Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
A global leader in aerospace and defense technology managed its operations through several disconnected data lakes and 46 disparate systems for analytics.
This fragmentation created severe data silos that prevented the organization from scaling AI initiatives or accessing high-quality insights. Complex...
Aerospace and defense contractor for aircraft, missiles, and space systems.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
Lockheed Martin's Enterprise AI platform is part of this use case:
Related implementations across industries and use cases
Rising IT and HR tickets were siphoning staff from defense programs. AI now fields most requests without a human in the loop.
Lunar hardware took years of sequential design cycles. Now, AI agents run physics simulations to deliver parts in days.
Quotes from 30,000 vendors meant manual parsing of dense contract clauses. Now AI extracts and routes data to Salesforce in minutes.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Support bottlenecked across secure sites. AI now resolves login and software requests via chat, adhering to strict federal standards.
Building a compliant bot took 512 hours. A unified framework cuts that to 64, launching agents with just 50 lines of code.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.
Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
A global leader in aerospace and defense technology managed its operations through several disconnected data lakes and 46 disparate systems for analytics.
This fragmentation created severe data silos that prevented the organization from scaling AI initiatives or accessing high-quality insights. Complex...
Aerospace and defense contractor for aircraft, missiles, and space systems.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
Lockheed Martin's Enterprise AI platform is part of this use case:
Related implementations across industries and use cases
Rising IT and HR tickets were siphoning staff from defense programs. AI now fields most requests without a human in the loop.
Lunar hardware took years of sequential design cycles. Now, AI agents run physics simulations to deliver parts in days.
Quotes from 30,000 vendors meant manual parsing of dense contract clauses. Now AI extracts and routes data to Salesforce in minutes.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Support bottlenecked across secure sites. AI now resolves login and software requests via chat, adhering to strict federal standards.
Building a compliant bot took 512 hours. A unified framework cuts that to 64, launching agents with just 50 lines of code.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.