Building a compliant bot took 512 hours. A unified framework cuts that to 64, launching agents with just 50 lines of code.
A subsidiary of a global aerospace leader found its internal teams were independently piloting AI initiatives without central coordination.
This fragmentation caused redundant work and compliance bottlenecks, with the manual creation of a single chatbot taking approximately 512 hours....
“Everyone was building their own bots. Some teams were ahead, some just starting. We wanted to create a shared foundation that made it easier to build and learn together.”
Navigation, flight planning, and crew management software for the aviation industry.
Data framework and agentic OCR platform for building LLM-powered applications.
Related implementations across industries and use cases
Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
Serial testing bottlenecked development. Now, parallelized checks validate hundreds of complex conversation paths in seconds.
Standard cloud setups were too rigid for orbital hardware. Now, custom GPU attachments power autonomous AI in space.
Manual reporting took 12 hours, leaving insights untapped. An AI agent now mines archives and maps safe routes in just 25 minutes.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Building a compliant bot took 512 hours. A unified framework cuts that to 64, launching agents with just 50 lines of code.
A subsidiary of a global aerospace leader found its internal teams were independently piloting AI initiatives without central coordination.
This fragmentation caused redundant work and compliance bottlenecks, with the manual creation of a single chatbot taking approximately 512 hours....
“Everyone was building their own bots. Some teams were ahead, some just starting. We wanted to create a shared foundation that made it easier to build and learn together.”
Navigation, flight planning, and crew management software for the aviation industry.
Data framework and agentic OCR platform for building LLM-powered applications.
Related implementations across industries and use cases
Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Critical data was scattered across disconnected lakes. Now, 10,000 engineers query a unified platform using natural language.
Serial testing bottlenecked development. Now, parallelized checks validate hundreds of complex conversation paths in seconds.
Standard cloud setups were too rigid for orbital hardware. Now, custom GPU attachments power autonomous AI in space.
Manual reporting took 12 hours, leaving insights untapped. An AI agent now mines archives and maps safe routes in just 25 minutes.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.