What We Solve
Agentic Workflow Reinvention
Don't automate yesterday's process.
Redesign important enterprise processes around humans, AI agents, automation, and systems rather than automating yesterday's workflow.
Executive Summary
Most enterprise processes were created under the assumption that humans perform nearly all knowledge work and software records the result. AI agents fundamentally change that assumption.
WunderHub redesigns workflows around what should be performed by humans, AI agents, deterministic automation, business applications, data services, and external systems.
The objective is not simply faster execution. The objective is a structurally better operating model.
Ideal Buyers
- COO
- CIO
- CFO
- CHRO
- Functional leader
- Transformation leader
- Operations executive
Common Symptoms
- too many handoffs and duplicate entry
- copying data between systems
- repeated manual reviews and unnecessary approvals
- employees searching for information
- queues, backlog, and high exception rates
- inconsistent decisions
- excessive email and spreadsheet-driven work
- repetitive knowledge work
- employees working outside systems
- high administrative overhead and slow customer response
The Core Question
If this workflow were invented today, knowing AI agents existed, would we design it this way?
The Human + Agent Model
Judgment, relationships, accountability, ethics, leadership, complex exceptions.
Research, reasoning, drafting, classification, coordination, analysis, knowledge retrieval.
Routing, notifications, data movement, validation, system actions.
Transactions, systems of record, applications, APIs.
Enterprise knowledge, master data, documents, analytics.
Engagement Phases
- Discover
- Measure
- Deconstruct
- Redesign
- Prototype
- Govern
- Measure
- Scale
Deliverables
- current-state architecture
- labor model
- systems and data inventory
- pain-point and bottleneck analysis
- decision and exception inventory
- automation opportunities
- agent opportunity map
- human-agent responsibility matrix
- future-state process
- control framework
- KPI framework
- ROI model
- implementation architecture
- working prototype
- change-impact assessment
- implementation roadmap
Example Workflows
Sourcing, screening support, scheduling, coordination, candidate communication, scorecards, references, offers.
Provisioning, documentation, orientation, manager tasks, knowledge delivery.
Triage, knowledge retrieval, resolution, escalation, case summarization.
Intake, extraction, comparison, risk analysis, drafting, approval.
Request, vendor analysis, policy review, approval, purchasing coordination.
Invoice handling, expense review, reporting, close support, variance investigation.
Account research, opportunity preparation, proposals, CRM updates, pipeline analysis.
Search, synthesis, Q&A, content lifecycle, institutional knowledge.
Success Metrics
- cycle time and queue size
- labor hours and cost per transaction
- error, exception, and rework rates
- employee capacity and satisfaction
- customer response time and SLA performance
- quality and revenue impact
Build the Future
Build the AI-Native Enterprise
Your next competitive advantage will not come from another SaaS subscription. It will come from owning the operating foundation that connects your people, data, workflows, intelligence, and decisions.