What challenges did Aella Credit face before AI implementation?

Rapid growth had stretched infrastructure to its limits, causing performance issues and expensive workarounds. The company needed a more stable, visible platform for a fully licensed microfinance bank serving more than two million users.

What was the impact of the AI solution?

Infrastructure costs dropped by 70%. Uptime increased from 95% to 99%. Aella processed seven million records via API in a single night without downtime. The platform enabled a Debt-as-a-Service model and expansion of services across Nigeria and beyond.

Source

GCPEvidence: Medium50/100

Aella builds AI-ready digital banking platform on Google Cloud

Use case typeDigital banking platformUpdated Jan 1, 2024

Aella (Nigeria) built a digital banking platform on Google Cloud to support rapid growth, improve reliability, and reduce infrastructure overhead. The company migrated its Kubernetes-based environment to Google Kubernetes Engine and Cloud Run, and uses Cloud SQL, BigQuery, Cloud Logging, and Cloud Trace for visibility and operations. Aella has also experimented with Gemini and Vertex AI for future fraud detection, anti-money laundering, customer service agents, and operations monitoring.

Organization: Aella Credit
Industry: Finance
Location: Nigeria
Published: January 2024

Reported outcomes

Infrastructure costs: −70%

Cost savings

Uptime: 95% to 99%API records processed in one night: 7,000,000 records

Catalog median for cost savings deployments: −40% across 171 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Infrastructure costs: 70% decrease

Google Cloud Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

infrastructure costs dropped by 70%

Normalized claim

Uptime: 95-99% increase

Google Cloud Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

uptime increasing from 95% to 99%

Normalized claim

API records processed in one night: 7,000,000 records increase

Google Cloud Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

accessed seven million records via API in a single night

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Aella Credit
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Stories

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

1Digital banking platform
2Infrastructure modernization
3Observability

Migrated in stages to Google Cloud with Google Kubernetes Engine and Cloud Run.
Used Cloud SQL, BigQuery, Cloud Logging, and Cloud Trace to improve monitoring, analytics, and alerting.
Worked with Codematic to stabilize and modernize the platform.

Technologies

Google Kubernetes Engine Cloud Run Cloud SQL BigQuery Cloud Logging Cloud Trace Gemini Vertex AI

Infrastructure costs dropped by 70%.
Uptime increased from 95% to 99%.
Aella processed seven million records via API in a single night without downtime.
The platform enabled a Debt-as-a-Service model and expansion of services across Nigeria and beyond.

Architecture

Aella migrated its Kubernetes-based platform in stages to Google Kubernetes Engine and Cloud Run, using Cloud SQL, BigQuery, Cloud Logging, and Cloud Trace for database visibility, analytics, and observability alerts. The customer also noted experimentation with Gemini and Vertex AI for future use cases such as fraud detection, AML, customer service agents, and monitoring.

Sources & evidence1

Evidence: Medium50/100Evidence strength