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Financial ServicesData Platform Architecture

50 Data Silos. One Insurance Provider. Real-Time Risk Scoring — Live in 10 Weeks with 70% Cost Reduction.

70% cost reductionwith 50+ sources unified in 10 weeks

Industry

Financial Services (Insurance)

Service

Data Platform Architecture

Duration

10 weeks

Team

Agilityx consultants + AI agents

Data Sources

50+ integrated

SnowflakeData MeshdbtPythonAgilityx AI Agent Suite
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The Situation

A major insurance provider was paralyzed by 'decision latency' — calculating risk for a new policy took days because data was siloed across 50+ legacy sources. The cost of maintaining this on-premise hardware was rapidly consuming the IT budget, preventing any investment in modern AI models for fraud detection or predictive underwriting.

They needed a modern, cloud-native architecture on Snowflake that could enable a domain-oriented data platform aligned with Data Mesh principles. The goal was to provide an immediate 360-degree view of the customer to enable automated risk scoring.

The project required reducing ongoing infrastructure costs by 70% within a strictly defined 10-week launch window.

The Approach

1

Mapping(Phase 1)

AI Agents

Ingested metadata and mapped dependencies across 50+ disparate databases.

Consultants

Aligned the target architecture with underwriting and regulatory risk goals.

2

Design(Phase 2)

AI Agents

Generated migration blueprints for Snowflake, including optimized partitioning strategies.

Consultants

Co-designed the 'Data Mesh' governance model to empower domain-specific teams.

3

Build(Phase 3)

AI Agents

Automated the generation of integration pipelines and dbt transformation layers.

Consultants

Managed the complex integration of third-party risk data and claims history.

4

Rigor(Phase 4)

AI Agents

Deployed agents to monitor pipeline health and compute spend in real-time.

Consultants

Directed the technical program to ensure all 50+ sources went live in 10 weeks.

5

Transfer(Phase 5)

AI Agents

Auto-generated technical documentation and security runbooks.

Consultants

Mentored the internal architecture team on modern cloud-native patterns.

Traditional vs. Agilityx

Planning Phase

Traditional

4 months

Agilityx

2 weeks (AI-accelerated)

Source Integration

Traditional

2 weeks per source

Agilityx

50+ prioritized sources in 9 weeks

Risk Scoring

Traditional

Batch (days)

Agilityx

Real-time (minutes)

Infrastructure Costs

Traditional

Over-provisioned

Agilityx

70% cost reduction

The Outcomes

70%

Cost Savings

Migrating to an elastic cloud foundation eliminated massive on-prem overhead.

10 weeks

Launch

Delivered a production-ready platform for 50+ sources in a single quarter.

Real-Time

Underwriting

Risk scoring now happens in minutes, giving the insurer a competitive edge.

Embedded

Capability

The client's team can now scale the Data Mesh architecture independently.

"Agilityx TPMs resolved our failure modes early, before they turned into delays. They lead with a hands-on platform understanding that traditional consultants just don't have."

Chief Technology Officer

Leading Insurance Provider

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