without pretending they are syslog noise. Production visibility stays close to the artifact.

Experiments that compare tasks

Run tasks side by side with the same scorers attached, then promote the winning setup into a benchmark when the team is ready to sign off.

Org boundaries that match reality

Billing and scorer libraries sit at the organization. Projects isolate what ships so integrations do not step on each other.

Live scoring on traces

Sample production traces under rules you configure. Scores attach to the trace, and a dataset benchmark stays a deliberate step when you need that contract.

FAQ

Answers to the most common questions

Learn how Frametail handles benchmarks, experiments, traces, and what your team should expect week to week.

View all 24 questions →

Blog

Notes on shipping generative video

Visit blog →

Gemini Omni shipped: benchmarks matter more now

Google’s Gemini Omni turns video into multi-turn, multimodal sessions. If you ship on top of that, pinned benchmarks beat launch demos.

PlaybookMay 19, 2026

When a benchmark is worth more than another leaderboard

Why curated evaluation beats endless model comparison, and how to build benchmarks that actually drive product decisions.

PlaybookFeb 28, 2026

Designing scorers that survive contact with real users

Building reliable evaluation criteria for generative video: from prompt engineering to human-in-the-loop validation.

GuideFeb 21, 2026

Get started today

Connect a project, send your first trace, and run a benchmark when you are ready to compare with intent. Most teams get a useful loop inside a day.

Book a demo

exp_8a3f2b9c4e1d

completed
Motion comparison test · Compare camera movements across fixed subject
A/B dimension
Configuration
Aspect ratio
16:9
Model
veo-3.1-fast
Run progress
6 / 6 cells (6 ok)
Results
One row per input; columns follow task order.
InputA: Subject closeupB: Wide shotC: Low angle
A ballet dancer performs a pirouette in a sunlit studio.
completed
8.2s
completed
8.1s
completed
8.3s
The dancer extends one arm gracefully while spinning.
completed
7.9s
completed
8.0s
completed
8.1s