TeamSystem
Enterprise search
Data silos across 300+ products made navigating fiscal regulations slow. A unified AI assistant now securely answers complex user queries.
- 30-40% reduction in task completion times
- Scaled AI platform to 500,000 users
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
Data silos across 300+ products made navigating fiscal regulations slow. A unified AI assistant now securely answers complex user queries.
Rising volume buried agents in manual tasks. AI now fields routine chats and writes summaries, cutting wrap-up time in half.
API latency bottlenecked live AI compliance checks. Faster open-source LLMs unlocked instant validation, processing up to 15x the tasks.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
Manual reviews of complex financial docs couldn't keep pace. Claude now masters the nuance, cutting review times by 50%.
Minor compliance updates once forced full video reshoots. Now, course creators generate and edit AI avatar videos directly from text.
Shifting to B2B sales exposed disconnected workflows and anecdotal forecasts. Now, AI analyzes interactions to surface deal intelligence.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
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
Data silos across 300+ products made navigating fiscal regulations slow. A unified AI assistant now securely answers complex user queries.
Rising volume buried agents in manual tasks. AI now fields routine chats and writes summaries, cutting wrap-up time in half.
API latency bottlenecked live AI compliance checks. Faster open-source LLMs unlocked instant validation, processing up to 15x the tasks.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
Manual reviews of complex financial docs couldn't keep pace. Claude now masters the nuance, cutting review times by 50%.
Minor compliance updates once forced full video reshoots. Now, course creators generate and edit AI avatar videos directly from text.
Shifting to B2B sales exposed disconnected workflows and anecdotal forecasts. Now, AI analyzes interactions to surface deal intelligence.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.