What is an enterprise AI chatbot?
An enterprise AI chatbot is a shared AI assistant for a team, not a per-seat license for one person.
A search box on a single Claude or ChatGPT seat is not an enterprise AI chatbot. Three properties separate the category: shared by default (one agent serves the whole team in the channel they already use, no per-seat browser tab to open), connected to the stack (reads documents, tickets, CRM records, and dashboards with the requester's permissions, not a god-mode service account), and auditable (every prompt, tool call, and reply is logged so compliance can answer 'what did the agent say to whom' without forensic archeology).
How is it different from ChatGPT or Claude?
Runbear gives the team shared agents, governed access, and an audit log. Three things per-seat licenses can't ship.
ChatGPT and Claude solve the individual problem: one person, one browser tab, one conversation. They do not solve the team problem. Runbear runs as a shared teammate inside Slack and Microsoft Teams. The team's memory lives with the team (scoped by channel and role), not per-user inside a private account. Stack reads use the requester's own permissions, not a god-mode service account. And every prompt, tool call, and reply is logged and SIEM-exportable. Per-seat licenses ship none of these.
What enterprise teams use it for
Most teams roll out Runbear inside the channel where the work is already happening: CS in #cs-questions, on-call in #incidents, HR in #ask-people.
Four shapes anchor most enterprise deployments. Customer support inside Slack: the CS team @mentions the agent in a channel, the agent answers from the knowledge base, retrieves the customer record, and drafts a reply, with about 15% of questions routing to a human in-channel within 30 seconds when the agent doesn't know. Internal help desk: HR, IT, and Finance route their FAQ to one agent; employees ask in Slack, the agent answers from policy documents and ticket history. Sales and revenue ops: account executives ask for a competitor brief or pricing comparison in the deal channel; the agent reads the CRM and the latest battlecards. Engineering and on-call: the agent watches an alert channel, correlates against runbooks, and proposes the next-step command for a human to approve.
Security and compliance
Runbear ships with the controls enterprise security teams actually gate on: SOC 2 Type II, per-user auth, full audit log, and approval gates on sensitive actions.
SOC 2 Type II is in production, with the annual audit available on request under NDA. Per-user auth on shared agents means that when the agent retrieves from Notion, Google Drive, or Salesforce, it reads with the requester's own permissions: a finance analyst asking for a deal record only sees what they would see in Salesforce directly. Data is encrypted at rest and in transit, retained 30 days by default, and never used to train upstream models. Every prompt, tool call, reply, edit, and human correction is logged and SIEM-exportable. Sensitive actions (refunds, deletes, outbound sends) require an explicit human approval gate before the agent executes.
Deployment time and rollout
There is no engineering ticket. A team lead connects Slack and the team's tools in plain English, and the agent auto-configures itself.
The full rollout shape on a typical enterprise: a workspace admin clicks the install link (one install covers the whole team), the team lead lists the tools the agent should read in plain English in the configuration channel (Notion, Confluence, Google Drive, Salesforce, HubSpot, Zendesk, GitHub, and more), the agent answers in the channel from day one while the team rates answers up or down so the agent reads the corrections and improves, then governance gates get layered as adoption grows: topic gates lock the agent to specific channels, approval gates wrap the actions that move money or delete records. Most teams have their first answer in production in under 30 minutes. The first 30 days is the adoption curve, not the build curve.
Cost and pricing posture
Runbear charges by capacity, not per seat. Because adoption is what compounds, not seat utilization.
Per-seat licenses are an adoption tax: when you pay $30 per user for an AI seat, you have to drive every user to log in every month to make the math work. Most enterprise deployments do not hit that bar. Runbear charges by capacity, not per seat: the shared agent serves the whole team, and adoption is what compounds. Two tiers today: general teams at $399/mo+ and Business+ for teams that need dedicated SLAs and white-glove rollout at $2K/mo+.
