Data Warehouse
Feathery serves as a clean data warehouse for your client data, with bulk synchronization into your various systems.
Feathery provides a unified warehouse for client data collected through workflows and synchronized from external systems. Data is normalized, identity-resolved, and aggregated into a single client profile that can be used for reporting, downstream integrations, and operational workflows.
Getting Started
Navigate to the Feathery form or workflow you want to configure. Open the Integrations tab to set up inbound and outbound data synchronization.
Once configured, all client-submitted data and external-system data will automatically populate Feathery’s warehouse and resolve into unified client records.
Client Identity Resolution
Feathery maintains a single client record by resolving identity across submissions, CRM data, custodial feeds, and other integrated systems.
Primary Identifiers
Choose one or more stable identifiers (email, CRM ID, account number, tax ID). To specify identifiers:
Select the field.
Enable Use as Client Identifier.
Add additional identifiers as needed.
All configured identifiers participate in the identity-resolution pipeline.
Multi-Attribute Matching
If a single identifier does not produce a match, Feathery evaluates additional attribute sets in priority order. Examples:
External CRM ID
Email Address
Phone Number + Date of Birth
Last Name + Postal Code
During ingestion:
Feathery attempts to match using the first attribute set.
If no match is found, Feathery tries the next set.
If multiple matches are found, Feathery flags the record for review or applies fuzzy/AI logic if enabled.
This supports heterogeneous external data sources.
Fallback Normalization Logic
If primary and secondary attributes fail to match, Feathery applies fallback normalization, such as:
Email alias normalization (
+tag, dot variants)Country-code–agnostic phone number comparison
Partial date matching (MM/YYYY)
Address normalization (tokenization and standardization)
Fallback rules reduce false negatives when ingesting large or inconsistent datasets.
Fuzzy Matching
Feathery supports fuzzy matching on human-entered fields.
Field examples:
Name similarity ("Jonh Smith" → "John Smith")
Address similarity (component-level matching)
Email typo correction
Configurable parameters:
Minimum similarity threshold (e.g., 0.92)
Which fields allow fuzzy matching
Automatic vs manual confirmation for low-confidence matches
Fuzzy matching is useful for custodial file imports, older CRM data, and systems with inconsistent formatting.
AI-Driven Resolution (Optional)
Feathery’s AI identity resolution evaluates many data points together and learns matching patterns over time.
AI matching considers:
Weighted attribute importance (DOB > phone > address)
Name variations and known alias patterns
Historical merges and administrator-approved matches
Cross-field consistency (e.g., matching spouse/household information)
Modes:
Auto-Link: High-confidence matches merge automatically.
Review Mode: Feathery surfaces matches with confidence scores.
This is ideal for migrations, multi-system consolidation, and legacy datasets.
Duplicate Detection and Merging
If multiple records satisfy matching rules, Feathery identifies duplicates.
Duplicate handling:
Surface conflicting profiles
Allow merge operations
Preserve all submissions and documents
Maintain field-level version history
Merge external-system IDs into a single profile
Merging unifies lineage without losing historical data.
Bulk Synchronization From External Systems
Feathery supports high-volume inbound and outbound synchronization to keep the warehouse aligned with CRMs, custodians, and other systems.
System → Feathery (Inbound Bulk Sync)
Use inbound sync to import:
CRM objects and relationships
Custodial account data
Historical client attributes
External identifiers
Household or entity structures
During bulk sync:
Identity resolution maps each record to an existing profile or creates a new one
Mapped fields populate the profile
Sync logs capture all changes and resolution logic used
Feathery → System (Outbound Bulk Sync)
Outbound sync pushes Feathery-collected data back into external systems.
Examples:
Updating CRM client attributes
Pushing KYC/AML workflow outputs to custodial platforms
Sending structured data to internal databases or document systems
Bi-Directional Sync
For systems with full integration:
Feathery updates external systems when profile data changes
External systems update Feathery during scheduled or event-driven sync
Field-level sync rules define directionality (read-only, write-only, or bidirectional)
This ensures all systems share a consistent representation of the client.
Field Mapping
For each integration, define how Feathery fields map to external-system attributes.
Steps:
Open the integration.
Upload or configure the mapping (CSV or in-app).
Set directionality for each field.
Save and activate.
Mapped fields remain synchronized during bulk updates, form submissions, and webhook events.
Unified Profile Storage
Feathery maintains two layers of stored data:
1. Submission Records
Captured each time a client completes a workflow step. Includes:
Field-level data
Documents
Submission timestamp
Logic path taken
Useful for auditing and chronological history.
2. Client Profile Records
Aggregated, identity-resolved records that represent the authoritative view of the client. Includes:
Latest values for all mapped fields
All external-system IDs
Attached documents
Historical value versions
Metadata describing data origin and resolution
Profile records act as the warehouse’s primary table.
Reporting Views
Feathery provides reporting layers for analytics and export.
Client Profile Reports
One row per client showing the consolidated record:
Key attributes
External IDs
Latest field values
Relationship metadata
Ideal for BI tools and operational reporting.
Submission Reports
One row per submission for:
Audit trails
Time-based analysis
Reviewing changes over time
Custom Views
You can create filtered reporting views based on:
Data fields
Status
External system values
Date ranges
All views are exportable or accessible via API.
API and Webhook Access
API
Use Feathery’s API to:
Retrieve unified client profiles
Fetch submission histories
Extract warehouse tables into your BI stack
Download documents
Build ETL pipelines
Webhooks
Trigger events when:
A submission is created or updated
A client profile updates
A bulk sync completes
Identity resolution merges records
Webhook payloads include fully resolved identifiers and mapped fields.
Summary
Feathery operates as a complete client-data warehouse by providing:
Multi-field, fuzzy, and AI-driven identity resolution
Bulk sync across CRMs, custodians, and internal systems
Unified client profiles with full version history
End-to-end field mapping and bi-directional synchronization
Reporting layers for analytics and exports
API and webhook access for data pipelines
This creates a single source of truth for client data across all workflows and integrated systems.
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