A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
An Australian fintech platform managing a home loan book of more than AU$107 billion across a national network of 1,350 brokers and 215 retail stores.
A post-merger data infrastructure bloated to over 500 deployable components across mixed databases forced developers to spend time tuning systems...
“It is like having an expert watching over your home loan 24x7.”
Fintech platform for home loan comparisons and mortgage broking services.
Multi-cloud developer data platform for building and scaling applications.
Lendi Group's Home loan assistant is part of this use case:
Related implementations across industries and use cases
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
API latency bottlenecked live AI compliance checks. Faster open-source LLMs unlocked instant validation, processing up to 15x the tasks.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
Scattered across legacy systems, mid-market banks bore big-bank regulations. Constantinople runs the platform so banks run the business.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
Most AI tools addressed one step—code review or a single feature—and couldn't run in-house. Factory covers the full SDLC, on-premise.
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.
A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
An Australian fintech platform managing a home loan book of more than AU$107 billion across a national network of 1,350 brokers and 215 retail stores.
A post-merger data infrastructure bloated to over 500 deployable components across mixed databases forced developers to spend time tuning systems...
“It is like having an expert watching over your home loan 24x7.”
Fintech platform for home loan comparisons and mortgage broking services.
Multi-cloud developer data platform for building and scaling applications.
Lendi Group's Home loan assistant is part of this use case:
Related implementations across industries and use cases
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
API latency bottlenecked live AI compliance checks. Faster open-source LLMs unlocked instant validation, processing up to 15x the tasks.
Fragmented pipelines slowed cross-site suggestions. A unified AI vector database cut latency 90%, processing 1,500 queries per second.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
Scattered across legacy systems, mid-market banks bore big-bank regulations. Constantinople runs the platform so banks run the business.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
Most AI tools addressed one step—code review or a single feature—and couldn't run in-house. Factory covers the full SDLC, on-premise.
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.