# Scan: Automaise Conversational AI > GAMMA-Ray v0.0.155 (beta, for review; every rating is experimental). An example GAMMA-Ray beta rating of Automaise Conversational AI: freedom 1, 4 across its configurations; deployment governance not assessed. > Page: https://gamma-ray.sgit.ai/scans/automaise-conversational-ai/ · Source: data/scans/automaise-conversational-ai.json Example · beta rating · a product as its vendor documents it · read 2026-11-10 · not seen by the vendor Voice and chat assistant (inbound and outbound voice, customer self-service chat, internal helpdesk chat) that answers customers and completes transactions such as data changes, payments and orders. A scan of a product as its vendor documents it, not of any one deployment. Made by the report studio: a researcher-assessor, a challenger, then the scorer. Part of the first Portuguese cohort. Built only from Automaise (Automaise S.A.)'s own public pages (product, documentation, blog, customer stories, legal and security pages). Nothing was tested. If you are the vendor and something here is wrong, the correction will be made and dated. *Figure. The label for this rating; its contents are in the text.* 1 Freedom as shipped Answers 4 Freedom at most Acts widely 2 Controls it brings as shipped n/a Deployment governance not assessed ## How to read it This is a product, not a deployment. A product has no owner, no policy in force and no mandate until somebody runs it, so it is given **no governance level and no level held**: those belong to a deployment. What a product has is a freedom level for each way it can be configured, and a list of the controls each configuration brings. *Figure. The freedom level of each configuration; the table has the same.* | Configuration | What changes | Freedom | Controls | Turned on by the operator | |---|---|---|---|---| | **As shipped** | Conversational AI with its documented defaults. | 1 Answers | 2 | nothing | | **Connected systems** | A deployment connected to the operator's own CRM, contact-centre or messaging platforms; the connection is built per deployment. | 4 Acts widely | 2 | it executes actions itself; it works across several domains or systems | The same product is a different agent in each row. A rating of a deployment starts by saying which row it is. An indicator with no evidence is reported as not evidenced; it is never read as a no. ## The profile *Figure. One square per indicator, by question; every answer is listed below.* ## The grant: what it can actually do The questions measure what is said about an agent: its purpose, its rules, its controls. The grant is the other half: what its permissions let it do, capability by capability, and what stands in the way of each. This is RiskMandate's measurement, and it depends on the permissions a deployment was given. **Not measured.** Not measured. No deployment shape for this product is published in the capability grammar. ## Seen, and not credited - Named connectors or an integration list for the CRM, CCaaS and messaging connections (would strengthen I10 and Reach 2) The product page names categories only; no connector, integration list or integration documentation was found in the scan's sources. [Source](https://site.automaise.com/conversational-ai) - Approval of critical decisions only (I18) The FAQ escalation text has a person take over the conversation, not approve a decision; it supports I17 only. [Source](https://framerusercontent.com/sites/2oOCAmSqmUJsdceu4ef5J/Qq644o6Aab6qlVpuxwnOdBYCwMeQYtwb4UBEDaOYKYc.uN0Y50vq.mjs) - Third-party messaging channels named in the service terms (I11 connects to external tools or services across a trust boundary) The terms describe the company's Virtual Employee platform answering on channels (Facebook Messenger, WebChat, Twitter, E-mail, WhatsApp, etc.); a channel it answers on is its interface, not a tool it calls, and the page does not tie that text to Conversational AI. Reach 2 rests on I10. [Source](https://www.automaise.com/legal/privacy-policy) ## What its evidence reaches *Figure. The mashup graph with this agent's evidenced indicators lit.* ## Every answer, with its source ### What is the agent built on? - *Not evidenced.* It is a vendor's assistant, used as supplied. - *Not evidenced.* It runs on an AI platform with the organisation's own data, without executing arbitrary code. - *Not evidenced.* It is configured on a low-code or no-code builder and acts on real organisational data. - *Not evidenced.* It generates and executes code with local or cloud privileges. - *Not evidenced.* It is built in-house: the organisation controls its identity, tools and boundaries. ### Does it act, or only answer and recommend? - *Not evidenced.* It follows fixed rules, with no reasoning. - *Not evidenced.* It retrieves information and recommends actions; a person acts. - **Available, if the operator turns it on.** It executes actions itself. The product page says, in one vendor sentence with no named customer, that data changes, payments, orders and service subscriptions are completed end-to-end by the AI with no agent stepping in; it does not say through which systems, and the connected-systems configuration is the scan's inference. [Source](https://site.automaise.com/conversational-ai) (documented) - **As shipped.** It is in production: a public source names a customer or gives usage figures for what it does on its own. CTT, a named customer, uses the chat assistant to resolve account access issues itself (password recovery, unblocking accounts, new passwords); the page gives 93% as the automation rate of all webchat interactions. [Source](https://site.automaise.com/use-cases/via-ctt) (documented) ### How far does it reach? - *Not evidenced.* It works in one domain's data. - **Available, if the operator turns it on.** It works across several domains or systems. The product page says Conversational AI connects with CRM, contact-centre (CCaaS) and messaging platforms; it names these categories only, and no named connector or integration list was found in the sources. [Source](https://site.automaise.com/conversational-ai) (documented) - *Not evidenced.* It connects to external tools or services across a trust boundary. ### Does it work with other agents? - *Not evidenced.* Several agents coordinate inside the organisation. - *Not evidenced.* Agents operate across organisational boundaries or disparate stacks. - *Not evidenced.* There is a published protocol or communication layer between agents. - *Not evidenced.* Others build on it: third parties publish integrations, skills or agents for it. - *Not evidenced.* It exposes an agent interface: a published MCP server, an agent card, or an API documented for agents to call. ### What is the person's role? - *Not evidenced.* The person operates: every action is prompted and controlled by them. - *Not evidenced.* The agent suggests; the person reviews and approves each action. - **As shipped.** The agent handles routine tasks; the person is consulted on exceptions. The FAQ says requests that follow a predictable flow are handled autonomously, and that a conversation needing human intervention passes to an available agent with its context (the FAQ text is in the product page's script file, captured as it loads). [Source](https://framerusercontent.com/sites/2oOCAmSqmUJsdceu4ef5J/Qq644o6Aab6qlVpuxwnOdBYCwMeQYtwb4UBEDaOYKYc.uN0Y50vq.mjs) (documented) - *Not evidenced.* The agent works independently; the person approves critical decisions only. - *Not evidenced.* The agent has full autonomy within boundaries; the person monitors. ### Is what it is for written down? - **As shipped.** Its purpose and permitted tasks are stated in writing. The FAQ lists the types of request the assistant handles on its own. [Source](https://site.automaise.com/conversational-ai) (documented) - *Not evidenced.* Its autonomy limits and the tools it may use are defined. - *Not evidenced.* Its limits and known failure cases are documented for those who use it. ### Does it have its own identity and only the access it needs? - *Not evidenced.* What it can reach is enumerated: scopes, permissions, tools. - *Not evidenced.* Its authorisation is published as metadata that anyone can read. - *Not evidenced.* It asks for narrower access than the whole account. - *Not evidenced.* It has its own identity, separate from any person's. - *Not evidenced.* Its identity is cryptographic and can be checked by others. - *Not evidenced.* Its tokens are bound to the service they were issued for and are not passed on. ### Is it in a registry, with an owner? - *Not evidenced.* The organisation keeps a registry of its agents. - *Not evidenced.* Each agent has a named owner. - *Not evidenced.* Agents are retired by a defined process. ### Who is accountable for it? - *Not evidenced.* A named executive or body is accountable for the organisation's agents. - *Not evidenced.* Roles and responsibilities for AI risk are documented. ### Is there a policy that governs it? - *Not evidenced.* A governance policy for agents is published. - *Not evidenced.* Agents and use cases are classed by risk. - *Not evidenced.* The laws that apply to it are identified. - *Not evidenced.* New agents pass an approval or review before they run. ### Can a person step in or stop it? - *Not evidenced.* High-impact actions need a person's approval. - *Not evidenced.* There is a way to pause or stop it. - *Not evidenced.* There is a defined escalation path. ### Is what it does logged? - *Not evidenced.* Its actions are logged. - *Not evidenced.* The log is tamper-evident and kept for a stated time. ### Is it watched while it runs? - *Not evidenced.* It is monitored in operation. - *Not evidenced.* Anomalies are detected in real time and raise alerts. ### What stands between it and what it should not do? - *Not evidenced.* A limit on it is enforced by something outside its own reach. - *Not evidenced.* A limit on it is a setting that its own account could change. - *Not evidenced.* A limit on it is a rule in prose. - *Not evidenced.* Policy is enforced as machine-readable rules. - *Not evidenced.* The difference between what it can reach and what it is for is stated. ### Is it tested, and are the results shown? - *Not evidenced.* Test or evaluation results are published. - *Not evidenced.* It is tested for safety and security, including by attack. - *Not evidenced.* People who did not build it take part in assessing it. ### What happens when it goes wrong? - *Not evidenced.* There is an incident process for agents. - *Not evidenced.* Incidents and errors are communicated to those affected. - *Not evidenced.* There is a plan for a failure of a third party it depends on. ### Do people know it is an AI, and can they answer back? - *Not evidenced.* It tells the people it talks to that it is an AI. - *Not evidenced.* There is a channel to report problems with it or contest its output. - *Not evidenced.* It is machine-readable for agents: it publishes an llms.txt, an AGENTS.md, an API description or an agent card. ### What data does it use, and under what rules? - **As shipped.** The data it uses is described. The service terms define Customer Data as what a business provides to the service, including assistant configurations, frequent questions' answers and messages, and the data of its end users. [Source](https://www.automaise.com/legal/privacy-policy) (documented) - *Not evidenced.* There are data quality rules for what it reads. - *Not evidenced.* Its privacy risk has been examined. ### What does it depend on from others? - *Not evidenced.* The models and third-party components it uses are listed. - *Not evidenced.* Third-party components are monitored and have risk controls. ### Has anyone independent checked? - *Not evidenced.* A public certificate or audit report covers it. - *Not evidenced.* Compliance evidence is produced continuously, ready for a regulator. ### Is the organisation behind it ready? - *Not evidenced.* There is a stated strategy for agents. - *Not evidenced.* The people who work with it are trained. - *Not evidenced.* Its value is measured. - *Not evidenced.* It is improved on a regular cycle. - *Not evidenced.* The organisation's risk management covers agents. ## The vault This rating, its evidence list, its grant and the questions it was made against are kept in a public sgit vault (`gn938lnr`, published 2026-11-10). Anyone can read it with this key: `sgit_public_read_ac0df2472fde834f3552fd90441fa936ba011f083701d052d32d69a8b44ef30d:gn938lnr` With [sgit](https://sgit.ai/): `sgit clone sgit_public_read_ac0df2472fde834f3552fd90441fa936ba011f083701d052d32d69a8b44ef30d:gn938lnr`. The key reads; it cannot write. An operator who wants to add what only they hold forks the vault into a private one.