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Cybersecurity · head to head

Camio vs OpenAI API

Camio logo

Camio

Cybersecurity

AI video search that runs on cameras you already own, starting near five dollars per camera per month

From
$4.99/month
Rated
-
Full reviewWebsite
OpenAI API logo

OpenAI API

Machine Learning

Hosted API for OpenAI's language, embedding, image and audio models, billed per token

From
$0.15/per-million-tokens
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Camio the 4.99 US dollars per camera per month starting rate is genuinely a starting rate: Flex add-ons run from 1 to 89 dollars per stream per month, so a busy camera with detailed vehicle labelling can cost more than fifteen times a quiet one and a site budget built on the headline number will be badly wrong.; OpenAI API cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.
  • They diverge on capability: Camio covers Natural language video search, OpenAI API covers Text and reasoning models.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Camio and OpenAI API actually diverge.

Attributes where Camio and OpenAI API differ
AttributeCamioOpenAI API
Starting price$4.99/month$0.15/per-million-tokens
Pricing modelPer camera per monthusage-based
PlatformsWeb, iOS, Android, LinuxApi
CategoryCybersecurityMachine Learning
FoundedUnknown2015

Identical on both: free tier (No), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Camio

  • Natural language video search
  • Works with existing cameras
  • Free Box software
  • Zone and schedule rules
  • Vehicle and person attributes
  • Retail and queue analytics
  • Alerting integrations
  • Camio Flex add-ons

Only in OpenAI API

  • Text and reasoning models
  • Embeddings
  • Speech and audio
  • Image generation
  • Function calling
  • Structured outputs
  • Batch processing
  • Prompt caching

What people use each for

The jobs each tool is most often brought in to do.

Camio

  • A warehouse that needs an alert when a trailer door opens outside scheduled hours rather than a recording nobody watchesnot OpenAI API
  • A retailer investigating a shrink pattern who needs to find every instance of a behaviour across a month of footagenot OpenAI API
  • A manufacturer wanting a safety alert when a person enters a machine zone during a runnot OpenAI API
  • A property manager who wants search and alerting on an existing camera estate without replacing recordersnot OpenAI API

OpenAI API

  • Adding summarisation, drafting or classification to an existing product where building a model would take longer than the product's whole roadmapnot Camio
  • Retrieval-augmented question answering over internal documents, using the embedding and generation models togethernot Camio
  • Extracting structured records from unstructured text, where schema-constrained output removes most of the parsing problemnot Camio
  • Prototyping a language feature quickly to find out whether it is worth the cost of a self-hosted alternative laternot Camio

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Camio

  • The 4.99 US dollars per camera per month starting rate is genuinely a starting rate: Flex add-ons run from 1 to 89 dollars per stream per month, so a busy camera with detailed vehicle labelling can cost more than fifteen times a quiet one and a site budget built on the headline number will be badly wrong.
  • Camio is analytics and search, not a full video management system, so most sites still need a recorder or VMS alongside it and end up with two products and two bills.
  • The Camio Box gateway must sit on the same local network as the cameras, which means a device, power and network port at every site, and multi-site estates multiply that install work.
  • It is a small private company against Verkada, Eagle Eye and the analytics bundled free into major VMS platforms, so it is structurally exposed to an incumbent bundling equivalent capability at no extra charge.
  • Analytic accuracy depends heavily on the existing cameras’ placement, resolution and lighting, and cameras installed years ago for recording rather than for computer vision often produce detection rates that disappoint against the demo.

OpenAI API

  • Cost scales with tokens rather than with seats, so a successful feature's bill grows with its adoption, and an interface that lets users paste long documents has no natural ceiling on spend unless you build one yourself.
  • Models are deprecated on the vendor's timetable, and a fine-tuned model built on a retired base goes with it, so the tuning work and the data curation behind it must be redone rather than migrated.
  • Behaviour shifts between model versions in ways no test catches unless you wrote one, so prompts tuned over months against a particular snapshot can regress quietly on migration, which makes an evaluation suite a prerequisite rather than an improvement.
  • It cannot run inside your own network, so data residency requirements, air-gapped environments and contracts forbidding third-party processing rule it out regardless of the provider's own security posture.
  • You inherit its availability and its rate limits, so a provider incident is an outage in your product and a traffic spike can be throttled at precisely the moment the feature is proving itself.

Pricing, plan by plan

Camio

$4.99/month
  • Camio usage-based plan$4.99/month
    • Starting rate per camera per month
    • Scales with search, storage and feature use
    • Works with existing ONVIF and RTSP cameras
  • Camio Flex add-ons$undefined/month
    • Optional services from 1 to 89 USD per stream per month
    • High-traffic cameras and detailed vehicle labelling at the expensive end
    • Priced per stream rather than per site

OpenAI API

$0.15/per-million-tokens
  • GPT-4o mini$0.15/per-million-input-tokens
    • Fast
    • Affordable
  • GPT-4o$5/per-million-input-tokens
    • Multimodal
    • 128K context

Which should you pick?

Choose Camio if

  • You need natural language video search.
  • You work on Web, iOS, Android, Linux.
  • You also want works with existing cameras.
Camio review

Choose OpenAI API if

  • You need text and reasoning models.
  • You work on Api.
  • You also want embeddings.
OpenAI API review

Questions people ask

Is Camio or OpenAI API better?
Neither clearly leads. Camio starts at $4.99/month and OpenAI API at $0.15/per-million-tokens, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Camio or OpenAI API?
Camio starts at $4.99/month and OpenAI API at $0.15/per-million-tokens.
Does Camio or OpenAI API run on more platforms?
Camio runs on Web, iOS, Android, Linux. OpenAI API runs on Api.
What is Camio best used for?
Camio is most often used for a warehouse that needs an alert when a trailer door opens outside scheduled hours rather than a recording nobody watches, a retailer investigating a shrink pattern who needs to find every instance of a behaviour across a month of footage, a manufacturer wanting a safety alert when a person enters a machine zone during a run, a property manager who wants search and alerting on an existing camera estate without replacing recorders. Of those, a warehouse that needs an alert when a trailer door opens outside scheduled hours rather than a recording nobody watches and a retailer investigating a shrink pattern who needs to find every instance of a behaviour across a month of footage are not what OpenAI API is typically brought in for.
What can Camio do that OpenAI API cannot?
Camio covers Natural language video search, Works with existing cameras, Free Box software, Zone and schedule rules. OpenAI API covers Text and reasoning models, Embeddings, Speech and audio, Image generation.

Answered from the vendors’ own pages

Camio: Do I have to buy Camio cameras?

No. Camio works with ONVIF and RTSP cameras you already have, which is the main reason to choose it over camera-bundled AI platforms.

OpenAI API: Is my data used to train the models?

API inputs and outputs are not used for training by default, which differs from the consumer product. Retention periods and enterprise terms change, so read the current data usage policy rather than trusting a summary.

Camio: Do I have to buy the Camio Box?

Not necessarily. The gateway software can be downloaded onto hardware you already own; Box and Box Pro units are for sites needing more processing capacity.

OpenAI API: Can I run these models on my own hardware?

No. The weights are not distributed. If self-hosting is a requirement, you are looking at open-weight models instead, with the operational and quality trade-offs that implies.

Camio: What does it really cost?

Plans start at 4.99 US dollars per camera per month, but Flex add-ons run from 1 to 89 dollars per stream per month, so per-camera cost varies enormously by traffic and labelling detail.

OpenAI API: How is it priced?

Per token, with input and output priced differently and each model priced differently. Batch processing and cached input prefixes reduce it. The practical consequence is that your bill is a function of prompt design, not just of request count.

Camio: Does Camio replace my recorder?

No. It adds search and alerting. Continuous recording and evidence retention usually still need a VMS or recorder.

OpenAI API: What is the difference from Azure OpenAI Service?

The same model family delivered by Microsoft under an Azure contract, with Azure identity, networking and regional controls, and a different release cadence for new models. Enterprises with an Azure agreement often choose it for procurement and data residency reasons rather than technical ones.

OpenAI API: How do I keep the cost under control?

Cap input length, cache repeated prefixes, route easy requests to smaller models, use the batch path where latency does not matter, and set per-user limits before launch rather than after the first surprising invoice.

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