Workflows across your stack, without custom code.

Most of what an HR team does repeatedly should not need a person: the reminder before a document expires, the escalation when a clearance task goes overdue, the monthly report somebody rebuilds by hand. Automations handle those, and agentic AI workflows carry the longer ones end to end.

Agentic AI in production, not on a roadmap slide.

ISO 27001 & AICPA SOC 2 certified

What can be automated

Reminders & nudges

Overdue escalations

Scheduled reports

Multi-step approvals

Agentic AI workflows

Cross-system triggers

Because workflow logic is data rather than code, automations differ per organisation without forking the product.

Three levels

From a nudge to an agent

Rules and reminders

The simplest and highest-volume layer — the work that only needs doing because somebody has to remember it.

Document expiry alerts before a permit or ID lapsesOverdue clearance tasks escalated to a managerPending approvals nudged before they block a cycleScheduled reports delivered without a request

Multi-step workflows

Approval logic is configured as data, so a chain can differ by department, site or amount without anybody writing code.

Different approval chains per capabilityConditional routing by role, site or valueParallel task assignment across teamsConfigured once, applied every time

Agentic AI workflows

Agents that carry an HR process from trigger to completion — gathering what they need, and handing back to a person when they should.

Already running in production, not a pilotHands back rather than guessing at the edgeAuditable: every action stays on the recordExpanding across more capabilities

The design point

Why automation here is configuration, not code

In most platforms, "workflow automation" means a fixed set of triggers the vendor decided everybody needed. Anything outside that becomes a customisation request, and customisation requests become technical debt that breaks at the next release.

Bhivo treats workflow logic the same way it treats organisation structure: as data. That is why approval flows can differ per customer without forking the product, and why an automation you configure this year still runs next year. It is also why the honest limit is worth stating — an automation has to be expressible in the workflow layer. Where something genuinely is not, the services team builds it against real extension points rather than hard-coding a special case.

On AI specifically: agentic workflows are in production and in real use. What they are not is a replacement for judgement. The design principle is that an agent completes what it can and hands back to a person at the point where a human decision belongs — which is a deliberate constraint, not a limitation we are working around.

Automate the work nobody should be doing

Reminders, escalations, scheduled reports and multi-step approvals, configured to your process — plus agentic workflows for the longer chains.