Tutorials
Build a Sales Pipeline Flow
Build a CRM-style lead enrichment, scoring, and routing flow with LLM intelligence.
This tutorial builds a lead processing pipeline that enriches incoming leads with external data, scores them using an LLM, and routes them to the correct sales action based on their score.
What you'll build
flowchart TD
A[LeadReceived\nsource] -->|durable| B[EnrichLead\nintegration]
B -->|durable| C[ScoreLead\nllm]
C -->|durable| D{RouteByScore\nrouter}
D -->|hot score ≥80| E[AssignToSalesRep\naction]
D -->|warm 40–79| F[AddToNurtureCampaign\naction]
D -->|cold score <40| G[ArchiveLead\nterminal]
E -->|durable| H[SendWelcomeEmail\naction]
The complete flow YAML
yaml
flowdsl: "1.0"
info:
title: Sales Pipeline
version: "1.0.0"
description: |
Processes incoming leads: enriches from Clearbit, scores with LLM,
routes hot/warm/cold to appropriate sales actions.
nodes:
LeadReceived:
operationId: receive_lead
kind: source
summary: Receives new lead submissions from the website form or CRM webhook
outputs:
out: { packet: LeadPayload }
EnrichLead:
operationId: enrich_lead_clearbit
kind: integration
summary: Enriches lead data from Clearbit (company size, industry, funding)
inputs:
in: { packet: LeadPayload }
outputs:
out: { packet: EnrichedLead }
settings:
clearbitApiKey: "${CLEARBIT_API_KEY}"
enrichFields: [company, person, employment]
ScoreLead:
operationId: llm_score_lead
kind: llm
summary: Scores the lead 0–100 based on ICP fit using LLM
inputs:
in: { packet: EnrichedLead }
outputs:
out: { packet: ScoredLead }
settings:
model: gpt-4o-mini
temperature: 0.2
systemPrompt: |
You are a B2B sales qualification expert. Score this lead 0-100 based on
ideal customer profile fit. Consider: company size (prefer 50-500 employees),
industry fit, funding stage, and seniority of contact.
Return JSON: {"score": 0-100, "tier": "hot|warm|cold", "reasoning": "...", "topSignals": [...]}
RouteByScore:
operationId: route_lead_by_score
kind: router
summary: Routes leads based on their ICP score
inputs:
in: { packet: ScoredLead }
outputs:
hot:
packet: ScoredLead
description: Score ≥80 — assign to a sales rep immediately
warm:
packet: ScoredLead
description: Score 40–79 — add to nurture campaign
cold:
packet: ScoredLead
description: Score <40 — archive
AssignToSalesRep:
operationId: assign_sales_rep
kind: action
summary: Assigns the lead to a sales rep via round-robin in the CRM
inputs:
in: { packet: ScoredLead }
outputs:
out: { packet: AssignedLead }
settings:
crmSystem: salesforce
assignmentStrategy: round-robin
territory: us-west
SendWelcomeEmail:
operationId: send_welcome_email
kind: action
summary: Sends a personalized welcome email to the hot lead
inputs:
in: { packet: AssignedLead }
settings:
templateId: hot-lead-welcome-v3
senderName: "Sales Team"
AddToNurtureCampaign:
operationId: add_to_nurture_campaign
kind: action
summary: Enrolls the lead in a 6-email nurture sequence
inputs:
in: { packet: ScoredLead }
settings:
campaignId: nurture-sequence-q1-2026
startDelay: PT24H
ArchiveLead:
operationId: archive_cold_lead
kind: terminal
summary: Archives the lead with cold classification for future re-engagement
inputs:
in: { packet: ScoredLead }
edges:
# Enrich incoming lead — durable because external API call
- from: LeadReceived
to: EnrichLead
delivery:
mode: durable
packet: LeadPayload
idempotencyKey: "{{payload.leadId}}-enrich"
retryPolicy:
maxAttempts: 3
backoff: exponential
initialDelay: PT3S
retryOn: [TIMEOUT, RATE_LIMITED]
# LLM scoring — durable + idempotency (expensive, non-deterministic)
- from: EnrichLead
to: ScoreLead
delivery:
mode: durable
packet: EnrichedLead
idempotencyKey: "{{payload.leadId}}-score"
retryPolicy:
maxAttempts: 3
backoff: exponential
initialDelay: PT5S
retryOn: [RATE_LIMITED, TIMEOUT]
# Route to appropriate path
- from: ScoreLead
to: RouteByScore
delivery:
mode: durable
packet: ScoredLead
# Hot path — assign to sales rep immediately
- from: RouteByScore.hot
to: AssignToSalesRep
delivery:
mode: durable
packet: ScoredLead
idempotencyKey: "{{payload.leadId}}-assign"
retryPolicy:
maxAttempts: 3
backoff: exponential
initialDelay: PT2S
# Welcome email for hot leads after assignment
- from: AssignToSalesRep
to: SendWelcomeEmail
delivery:
mode: durable
packet: AssignedLead
idempotencyKey: "{{payload.leadId}}-welcome-email"
retryPolicy:
maxAttempts: 3
backoff: exponential
initialDelay: PT2S
# Warm path — nurture campaign
- from: RouteByScore.warm
to: AddToNurtureCampaign
delivery:
mode: durable
packet: ScoredLead
idempotencyKey: "{{payload.leadId}}-nurture"
retryPolicy:
maxAttempts: 3
backoff: exponential
initialDelay: PT2S
# Cold path — archive directly (fast, idempotent)
- from: RouteByScore.cold
to: ArchiveLead
delivery:
mode: direct
packet: ScoredLead
components:
packets:
LeadPayload:
type: object
properties:
leadId: { type: string }
email: { type: string, format: email }
firstName: { type: string }
lastName: { type: string }
company: { type: string }
title: { type: string }
phone: { type: string }
source:
type: string
enum: [website, referral, event, linkedin, cold-outreach]
submittedAt: { type: string, format: date-time }
required: [leadId, email, company, source, submittedAt]
EnrichedLead:
type: object
properties:
lead:
$ref: "#/components/packets/LeadPayload"
clearbit:
type: object
properties:
companySize:
type: integer
description: Number of employees
industry: { type: string }
fundingStage: { type: string }
annualRevenue: { type: number }
technologies: { type: array, items: { type: string } }
additionalProperties: true
enrichedAt: { type: string, format: date-time }
required: [lead, enrichedAt]
ScoredLead:
type: object
properties:
lead:
$ref: "#/components/packets/EnrichedLead"
score:
type: integer
minimum: 0
maximum: 100
tier:
type: string
enum: [hot, warm, cold]
reasoning: { type: string }
topSignals:
type: array
items: { type: string }
scoredAt: { type: string, format: date-time }
required: [lead, score, tier, scoredAt]
AssignedLead:
type: object
properties:
lead:
$ref: "#/components/packets/ScoredLead"
assignedTo:
type: object
properties:
repId: { type: string }
repName: { type: string }
repEmail: { type: string, format: email }
required: [repId, repName, repEmail]
crmLeadId: { type: string }
assignedAt: { type: string, format: date-time }
required: [lead, assignedTo, assignedAt]
Delivery mode decisions
| Edge | Mode | Why |
|---|---|---|
| LeadReceived → EnrichLead | durable | External API call, loss unacceptable |
| EnrichLead → ScoreLead | durable | Expensive LLM call with idempotency |
| ScoreLead → RouteByScore | durable | Business-critical classification |
| RouteByScore.hot → AssignToSalesRep | durable | CRM write, must not duplicate |
| AssignToSalesRep → SendWelcomeEmail | durable | Email send, must not duplicate |
| RouteByScore.warm → AddToNurtureCampaign | durable | Campaign enrollment, idempotent key |
| RouteByScore.cold → ArchiveLead | direct | Fast, idempotent, no external calls |
Next steps
- LLM Flows — deep patterns for LLM scoring and classification
- Idempotency — preventing duplicate CRM entries and emails
- Email Triage Flow — another real-world stateful flow