Google Cloud Vision, worked by an AI employee
Not another app for your team to learn, and not a set of rules for you to build. You hire an AI employee, you give it access to your Google Cloud Vision account, and you ask it for things in Slack or Teams the way you would ask anyone else on the team. There is nothing to map and nothing to maintain.
- Artificial Intelligence
- Connects with a key
- 23 ready-made tools
- Asked in Slack or Teams
An illustration of how the conversation reads, not a transcript from a client account.
What Google Cloud Vision is
Google Cloud Vision API enables developers to integrate vision detection features into applications, including image labeling, face and landmark detection, optical character recognition (OCR), and explicit content tagging.
You paste in a key from your own Google Cloud Vision account. It is kept encrypted, and you can withdraw it from inside Google Cloud Vision whenever you like.
One message in, the work done in Google Cloud Vision.
- 01
You ask
You message your AI employee in the chat your team already has open, in one sentence, in your own words.
- 02
It works out the step
It decides what the job needs in Google Cloud Vision. You do not pick anything from a menu or wire anything together.
- 03
It does the work
Signed in to your own Google Cloud Vision account, inside the access you granted it, doing the thing you asked for.
- 04
It reports back
It tells you what it did, in the same thread. If it could not do something, it says so rather than guessing.
What it can do in Google Cloud Vision
These are the ready-made tools your AI employee already has in Google Cloud Vision. It is not limited to them, but it never has to be taught these.
- Add Product to ProductSetTool to add a Product to a specified ProductSet. Use after creating both resources in the same project/location to link a product to its set.
- Cancel Vision OperationTool to cancel a long-running Vision API operation. Use when you need to abort a pending or in-progress operation.
- Create ReferenceImageTool to create a ReferenceImage under a product. Use when adding a new image to a product for detection.
- Create Vision ProductTool to create and return a new Product resource. Use when you need to register a product in a specific project/location after preparing product details.
- Delete ProductTool to permanently delete a Product and its reference images. Use after confirming the product's resource name.
- Delete Product SetTool to permanently delete a ProductSet. Use after confirming the ProductSet's resource name.
- Delete Reference ImageTool to permanently delete a reference image. Use when you have confirmed the reference image's resource name.
- Delete Vision API OperationTool to delete a long-running Vision API operation. Use after confirming the operation name.
- Get ProductTool to get information associated with a Product. Use when you have the product resource name and need its details.
- Get Product SetTool to get a ProductSet. Use when you need metadata details of an existing ProductSet by its full resource name. Use after obtaining the resource name.
- Get Reference ImageTool to get information associated with a ReferenceImage. Use when you have the full resource name and need its metadata.
- Get Vision API OperationTool to get the latest state of a long-running operation. Use after starting an async Vision API operation to poll its status.
- Import Product SetsTool to asynchronously import reference images into ProductSets from a CSV in GCS. Use when you need to bulk import images into product sets via a Cloud Storage CSV.
- List IndexEndpointsTool to list IndexEndpoints in a project and location. Use when you need to retrieve existing IndexEndpoints and handle pagination.
- List LocationsTool to list available Vision AI service locations for a project. Use when you need to discover supported regions before making region-specific API calls.
- List Products in ProductSetTool to list Products in a specified ProductSet. Use when you need to retrieve Products associated with a ProductSet after confirming it exists, with optional pagination.
- List ProjectsTool to list Google Cloud projects accessible by the authenticated user. Use when you need to enumerate available project IDs and resource names before performing further operation
- List Reference ImagesTool to list reference images for a product. Use when you need to retrieve stored reference images under a specified product resource name, with optional pagination.
- List Vision API OperationsTool to list operations that match the specified filter. Use when you need to retrieve all operations under a specific project and location.
- Purge ProductsTool to asynchronously delete products in a ProductSet or orphan products. Use when you need to clean up products at scale; ensure force is true to execute.
- Remove Product from ProductSetTool to remove a Product from a specified ProductSet. Use after creating both resources in the same project/location to unlink a product from its set.
- Update ProductTool to update a Product's mutable fields: displayName, description, and productLabels. Use after confirming the product resource name.
- Update Product SetTool to update a ProductSet resource. Use when you need to modify the displayName of an existing ProductSet.
You stay the boss of your Google Cloud Vision account.
Nothing connects until you approve it. You grant access one app at a time, you can take it back the same way, and everything your AI employee does in there is written down where you can see it.
How we handle your data- It signs in to your own Google Cloud Vision account. You are not moving anything into ours.
- You grant access one app at a time, and you can take it back the same way.
- Everything it does in Google Cloud Vision is written down, with what it did and when.
- Anything you tell it to check with you first, it checks with you first.
It works in Google Cloud Vision and the rest of your software in the same job
A real job rarely stays in one place. Reading a message in one app, checking a record in another and writing the result in a third is one request to your AI employee, not three.
Questions people ask about Google Cloud Vision
- Can an AI employee really work inside Google Cloud Vision?
- Yes. It signs in to your own Google Cloud Vision account and works in it the way a new hire would, from the chat your team already has open. Nobody installs anything, and nobody learns a new screen.
- Do I have to move anything out of Google Cloud Vision?
- No. Nothing moves and nothing is replaced. Your records stay in Google Cloud Vision, your team carries on in the same screens they used yesterday, and your AI employee works alongside them in there.
- How does it get into my Google Cloud Vision account?
- You paste in a key from your own Google Cloud Vision account. It is kept encrypted, and you can withdraw it from inside Google Cloud Vision whenever you like. You approve it before anything connects, and you can take the access back the same way you gave it.
- What can it actually do in Google Cloud Vision?
- It has 23 ready-made tools in Google Cloud Vision today, among them Add Product to ProductSet, Cancel Vision Operation and Create ReferenceImage. The full list is on this page. It is not limited to those, but it never has to be taught them.
- Can it use Google Cloud Vision and the rest of my software in the same job?
- Yes, and that is usually the point. Reading a message in one app, checking a record in Google Cloud Vision and writing the result somewhere else is one request to your AI employee, not three separate ones you stitch together.
- Who decides what it is allowed to do in Google Cloud Vision?
- You do. You grant access one app at a time and can withdraw it at any time, anything you ask it to check with you first it checks with you first, and everything it does in Google Cloud Vision is written down with what it did and when.