AI Infrastructure & MLOps Paid

Overshoot

Low-latency API infrastructure for real-time AI vision applications

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PricingPaid
Starting priceUsage-based
Free planUnknown
Free trialYes
APIYes
Open sourceNo
DeploymentCloud
Last verifiedJuly 30, 2026
Overview

Tool overview

Overshoot is listed under AI Infrastructure & MLOps AI tools.

Summary

What is Overshoot?

Overshoot provides infrastructure for real-time vision applications. Developers publish live video through WebRTC, reference frames or time ranges through an OpenAI-compatible API, and query hosted or passthrough vision-language models with low-latency responses.

Best fit

Best for

Developers building low-latency applications over live video streams

Audience

Who is it for?

AI developersRobotics teamsSecurity product teamsGame developersVideo infrastructure engineers
Recommendation

Decision note

Suitable for evaluation after confirming final commercial terms, permissions, data handling, lifecycle status, and edit-screen aliases. Keep Needs Review enabled until a human verifies the published profile.

Capabilities

Key features

REST API for live video ingestion and analysis

OpenAI-compatible chat-completions interface

Frame and time-range references for live streams

WebRTC and LiveKit stream publishing

Hosted and proprietary vision-language models

Stream leases, keepalive, model discovery, and lifecycle controls

Workflows

Use cases

Building real-time video agents

Adding visual understanding to robotics

Analyzing live security or safety feeds

Creating responsive vision-enabled games

Querying recent moments in a video stream

Strengths

Pros

  • OpenAI-compatible API reduces integration friction
  • Hosted models target low-latency inference
  • Multiple vision models share one interface
  • Documentation covers stream reliability and cost controls
Considerations

Cons

  • Public unit pricing is not displayed
  • Model availability changes over time
  • Resolution and frame volume can increase cost rapidly
Considerations

Limitations

Real-time vision output can miss events, misread scenes, or arrive too late for safety-critical action. Developers should design fallbacks, monitor model availability and latency, protect stream credentials, and avoid relying on the service as the sole safety control.

Cost

Pricing details

Pricing modelPaid
Starting priceUsage-based
Free planUnknown
Free trialYes
Pricing context

Billing options

Prepaid creditsUsage-based
Pricing context

Pricing note

Authenticated API calls consume credits and return an insufficient-credits error when the balance is exhausted. Public documentation discusses cost control but does not display stable unit rates, a recurring plan amount, an ongoing free tier, or a trial.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

LiveKit

WebRTC

OpenAI-compatible SDKs

Specs

Technical details

PlatformsAPI, Web
Multilingual supportUnknown
Login requiredYes
Open sourceNo
DeploymentCloud
CompanyOvershoot
Launch year2025
Current versionv1
Models / versionsQwen vision models Gemma vision models Holo3 Gemini Claude GPT
Editions / plansDeveloper API
Data confidenceHigh
Last verifiedJuly 30, 2026
Documentation → Release notes → Data source →
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Answers

Frequently asked questions

Overshoot provides infrastructure for real-time vision applications. Developers publish live video through WebRTC, reference frames or time ranges through an OpenAI-compatible API, and query hosted or passthrough vision-language models with low-latency responses.
Developers building low-latency applications over live video streams
The listed pricing model for Overshoot is Paid. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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