AI chatbot for SaaS and software companies

API documentation can be used as knowledge content when it is supplied through a supported source such as website content, a document or a manual entry. Clear version labels, authentication requirements, parameter definitions and examples improve retrieval. The assistant explains what the documentation says; it does not automatically execute API calls or inspect a customer's request. Keep secrets and private credentials out of the knowledge base, and route account-specific debugging to an engineer.

GoBrise provides an embeddable website chat widget installed with a JavaScript snippet. It can sit inside a web application where that application allows the script, and the experience combines AI replies with human takeover in one thread. It is not a claim of feature parity with Intercom's broader Messenger ecosystem, mobile SDKs or outbound tools. If you require native mobile support or a particular framework integration, confirm that requirement before rollout.

Yes, provided those distinctions are explicit in the source material. A useful article says which plans include the feature and which software versions the steps apply to. Do not rely on an old page title or an implied release date. Test questions that mention each plan and version. If the user's entitlement is private account data rather than something stated in the conversation, an agent or secure integration must verify it.

Not merely because the widget is embedded in your application. The public assistant is designed to answer from approved knowledge content. Accessing a private account, subscription state, logs or billing record requires a deliberate, authenticated integration and appropriate authorisation. Unless that capability has been confirmed for your setup, the safe workflow is to collect context and hand the conversation to a support agent who can use your existing internal tools.

The assistant can provide documented troubleshooting steps when the symptoms match approved material. It should not claim that a defect is confirmed or invent a workaround from weak evidence. An uncertain, unsupported or account-specific issue escalates into the shared inbox with the prior conversation attached. Once an agent or engineer responds, the AI remains silent in that thread so technical investigation can continue without automated interruptions.

On Growth and higher plans, website crawling and automatic knowledge updates can keep indexed web content aligned with published changes. Other sources and lower plans need manual maintenance. Automation does not remove editorial responsibility: release notes should identify changed behaviour, old instructions should be removed or marked by version, and important questions should be re-tested after a release. A crawler can ingest a contradiction just as easily as a correct update.

Multiple AI agents are available on Growth and higher plans. A SaaS company might separate public pre-sales questions from existing-customer setup guidance, giving each agent a focused source set and instruction boundary. That can reduce irrelevant retrieval, but it still requires careful routing and maintained content. Confirm the current plan allowance and design the handoff path before splitting a single well-tested assistant into several agents.

One AI conversation is the complete back-and-forth session, not each individual message inside it. A user can ask an initial setup question and several follow-ups within that session and it counts once. Conversations handled only by people are not counted as AI conversations. The current published plans include 500 per month on Starter, 2,000 on Growth and 7,500 on Business, with optional top-up credits and custom Enterprise limits.

Yes. A user can ask for a person, and the assistant can also escalate when it lacks support for a useful answer. The agent receives the same thread instead of asking the user to repeat the issue. Human live chat is available on every plan, including Free. After an agent reply or takeover action, the AI does not resume in that conversation, regardless of later status changes.

Use a set of real questions covering onboarding, configuration, billing, limits, API versions, recently changed features and genuine bug reports. Score whether the answer is correct, complete and supported by current documentation, and whether unsafe cases hand off. Test follow-up questions because context errors often appear on the second message. Involve support and product owners in reviewing misses; the right fix is often clearer documentation rather than a looser AI instruction.