What is a Product?
A product in Galtea represents a functionality or service that you want to evaluate. Examples include QA chat, Summarization, or Content Generation.Even if your organization has a single public-facing product (like a website or dashboard for all user interactions), you should define separate Galtea products for each distinct functionality you want to evaluate.
SDK Integration
The SDK allows you to list existing products, retrieve specific products by their ID or name, and delete products. Product registration is done through the Galtea dashboard. See the Product Service API documentation for more details.Product Service SDK
Manage products using the Python SDK
Product Properties
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The name of your product.
Example: “Document Summarizer”
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Write what the product must do and what you want to test or evaluate: what it must get right, what it must refuse, and where it must be accurate.
Learn how to write effective product descriptions in our detailed guide.Example: “A mobile sales assistant for smartphones. It must recommend only phones that are in stock, never quote a price it cannot find in the catalog, and hand over to a human when the customer asks about an existing order.”
- What to include: The behaviors that must hold, the limits the product must respect, and the results that must be correct.
- What to avoid: A marketing summary. Concrete behavior produces specific specifications; a summary produces generic ones that would fit any AI product.
Learn how to write effective product descriptions in our detailed guide.
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List what your product is designed to do and what information it has access to. This helps Galtea generate targeted test cases.Example: “Can answer questions about phone specifications, recommend devices based on user preferences, can access past user purchases, compare prices across models, and provide information about warranties and accessories.”
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List what your product cannot do — information it does not have access to, tools it cannot use, and its general scope boundaries. This prevents generation of irrelevant or misleading test cases.Example: “Cannot process purchases, access customer account information, or provide technical support for device repairs.”
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Define specific rules and instructions for how the product must behave in certain situations. Policies ensure consistent, safe, and compliant responses.Example: “If asked for guaranteed investment returns, respond that all investments carry risk. Always end investment advice with a ‘consult a professional’ disclaimer.”
Policies consist of clear instructions, such as “always answer with x if asked about y” or “add [specific disclaimer text] at the end of your responses when asked about z.”
Enum
The risk level of the product under the EU AI Act.
Possible values:
GPAI: General-Purpose AI Model (Article 3(63), Title VIII A - Chapter 1).GPAI Systemic: General-Purpose AI Model with Systemic Risk (Article 52a, referring to criteria in Article 52c).Special System: AI Systems with Specific Transparency Obligations (Article 50).High: High-Risk AI System (Article 6, Annexes I & III).Prohibited: Prohibited AI Practices (Article 5).Legal definitions available in the Rules for trustworthy artificial intelligence in the EU.
Enum
The operator type of the product under the EU AI Act.
Possible values:
Authorised Representative: An entity established in the EU, appointed by a provider from a third country, to act on their behalf regarding AI Act obligations.Deployer: An entity that uses an AI system under its authority, except when the AI system is used in the course of a personal non-professional activity.Distributer: An entity in the supply chain, other than the provider or importer, that makes an AI system available on the Union market.Importer: An entity established in the EU that places on the market or puts into service an AI system bearing the name or trademark of a person established outside the Union.Product Manufacturer: The manufacturer of a product that incorporates an AI system.Provider: An entity that develops an AI system or that has an AI system developed and places it on the market or puts it into service under its own name or trademark.Legal definitions available in the EU AI Act.
Enum
Which sessions Galtea closes automatically after they stay inactive too long. Set it through the API; the SDK only reads it.
Possible values:
None: never close sessions automatically.Development: only close development (test) sessions.Production: only close production sessions.All: close both development and production sessions.The API default isProduction.
Number
How many minutes a session can stay inactive before Galtea closes it automatically.
The API default is
30.Enum
What happens when you try to add an inference to a session that is already closed.
Possible values:
Reopen And Reevaluate(the default): keep the inference and open the session again. The session’s monitor evaluations move to theOutdatedstatus, so a Monitor scores the session again once it closes for good. Only production sessions reopen; a development (test) session is dropped as withIgnore.Reject: refuse the inference and return an error.Ignore: silently drop the inference.The API default isReopen And Reevaluate.
How Everything Connects
The cross-entity diagram now lives on the Concepts overview — see it there along with reading guidance and per-entity links.Related
A product in Galtea is associated with:Concepts overview
How Galtea’s concepts connect — diagram + per-entity quick reference.
Version
A specific iteration of a product
Dataset
A dataset of test cases for evaluating product performance
Specification
A testable behavioral expectation for a product