Cited answers from company sources
qbrin reads across company documents and knowledge sources and returns answers with links back to the exact source. The product messaging repeatedly stresses grounded output rather than uncited guesses.
qbrin is an enterprise AI search and governed agent platform that turns company knowledge into cited answers and can abstain when evidence is missing.
qbrin is an enterprise AI search and agent platform focused on grounded answers and governed actions. Its core promise is to turn scattered company knowledge into cited responses that can either prove the answer from connected sources or abstain when the evidence is missing.
The homepage positions qbrin as a product for asking real workplace questions across documents, email, chat, and other company sources, while the agents page expands that idea into governed AI agents that can act with identity, policy checks, observability, and sandboxed execution. The pricing page shows a flat, seat-based model with Starter, Team, and Enterprise plans for teams that want a source-of-truth workspace, not per-query metering.
qbrin reads across company documents and knowledge sources and returns answers with links back to the exact source. The product messaging repeatedly stresses grounded output rather than uncited guesses.
When the records do not support an answer, the system is designed to abstain instead of guessing. This behavior is central to both the homepage and agents page positioning.
The agents page describes a control plane with identity, activity, observability, governance, and least-privilege security. Every agent gets a stable principal, a named human owner, and a structured reasoning trace.
Policies are checked before actions such as reading, writing, code execution, and sending messages. Higher-risk actions can pause for human approval, and default-deny behavior is shown for writes, code, and sends.
Untrusted code runs in a sealed sandbox with no filesystem, network, or host-process access and a hard timeout. The page presents this as containment for agent-written code.
The pricing page highlights read-only connectors, saved answers and collections, go-links and shared collections, permissions that mirror source tools, and priority support on higher tiers.
A team can connect a knowledge source read-only and ask recurring questions like policy, account, or project-status queries. qbrin is designed to return a sourced answer fast enough for live work, while abstaining if the evidence is missing.
The product examples show onboarding, policy, meeting prep, and account briefing. These scenarios suggest qbrin is useful when someone needs a concise briefing drawn from emails, docs, threads, and notes before a call or decision.
The agents page describes agents that can join Slack, ask clarifying questions, file Jira tickets, and pull keys from a vault under policy control. That makes it suitable for teams that want agents to do bounded work rather than only chat.
The Enterprise tier is described for regulated and security-first organizations that need SSO, SCIM, audit logs, and custom data residency. This makes qbrin relevant where access control and traceability matter as much as answer quality.
The pricing page emphasizes saved answers, collections, and shared go-links, which fit teams that want repeatable knowledge artifacts instead of one-off search results.
qbrin is presented as a governed enterprise AI search product that connects to company sources read-only and returns cited answers. The homepage and pricing page both emphasize that it can answer with sources, and the pricing page says it is designed to go live in minutes once connected.
The pricing page shows tiers for Starter, Team, and Enterprise. Starter is framed for a single team, Team for growing companies, and Enterprise for regulated or security-first organizations that need self-hosting or local-first deployment options.
The source text shows a walkthrough flow where qbrin connects one source read-only and answers a real question without changing existing tools. The agents page also describes it reading across docs, chat, and email to ground answers and actions.
qbrin is described as citing sources or abstaining when records do not support an answer. On the agents page, this is stated as '100% confidence cited, or it abstains,' and the product copy says it should not confidently answer when it lacks evidence.
The pricing page says Enterprise includes SSO, SCIM, audit logs, custom data residency, and a self-hosted or local-first option. It also says customer data is never used to train anyone else’s models.
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