What challenges did Pienomial face before AI implementation?

Needed reliable, low-cost infrastructure to support always-on processing of dense scientific and regulatory documents. Deployments were manual and could take half a day, with limited logging and alerting that slowed issue detection and resolution. Previous infrastructure created higher complexity and less predictable costs.

Source

GCPEvidence: Medium50/100

Pienomial case study - Google Cloud

Use case typeCloud migrationUpdated Jun 13, 2026

Pienomial's Knolens platform delivers always-on AI for life sciences at lower prices while developers focus on products, not ops. Knolens combines proprietary evidence-structuring technology with generative AI to help organizations work with dense scientific and regulatory information so that high-stakes decisions can move forward with confidence. Pienomial migrated Knolens fully to Google Cloud to improve reliability, scalability, and cost predictability for time-sensitive scientific work.

Organization: Pienomial
Industry: Pharma
Location: United States
Published: May 2026

Reported outcomes

Cost: −40%

Cost savings

Time: 15 minutes

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

Cost: 40% decrease

Google Cloud Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

Cloud infrastructure costs were reduced by 40%.

Normalized claim

Time: 15 minutes decrease

Google Cloud Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

Deployment time dropped from half a day to 15 minutes.

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

Customer: Pienomial
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

1Cloud migration
2Infrastructure modernization
3MLOps

Migrated Knolens fully to Google Cloud.
Built a managed, cloud-native architecture using Cloud Run and Compute Engine, with secure networking through Virtual Private Cloud, Identity and Access Management, and Certificate Manager.
Automated CI/CD with Cloud Build for zero-downtime rollouts and centralized observability with Cloud Monitoring and Cloud Logging.
Worked with Google Cloud partner Enhub to redesign secure networking, codify infrastructure, and establish repeatable patterns for growth.

Technologies

Cloud Run Compute Engine Virtual Private Cloud Identity and Access Management Certificate Manager Cloud Build Cloud Monitoring Cloud Logging Google Kubernetes Engine

Architecture

Knolens runs on a managed Google Cloud architecture using Cloud Run and Compute Engine behind VPC boundaries, with IAM-based access control, Certificate Manager, Cloud Build-driven deployments, and Cloud Monitoring/Cloud Logging for operations. Enhub helped redesign the environment and codify infrastructure.

Sources & evidence1

Evidence: Medium50/100Evidence strength