Take the document, invoice, vendor, and compliance workflows that absorb your team's bandwidth and run them on managed AI agents. Configurable by ops, integrated with the existing stack.
Operations managers live in the gap between strategy and execution. The team's bandwidth is consumed by document review queues, invoice processing, vendor coordination, compliance reporting, and the dozen smaller workflows that don't fit a single owner. Beth (in build) is Huper's managed AI agent platform — agents configurable by operations leads (not just developers), integrated with the existing enterprise stack, deployable inside the same security perimeter the security review already cleared. Where the COO office cares about strategic operating model and CISO-grade governance, the operations manager office cares about the workflow-level execution: which queues get cleared, which exceptions get handled, which reports get generated, which integrations stay healthy. Beth ships against that surface.
Workflow-level reliability across document review, invoice processing, vendor management, compliance monitoring, and report generation
Operations-team configurability — agents adjustable without an internal AI engineering build
Exception handling with full context handed back to the operations team rather than failing silently
Real-time visibility into queue depth, processing rates, error rates, and exception escalations
Integration with the existing enterprise stack (SAP, Oracle, ServiceNow, Salesforce, Workday, custom APIs)
Beth's configuration is designed for operations teams, not developers. Workflow rules are expressed in natural language; integrations are pre-built for the major enterprise systems; exception-handling logic is configured via a visual interface. Your team defines what the agent should do in plain English, and Beth handles the underlying agent behavior.
Beth deploys in parallel with existing processes. Agents run alongside current workflows, handling new tasks or absorbing volume from existing ones — no big-bang cutover. Migration happens at the pace your team is comfortable with, with the option to roll back at any point in the pilot.
Each agent has built-in exception handling. When it encounters a scenario outside its configured rules, it escalates to your team with full context — what it saw, what it tried, what it recommends. Over time, you train the agent to handle more exception types, continuously expanding the workflow coverage.
Configurable by operations leads using natural-language rules and visual workflow design — no internal AI engineering required
Parallel deployment alongside current processes; zero big-bang cutover; roll back at any pilot stage
Exception management routes edge cases to your team with full context, not silent failure
Pre-built integrations for SAP, Oracle, ServiceNow, Salesforce, Workday, plus custom-system APIs
Real-time dashboards on queue depth, processing rate, error rate, and exception escalation — manage by exception, not by task
Document review, contract analysis, invoice processing, employee onboarding, internal knowledge base, policy lookup, claims processing, compliance monitoring, vendor management, report generation. See /use-cases for the workflow-by-workflow detail. Most operations managers start with the highest-volume single workflow as the pilot, then expand to additional workflows once the deployment has cleared the security and operational checks.
Yes — that's the design intent. Initial integration setup may need IT help (connecting to the enterprise stack, configuring authentication, establishing the deployment posture). Once that's in place, operations leads can define new workflows, adjust agent rules, change escalation logic, and update integrations through the visual interface without an IT ticket.
Beth and traditional RPA can coexist — RPA is good for fully deterministic workflows; Beth is good for workflows where input shapes vary or context matters. Many enterprise customers run both in parallel during a transition period and migrate workflows from RPA to Beth as the brittleness of RPA on those workflows becomes the bottleneck.
Simple workflows can be automated in a single day once the initial deployment is in place. More complex multi-system workflows typically take 3–5 business days from configuration to production. Pre-built templates cover common operations patterns — document review, invoice processing, vendor onboarding — and accelerate deployment further.
Tell us what you need. We’ll build, deploy, and manage your AI agents — on our cloud or yours.
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