Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Vietnam's leading enterprise software company, serving more than 450,000 government and business customers and 3.5 million individual users across accounting, tax, sales, HR, and public administration workflows.
Dependence on external LLM APIs created high operational costs, data security gaps, and latency problems for sensitive enterprise and government...
“NVIDIA's solutions not only enhance processing speed, system stability, and task-specific accuracy, but also establish a strong foundation for MISA to fully master the technology, including research, training, deployment, and security assurance, in order to deliver the best AI solutions to customers.”
Enterprise software for accounting, HR, CRM, e-invoicing, and government solutions.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
MISA's Enterprise workflow automation is part of this use case:
Related implementations across industries and use cases
Standard OCR failed on complex layouts. Vision-language models now automate matching, cutting validation effort by 40%.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Vietnam's leading enterprise software company, serving more than 450,000 government and business customers and 3.5 million individual users across accounting, tax, sales, HR, and public administration workflows.
Dependence on external LLM APIs created high operational costs, data security gaps, and latency problems for sensitive enterprise and government...
“NVIDIA's solutions not only enhance processing speed, system stability, and task-specific accuracy, but also establish a strong foundation for MISA to fully master the technology, including research, training, deployment, and security assurance, in order to deliver the best AI solutions to customers.”
Enterprise software for accounting, HR, CRM, e-invoicing, and government solutions.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
MISA's Enterprise workflow automation is part of this use case:
Related implementations across industries and use cases
Standard OCR failed on complex layouts. Vision-language models now automate matching, cutting validation effort by 40%.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.