Conflicting rules across 3,000 services blocked qualified drivers. AI now traverses a graph to validate dependencies in milliseconds.
A global mobility platform operating in 15,000 cities with over 8 million earners, managing a complex architecture of 3,000 microservices with unique regulatory rules.
Configuration sprawl across isolated systems caused costly conflicts, such as drivers passing onboarding checks but failing dispatch rules for...
“We tried modeling this using SQL. It exploded in complexity.”
Uber's Configuration validation is part of this use case:
Mobility and delivery platform for ride-hailing, food, and freight logistics.
Graph database and analytics platform for enterprise data relationships.
Related implementations across industries and use cases
Auditors spent six hours manually preparing each review. Models now validate evidence, freeing experts to focus on analysis.
Fixing 60,000 compliance errors per module bottlenecked scarce engineers. Now, three AI agents draft transparent fixes for human approval.
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
Auditors spent six hours manually preparing each review. Models now validate evidence, freeing experts to focus on analysis.
Auditors spent five days manually validating files. AI now parses the data against contracts, cutting manual effort by 90%.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Conflicting rules across 3,000 services blocked qualified drivers. AI now traverses a graph to validate dependencies in milliseconds.
A global mobility platform operating in 15,000 cities with over 8 million earners, managing a complex architecture of 3,000 microservices with unique regulatory rules.
Configuration sprawl across isolated systems caused costly conflicts, such as drivers passing onboarding checks but failing dispatch rules for...
“We tried modeling this using SQL. It exploded in complexity.”
Uber's Configuration validation is part of this use case:
Mobility and delivery platform for ride-hailing, food, and freight logistics.
Graph database and analytics platform for enterprise data relationships.
Related implementations across industries and use cases
Auditors spent six hours manually preparing each review. Models now validate evidence, freeing experts to focus on analysis.
Fixing 60,000 compliance errors per module bottlenecked scarce engineers. Now, three AI agents draft transparent fixes for human approval.
A 50% staff cut bottlenecked security across 14 clouds. AI now automates policy code, boosting development efficiency by nearly 70%.
Auditors spent six hours manually preparing each review. Models now validate evidence, freeing experts to focus on analysis.
Auditors spent five days manually validating files. AI now parses the data against contracts, cutting manual effort by 90%.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.