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.
Jeppesen's AI development platform is part of this use case:
Related implementations across industries and use cases
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.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Staff scoured dispersed docs to answer technical queries. An AI now scans internal data to provide answers in under a minute.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
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.
Jeppesen's AI development platform is part of this use case:
Related implementations across industries and use cases
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.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Staff scoured dispersed docs to answer technical queries. An AI now scans internal data to provide answers in under a minute.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.