Forlex
Legal workflow automation
Overtaxed servers left 13 legal models trailing as laws changed. AWS migration cut costs 40%, throughput up 170%, opened new markets.
- Expected full ROI within 3–6 months
- Legal workflows automated in 30–60 seconds
Reactive management wasted resources. AI now forecasts contamination to optimize dosing, cutting energy consumption by 30%.
A water technology provider monitors treatment processes at over 100 plants across Latin America, impacting water quality for more than 1 million people.
Water treatment plants traditionally rely on reactive management, often leading to excessive chemical usage and energy waste. The company needed to...
“Water doesn’t wait, nor does the planet. That’s why we need to build solutions that facilitate water security. That includes public policy, engineering, and software and AI for making sure facilities run properly.”
AI platform for real-time optimization and management of water treatment facilities.
Cloud computing platform and on-demand infrastructure services.
AInwater's Water treatment optimization is part of this use case:
Related implementations across industries and use cases
Overtaxed servers left 13 legal models trailing as laws changed. AWS migration cut costs 40%, throughput up 170%, opened new markets.
Complex email chains bottlenecked utility agents. AI now summarizes 55k threads monthly, cutting handling time by 87%.
Case by case, bill disputes needed detailed human analysis—slow and inconsistent. An AI agent now resolves each from start to finish.
336 hours a month combing 8M daily logs by hand, always one step behind. Now engineers ask in plain language and act in minutes, not hours.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
350,000 track images reviewed by hand each month, always chasing failures. TrackDefectX now catches defects before they escalate.
Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
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.
Reactive management wasted resources. AI now forecasts contamination to optimize dosing, cutting energy consumption by 30%.
A water technology provider monitors treatment processes at over 100 plants across Latin America, impacting water quality for more than 1 million people.
Water treatment plants traditionally rely on reactive management, often leading to excessive chemical usage and energy waste. The company needed to...
“Water doesn’t wait, nor does the planet. That’s why we need to build solutions that facilitate water security. That includes public policy, engineering, and software and AI for making sure facilities run properly.”
AI platform for real-time optimization and management of water treatment facilities.
Cloud computing platform and on-demand infrastructure services.
AInwater's Water treatment optimization is part of this use case:
Related implementations across industries and use cases
Overtaxed servers left 13 legal models trailing as laws changed. AWS migration cut costs 40%, throughput up 170%, opened new markets.
Complex email chains bottlenecked utility agents. AI now summarizes 55k threads monthly, cutting handling time by 87%.
Case by case, bill disputes needed detailed human analysis—slow and inconsistent. An AI agent now resolves each from start to finish.
336 hours a month combing 8M daily logs by hand, always one step behind. Now engineers ask in plain language and act in minutes, not hours.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
350,000 track images reviewed by hand each month, always chasing failures. TrackDefectX now catches defects before they escalate.
Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
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.