Manually extracting data from PDFs took 4 hours per loan, delaying approvals for weeks. Now, in-country AI securely structures the data.
A software provider builds digital lending platforms for complex financial operations across Europe, operating in highly regulated markets where data sovereignty is critical.
Processing unstructured financial statements like PDFs and scans manually took up to four hours per application, stalling credit decisions for weeks....
“Azure Red Hat OpenShift provided us with a foundation to move with speed, while being robust enough to run in a serious banking environment. Trust, reliability, and scalability is our license to operate.”
Composable banking platform for digital lending, mortgages, and wealth management.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Akkuro's Financial document processing is part of this use case:
Related implementations across industries and use cases
Brokers were bottlenecked manually re-entering data across systems. Now, AI reads incoming paperwork and runs real-time compliance checks.
Teams manually transcribed complex 300-page tax forms. Now, a specialist annotates one page and AI trains custom extraction models.
Trade data was buried in messy chat logs. GenAI now mines the text for pricing, turning raw noise into new revenue streams.
Brokers were bottlenecked manually re-entering data across systems. Now, AI reads incoming paperwork and runs real-time compliance checks.
Teams manually transcribed complex 300-page tax forms. Now, a specialist annotates one page and AI trains custom extraction models.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.
Manually extracting data from PDFs took 4 hours per loan, delaying approvals for weeks. Now, in-country AI securely structures the data.
A software provider builds digital lending platforms for complex financial operations across Europe, operating in highly regulated markets where data sovereignty is critical.
Processing unstructured financial statements like PDFs and scans manually took up to four hours per application, stalling credit decisions for weeks....
“Azure Red Hat OpenShift provided us with a foundation to move with speed, while being robust enough to run in a serious banking environment. Trust, reliability, and scalability is our license to operate.”
Composable banking platform for digital lending, mortgages, and wealth management.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Akkuro's Financial document processing is part of this use case:
Related implementations across industries and use cases
Brokers were bottlenecked manually re-entering data across systems. Now, AI reads incoming paperwork and runs real-time compliance checks.
Teams manually transcribed complex 300-page tax forms. Now, a specialist annotates one page and AI trains custom extraction models.
Trade data was buried in messy chat logs. GenAI now mines the text for pricing, turning raw noise into new revenue streams.
Brokers were bottlenecked manually re-entering data across systems. Now, AI reads incoming paperwork and runs real-time compliance checks.
Teams manually transcribed complex 300-page tax forms. Now, a specialist annotates one page and AI trains custom extraction models.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.