Normalized claim
Accuracy: 99%
Up to 99% predictive accuracy in forecasting.
Aily Labs builds enterprise decision intelligence mobile app with Amazon Bedrock agentic orchestration
Use case typeAutomotive operations automationUpdated Jun 13, 2026
Aily Labs built a mobile-first decision intelligence platform for enterprise users across pharmaceutical, retail, consumer goods, and other sectors. The platform’s AI brain coordinates hundreds of classical ML models, LLMs, and thousands of enterprise agents orchestrated by a Super Agent to surface insights and actions in real time. Aily Labs uses AWS infrastructure including Amazon Bedrock, Amazon EKS, Amazon S3, Amazon RDS, AWS KMS, and AWS security/auditing services, and uses Bedrock Prompt Caching to reduce recomputation and latency.
Reported outcomes
−83%
quantified impactRisk, reliability & safety
99%accuracy
Strategic outcomes
New product / capabilityBuilt mobile-first decision intelligence platformNew product / capabilityOrchestrated thousands of enterprise agentsNew product / capabilityEnabled real-time decision executionSpeed & agilityDelivered near real-time decision support
Catalog median for risk, reliability & safety deployments: −70% across 13 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 83% decrease
83% reduction in inventory risk for pharmaceutical clients.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Aily Labs
- Provider
- AWS
- Maturity
- Scaled Production
- Linked source
- AWS Solutions Case Study
Static reporting and manual analysis caused delayed decision-making, operational inefficiency, limited scenario analysis at scale, and decision latency across functions
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 5
- 1Decision automation
- 2Enterprise search/insights
- 3Predictive analytics
- Fortune 500 enterprises struggled to make cross-silo, data-driven decisions in real time.
- Static reporting and manual analysis caused delayed decision-making, operational inefficiency, limited scenario analysis at scale, and decision latency across functions.
- Aily built an AI brain composed of hundreds of classical ML models, LLMs, and thousands of enterprise agents orchestrated by a Super Agent.
- The platform dynamically selects the best model per use case and supports near real-time inference for a mobile-first decision intelligence app.
- Amazon Bedrock Prompt Caching is used to skip recomputation of inputs and lower response latency.
- The platform runs on Amazon EKS on EC2 and uses Amazon S3, Amazon RDS, AWS KMS, and AWS security/auditing services.
- The solution can generate what-if scenarios at scale and, at defined autonomy levels, execute decisions within transactional systems.
- Up to 99% predictive accuracy in forecasting.
- 83% reduction in inventory risk for pharmaceutical clients.
- Projected $685M value through inventory optimization.
- Expected incremental net sales of over $550M through resource reallocation.
- Supports over 300 AI models and thousands of agents, processing requests in real time for tens of thousands of users.
Architecture
The platform runs primarily on AWS, with Amazon EKS on EC2 for production services, Amazon S3 as a data lake, Amazon RDS for data warehousing/analytics support, Amazon Bedrock for model orchestration and Anthropic model access, Bedrock Prompt Caching for latency reduction, and AWS KMS plus AWS security/auditing services for encryption and compliance.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: PrimaryConfidence: High
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