6 · Tools & workflowsStandard CS workflows

Standard CS workflows

At a glance

Six phases to every CS engagement: Discovery → Solution design → Configuration → Eval/UAT → Deployment → Monitoring/Expansion.

Each phase has inputs, outputs, and handoff criteria. Knowing the workflow prevents dropped balls between phases and gives customers predictable timelines.

The end-to-end workflow

Phase 1: Discovery

Goal: Understand the customer’s pain points, current process, and what “success” looks like.

InputActivityOutput
Customer intro, existing contractsStakeholder interviews, process mappingDiscovery doc: pain points, volume data, current workflow
Identify automation candidatesPrioritized use case list with estimated ROI
Technical assessmentIntegration requirements, data availability

Key questions to answer:

  • What percentage of CX volume is WISMO / tracking queries? (If >30%, WISMO agent is the obvious first deploy.)
  • What systems do they use? (TMS, WMS, ERP — determines integration scope.)
  • What are their data residency requirements? (Drives deployment mode choice.)
  • What channels do their customers use? (Voice, WhatsApp, email, chat.)

Phase 2: Solution design

Goal: Map use cases to agents and define the technical architecture.

InputActivityOutput
Prioritized use case listMap use cases to agent templatesSolution architecture doc
Integration requirementsDesign integration layer (APIs, webhooks)Integration spec
Data residency needsChoose deployment mode (cloud/hybrid/on-prem)Deployment plan
Define success metrics (SLA, accuracy, cost)KPI framework

Tools: Use the AgentFleet builder to configure agents. Use AgentFlow Copilot for workflow automation.

Phase 3: Configuration

Goal: Build and configure the agents, tools, and integrations.

InputActivityOutput
Solution architectureConfigure agents in Dashboard or via APIAgent definitions (workflow DAGs)
Integration specSet up tool connections (ProjectX, LIA, carrier APIs)Working integrations
Write/customize system promptsPrompt library
Configure policies (HITL thresholds, retry, follow-up)Policy configs
Set up guardrails (PII masking, content safety)Guardrail configs

Phase 4: Eval / UAT

Goal: Verify agents work correctly before going live.

InputActivityOutput
Configured agentsBuild eval scenarios (happy path, edge cases, adversarial)Eval dataset
Run evals — check accuracy, tool-call correctness, latencyEval results
Customer UAT with real (or realistic) dataUAT sign-off
Fix issues from UATUpdated agent configs

Eval categories: Happy path, edge cases, adversarial inputs, timeout handling, language switching, escalation triggers. See Eval framework for details.

Phase 5: Deployment

Goal: Go live with monitoring in place.

InputActivityOutput
UAT-approved agentsDeploy to production (cloud/hybrid/on-prem)Live agents
Configure observability (New Relic, Langfuse, Elasticsearch)Monitoring dashboards
Set up alerting (error rate, latency, cost thresholds)Alert rules
Gradual rollout (% of traffic, then full)Rollout plan
Customer training on DashboardTrained customer admins

See Deployment modes for cloud/hybrid/on-prem specifics.

Phase 6: Monitoring & expansion

Goal: Maintain performance and grow the deployment.

InputActivityOutput
Live deploymentMonitor accuracy, latency, cost in Dashboard + LangfuseWeekly performance reports
Review escalation patterns — what’s the agent missing?Agent improvement backlog
Run periodic evals to detect driftDrift detection alerts
Identify new use cases from monitoring dataExpansion proposal
Upsell additional agentsExpanded deployment

Sources

Changelog

  • 26 May 2026: Full content with six-phase workflow, activities, and handoff criteria.