Overtaxed servers left 13 legal models trailing as laws changed. AWS migration cut costs 40%, throughput up 170%, opened new markets.
A 2023 Brazilian legal-technology startup with 13 proprietary small language models built to automate legal research, document analysis, and routine workflows for legal professionals.
As user adoption and data volumes grew, the company's existing compute infrastructure couldn't provide the training speed or scalability needed to...
“Our proprietary models require continual training on high-quality datasets. But we couldn’t maintain service quality with the existing infrastructure.”
AI operating system for legal and regulated workflows.
Cloud computing platform and on-demand infrastructure services.
Forlex's Legal workflow automation is part of this use case:
Related implementations across industries and use cases
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Contract routing took 2 days of manual checks. AI now finishes in 60 minutes, escalating only complex exceptions for human review.
Complex protocols blocked user adoption. AI agents now execute wallet setup and swaps from natural language, driving 330k signups.
Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Manual analysis limited teams to three scenarios. Now, 1,000+ AI agents run 100,000+ real-time simulations to automate decisions.
IR research meant sifting hundreds of SharePoint docs by hand. Now specialized agents route and synthesize it—26% faster, citations sharper.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Overtaxed servers left 13 legal models trailing as laws changed. AWS migration cut costs 40%, throughput up 170%, opened new markets.
A 2023 Brazilian legal-technology startup with 13 proprietary small language models built to automate legal research, document analysis, and routine workflows for legal professionals.
As user adoption and data volumes grew, the company's existing compute infrastructure couldn't provide the training speed or scalability needed to...
“Our proprietary models require continual training on high-quality datasets. But we couldn’t maintain service quality with the existing infrastructure.”
AI operating system for legal and regulated workflows.
Cloud computing platform and on-demand infrastructure services.
Forlex's Legal workflow automation is part of this use case:
Related implementations across industries and use cases
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Contract routing took 2 days of manual checks. AI now finishes in 60 minutes, escalating only complex exceptions for human review.
Complex protocols blocked user adoption. AI agents now execute wallet setup and swaps from natural language, driving 330k signups.
Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Manual analysis limited teams to three scenarios. Now, 1,000+ AI agents run 100,000+ real-time simulations to automate decisions.
IR research meant sifting hundreds of SharePoint docs by hand. Now specialized agents route and synthesize it—26% faster, citations sharper.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.