Know when you can trust AI output.

Yes. Connect zenture once, then ask @zenture right in your ChatGPT or Claude conversation, without switching tabs. zenture is also available in its web and iOS apps and through API and MCP. One account and one credit balance follow you everywhere, and the same reliability standard applies whichever AI model wrote the answer.

No. In ChatGPT or Claude you ask @zenture in the conversation. zenture receives your task and the answer, reviews both, and your assistant brings the result back into the same chat. In the zenture apps, the evaluation sits right next to the answer.

zenture is an independent, unbiased, provider-neutral reliability layer, not another AI model producing a second answer. It runs on its own evaluation engine, business logic, data and compute infrastructure, built to examine the response you already have against its claims, sources and requirements rather than generate a new one. That is what makes zenture AI reliability infrastructure, not another AI application.

No. Models help weigh the evidence, but the decision follows fixed rules. Unresolved ambiguity in your task goes to human review. Missing or unavailable evidence means “not enough evidence”. Material findings or failed checks mean “revise”. Only what clears all of them is ready. The same rules apply to every answer, whichever model wrote it.

zenture checks what an answer claims against the sources it cites and against your task, and flags every claim the evidence doesn’t carry. It won’t catch every error, and it always shows what it couldn’t check, so an unverified claim never looks verified.

zenture evaluates claims, sources, requirements and the overall reliability of an AI answer. It retrieves the accessible sources an answer cites and checks whether each one supports its claim. It separates supported evidence from weak, restricted or unavailable material and never treats an inaccessible citation as verified. It also checks whether the answer did what your task asked, and names the next step. Explore the product

No. zenture does not guarantee that an AI answer is correct. It evaluates the available evidence, identifies unsupported or uncertain claims, checks requirements and explains the result. Users keep decision authority and can see what is reliable, what needs review and which limitations remain before acting on the answer.

zenture is built for people who answer for their work, in consulting, legal, finance, research or any client-facing role. It doesn’t replace your judgement or certify truth. It shows what a result rests on, what’s missing and what still needs review, so you can stand behind your decision and explain it.

zenture data is stored on servers in Germany, and customer conversations are not used to train a general-purpose AI model. Data is processed only to provide and protect the service. The Trust Center, Privacy Policy and subprocessor information give the authoritative details. Read the Trust Center

Yes. Teams can define organisation-specific evaluation standards that apply the same requirements across tools, providers and workflows. In agentic workflows, zenture evaluates automated steps and intermediate results, not only the final answer, so automation keeps its traceability, visible uncertainty and human decision authority. Explore reliable AI operations