Thousands of project models across disconnected systems made every query a hunt. Natural language in Teams now surfaces answers immediately.
A global engineering, procurement, and construction firm with 10,000+ employees delivering technology and project solutions to the downstream energy and chemical industries across highly regulated, high-stakes projects worldwide.
Engineers working on complex global projects had to navigate multiple disconnected systems to query thousands of project models, documents, and...
“Staying competitive means more than adding new tools, so we set out to design a digital landscape that could evolve with the business. One that would help our engineers navigate complexity, collaborate across disciplines, and prepare the company for the next decade of innovation.”
Engineering and technology group for nitrogen and energy transition industries.
Enterprise software, cloud infrastructure, and consumer electronics platform.
MAIRE's Engineering data search is part of this use case:
Related implementations across industries and use cases
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Thousands of project models across disconnected systems made every query a hunt. Natural language in Teams now surfaces answers immediately.
A global engineering, procurement, and construction firm with 10,000+ employees delivering technology and project solutions to the downstream energy and chemical industries across highly regulated, high-stakes projects worldwide.
Engineers working on complex global projects had to navigate multiple disconnected systems to query thousands of project models, documents, and...
“Staying competitive means more than adding new tools, so we set out to design a digital landscape that could evolve with the business. One that would help our engineers navigate complexity, collaborate across disciplines, and prepare the company for the next decade of innovation.”
Engineering and technology group for nitrogen and energy transition industries.
Enterprise software, cloud infrastructure, and consumer electronics platform.
MAIRE's Engineering data search is part of this use case:
Related implementations across industries and use cases
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Critical know-how was retiring with veteran engineers. Now, AI agents turn expert videos into instant, searchable guidance for new hires.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Flying blind with agents in critical infrastructure — raw logs the only window. Now production traces feed evaluation before every release.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.