Hiver Omni brings AI Agents, customer context, internal teams and business systems into one environment to enable better resolution for complex, high-stakes support
AI has made it easier for customer support teams to automate simple questions. But when a customer issue requires an investigation, an internal approval, a CRM update or an Engineering fix, the work still moves across people, tools and systems.
This is where many AI implementations reach their limit. An AI agent may identify the problem or draft a response, but the actual resolution still depends on a support representative switching between systems, finding the right information and coordinating with other teams.
Hiver is taking a different approach with Hiver Omni, its agentic omnichannel customer service platform built for complex high-stakes support.
Hiver’s 2026 B2B Customer Support Benchmark Report found that 66.8% of complex tickets require support representatives to consult at least three different tools before acting with full information.
Hiver has spent 10+ years building customer support workflows. Its products are now used by 10,000+ teams and have powered the resolution of 484M+ requests. With Omni, the company is extending that decade-long experience into building an agentic platform that goes beyond deflecting queries.
Most platforms layer an AI assistant onto an existing helpdesk. Hiver’s approach is to build the scaffolding that helps AI work reliably. For example, when a customer reports that a product integration has stopped syncing, an AI Agent can ask clarifying questions, pull relevant account and product information, review previous interactions, investigate the issue, and route it to the appropriate team with the findings attached. Where required, it can also update connected systems or create a Jira ticket.
The difference becomes clearer when a support issue crosses organizational boundaries. A customer may report a billing discrepancy that needs account verification, input from Finance and an update in the CRM. A product issue may require Support to gather details, Engineering to investigate logs and Customer Success to understand the account context.
Instead of treating these as separate handoffs, Omni keeps the work connected to the original customer issue. AI Agents can gather information, follow defined workflows and trigger actions across connected systems, while teams can collaborate within the same case. This means the customer-facing conversation and the internal work required to resolve it no longer have to live in separate places.
The support reps do not have to reconstruct the issue from separate conversations. Engineering, Product or Customer Success can work from the same case, with the relevant context carried through the resolution process. This becomes particularly important as support increasingly works alongside other customer-facing teams. Hiver’s benchmark report found that 59.1% of support teams identify Customer Success or Account Management as their most frequent internal collaborator.
The same approach extends to the knowledge behind support. Hiver Omni uses institutional knowledge from resolved conversations and existing documentation, while helping teams identify gaps or outdated information. This gives AI Agents a stronger foundation for handling requests that require more than a standard response.
The platform also gives businesses control over how much autonomy AI has. Teams can define the procedures AI Agents can follow, decide where human review is required and expand automation as confidence grows.
Hiver’s approach is to make AI part of that entire workflow. The shift is from AI that answers support questions to AI that can work through support problems while people retain control over the decisions that require judgment. For Hiver, the opportunity is not simply to automate more tickets. It is to give AI Agents the environment to do the work that comes after the first answer.
