Beth's managed AI agents handle the high-volume back-office workflows that scale linearly with growth — without your team scaling linearly to match.
Most enterprise back-office work scales linearly with revenue: more customers means more vendors, more contracts, more documents, more compliance touchpoints, more invoices to process. Beth (in build) deploys managed AI agents on those high-volume workflows so the operations organization can absorb growth without absorbing proportional headcount. Each agent runs inside the existing security perimeter with audit-grade decision trails, deterministic guardrails, and deployment posture chosen against the security team's review.
Adding back-office headcount to absorb growth costs $80K–$150K fully loaded per role at enterprise pay bands, plus 12–18 months of onboarding to full productivity. Companies scaling through headcount alone see operational margins compress 15–25% during growth phases. Beth's consumption-based pricing scales with workflow volume rather than seat count, decoupling operational capacity from team size.
Beth identifies the back-office workflows that consume the most operator hours (document review, contract analysis, vendor onboarding, claims, compliance monitoring), maps them to managed agents, and deploys those agents inside the existing enterprise stack with the deployment posture the security review approves. Workflows that previously required an FTE per shift run autonomously with exception escalation to humans on the boundary cases.
Identify the back-office workflows that are bottlenecking growth — document review queue depth, vendor onboarding cycle time, contract review backlog, compliance monitoring coverage gaps.
Scope a pilot on the highest-leverage workflow with the security team's deployment-posture decision (cloud SaaS, VPC, on-premise, air-gapped) and the integration plan against the existing enterprise stack.
Deploy managed agents on the pilot workflow inside the security perimeter. Agents reason about workflow context, escalate exceptions with full context, and produce audit-grade decision trails.
Once the pilot workflow is stable, expand to additional workflows in priority order. Stakeholder cohort and integration patterns from the pilot inform faster deployment of subsequent workflows.
Most pilots start with a single high-volume workflow that has clear cycle-time and error-rate baselines — document review, contract analysis, invoice processing, employee onboarding, internal knowledge base, claims processing, compliance monitoring, vendor management, or report generation. Pilot typically runs in 4–6 weeks including security review and integration with the existing enterprise stack.
Yes. Beth and traditional RPA can coexist; Beth handles the workflows where input shape varies or context matters, RPA handles the fully deterministic ones. Many enterprises run both in parallel during a transition.
Tell us what you need. We\u2019ll build, deploy, and manage the AI agents to fix it.
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