Systems

CRM Deduplication Layer

Deterministic and fuzzy matching architecture to prevent duplicate records across CRM systems and API integrations, ensuring data integrity.

System Architecture Flow

Compact, event-driven flow. Each step is horizontally scalable and instrumented for failure recovery.

Resilience: Circuit breakers and fallbacks for external services.
Observability: Structured logs, metrics and alerting on queue depth/latency.
Permissions: Role-based access at tool and data level.

Problem

Duplicate records destroy CRM integrity. They cause sales reps to step on each other's toes, trigger embarrassing duplicate marketing emails, and break attribution models. Standard CRM dedupe tools (like HubSpot's native matcher) only look at exact email matches and fail when leads use different addresses or slight variations of company names.

Without a dedicated deduplication layer, databases degrade over time, forcing expensive manual cleanup projects and eroding trust in the data.

Siloed Data: Marketing, Sales, and Support talk to the same customer without knowing it
Attribution Failure: Ad spend ROI is miscalculated because the closed deal is on a different record
Embarrassing Outreach: Prospects receive automated welcome emails while already in deep negotiations
Fuzzy Match Blindness: "Acme Corp" and "Acme Corporation Inc" create split accounts
Destructive Merges: Blind automated merging overwrites critical recent data with old cached data

Architecture

A standalone data-cleansing middleware that sits between lead capture and the CRM. It uses a multi-pass matching strategy: fast deterministic checks followed by slower, LLM-assisted fuzzy matching for edge cases. It maintains an audit log of all merges and routing decisions.

Ingestion Buffer

Queues incoming records. Prevents race conditions when multiple systems update the same lead simultaneously.

Queue

Normalization Engine

Strips punctuation, standardizes company suffixes (LLC, Inc), and formats phone numbers to E.164 standard before matching.

Processing

Deterministic Matcher

Fast-pass evaluation against indexed fields (Email, Phone, Domain, External ID). Resolves 80% of duplicates instantly.

Logic

Fuzzy Matcher

Slower-pass evaluation using trigram similarity and LLM reasoning for company names and addresses (e.g., "IBM" vs "Intl Business Machines").

Merge Rule Engine

Executes survivorship rules (e.g., "Salesforce ID wins", "Keep most recent phone", "Append new notes"). Prevents data destruction.

Rules

Audit Logger

Records the before/after state of every merge. Allows rollbacks if a false-positive merge occurs.

Observability