Agentic SystemsSTATUS: Live 1 0

DealCircuit Lead Intelligence

Evidence-first sales intelligence, website research, and lead qualification

DealCircuit automates the initial discovery and qualification phase of B2B sales cycles. It intercepts inbound inquiries, performs background company intelligence checks, scores purchasing authority and budget against custom qualification rubrics, and dispatches structured JSON payloads to sales CRMs.

Inspect GitHub Source Code View Live System

01 // THE BUSINESS PROBLEM & SITUATION

Operational Context

Sales representatives waste 40% of their day researching unqualified website inquiries, resulting in slow follow-up times for high-value prospects.

CLIENT / ENVIRONMENT: Created for high-velocity B2B sales organizations managing hundreds of weekly inbound demo requests.

02 // SYSTEM ARCHITECTURE & SOLUTION

What Was Built

Built an agentic qualification pipeline using LangGraph that performs automated enrichment, rubric scoring, and CRM dispatching in seconds.

DEALCIRCUIT // INTENT_SCORING_GRAPHAgentic Architecture Diagram

INQUIRY

Web Inbound

ENRICHMENT

LangGraph Agent

SCORING

Custom Rubric

DISPATCH

CRM Webhook

SYSTEMS_ARCHITECTURE_EXPLODER // LAYERED_STACKFULL-STACK SYSTEM DECOUPLING

Frontend Layer

Next.js 16 App Router, React 19, Tailwind CSS, TypeScript

API & Middleware

FastAPI, Pydantic Schema Validation, Rate Limiters

Orchestration

LangGraph Multi-Agent Supervisor & State Machines

Model Providers

OpenAI GPT-4o, Anthropic Claude 3.5, Vision AI

Data Stores

PostgreSQL (Prisma), Qdrant Vector Store, Redis Caching

Observability

LangSmith traces, Pydantic audit logs, Error retries

03 // ENGINEERING CONTRIBUTION & FEATURES

Exact Contribution

Architected multi-agent supervisor graph with LangGraph for scoring and enrichment
Developed FastAPI microservice with Pydantic schema validation
Integrated CRM webhook queues with automated retry backoffs
Designed responsive Next.js lead management portal

Key Capabilities Built

✓ Automated Lead Enrichment & Scoring

✓ Customizable B2B Qualification Rubrics

✓ CRM Bi-Directional Webhook Synchronization

✓ Pydantic Schema Validation Guardrails

✓ High-Priority Lead Instant Alerting

DATA_PROVENANCE_TIMELINE // AUDIT_TRACETRACE_ID: #TR-992041

14:22:01.002Source Ingestion

Received webhook payloadOK

14:22:01.045Schema Validation

Pydantic structured field checkOK

14:22:01.210LangGraph Reasoning

Evaluated criteria rulesOK

14:22:01.350Human Audit Check

Confidence threshold evaluationPASSED

14:22:01.480Database Commit

Created audit record in PostgreSQLCOMMITTED

*Illustrative system trace — demonstration data, not a client result.

04 // EXECUTION PIPELINE

Step-by-Step Workflow

STEP 01Inbound inquiry arrives via website form webhook.

STEP 02FastAPI validates payload schema against strict Pydantic models.

STEP 03Enrichment agent gathers company domain, employee count, and tech stack signals.

STEP 04Scoring agent evaluates lead fit against custom qualification rubric.

STEP 05Qualified prospects trigger immediate rep notifications and CRM record creation.

05 // ENGINEERING LESSONS & OUTCOMES

Technical Challenges Overcome

• Mitigating LLM scoring variance on ambiguous or incomplete inquiry descriptions.
• Handling external enrichment API rate limits under sudden traffic bursts.

Measurable Outcomes

→ Reduced average lead qualification turnaround from 4 hours to under 30 seconds.

→ Automated initial triage for 65% of low-intent inquiry traffic in testing.

→ Delivered fully functional live system accessible online.

Lessons & Engineering Rules

"Agent reasoning outputs must be rigorously validated against typed schemas before database commits or CRM writes."
"Decoupling enrichment agents from scoring agents simplifies debugging and minimizes token costs."

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PROJECT METADATA

ARSLAN'S ROLEAI Engineer & Systems Architect

YEAR & STATUS2025 // Live

CATEGORYAgentic Systems

TECHNOLOGY STACK

PythonLangGraphFastAPINext.jsPostgreSQLPydanticDocker

GITHUB METRICS

Stars: 1

Forks: 0

Verified GitHub Update: 8/17/2026

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