# Realresultsfromrealteams

We get to the root of the problem, and then solve it delivering on the quantified benefits.

### Insurance
**80% Less Time on Data Requests with Self-Learning AI**  
An enterprise insurance team was drowning in ad hoc data requests. A self-learning AI agent that writes its own SQL and Python code cut analyst time by 80% and gave non-technical users direct data access.  
**80%**  
Reduction in analyst time  
[Link](/content/case-studies/self-learning-data-requests/index.html)

### Venture Capital
**Automating Monthly Portfolio Reports for a VC Fund**  
A Taiwan-based VC fund's finance team spent hundreds of hours manually writing monthly reports for portfolio companies. An AI system now generates them automatically, matching the fund's format and tone.  
**100s**  
Hours saved per month  
[Link](/content/case-studies/financial-report-generation/index.html)

### Sales
**Querying Billions of Rows of LinkedIn Data in Seconds**  
An outbound agency needed to find ideal prospects across billions of LinkedIn records. BetterBrain built ML models that write and execute SQL from natural language, driving over $600K in revenue.  
**>$600K**  
Revenue in 6 months  
[Link](/content/case-studies/linkedin-data-querying/index.html)

### Real Estate
**Structuring Thousands of Files from Internal and External Sources**  
A mid-market real estate firm needed to enrich and structure data from thousands of files in different formats. AI agents using web search, enterprise search, and custom tools made previously impossible analysis routine.  
**1000s**  
Files structured automatically  
[Link](/content/case-studies/data-enrichment-structuring/index.html)

### Venture Capital
**Enterprise Search for Faster Due Diligence**  
A VC fund needed to synthesize information from CRM, Airtable, Slack, and Google Drive for due diligence. Custom enterprise search surfaced long-forgotten insights that changed investment decisions.  
**10x**  
Faster due diligence  
[Link](/content/case-studies/vc-due-diligence-search/index.html)

### Financial Services
**Combining Internal Knowledge with External Intelligence**  
A back-office services firm needed to search across CRM, Slack, Google Drive, LinkedIn, and the web simultaneously. A ChatGPT-style interface gave every employee instant access to collective intelligence.  
**Significant**  
Time saved searching  
[Link](/content/case-studies/internal-external-search/index.html)

### Non-Profit
**Matching Mentors to Companies at Scale**  
A Latin American accelerator needed to match the right mentors to each company based on stage, geography, and industry. RAG-powered matching transformed how a 200-person team operates.  
**200**  
Team members supported  
[Link](/content/case-studies/mentor-matching/index.html)

### Banking
**Source Attribution API for a Major Bank**  
A large bank needed to know exactly where its AI systems were finding information and whether it was accurate. A source attribution platform connected all data sources and traced every answer to its origin.  
**Trust**  
Built in AI systems  
[Link](/content/case-studies/source-attribution-api/index.html)

### Venture Capital
**Automating End-to-End VC Deal Screening**  
A UK venture capital firm needed to clean, deduplicate, and classify 30,000+ companies from PitchBook and other sources. Automated screening reduced manual processing by over 90%.  
**>90%**  
Less manual processing  
[Link](/content/case-studies/vc-screening-automation/index.html)

### Document Management
**Automating Document Classification, Renaming, and Structuring**  
An enterprise document management team needed to classify, rename, and organize files at scale. AI replaced what previously required a multi-person full-time team.  
**Full team**  
Of manual work automated  
[Link](/content/case-studies/document-classification/index.html)

### Insurance
**Processing Insurance Documents on AWS at Scale**  
An insurance enterprise needed to extract, classify, and structure data from thousands of policy documents. Built on AWS with OCR and NLP pipelines, the system cut processing time dramatically.  
**80%**  
Faster document processing  
[Link](/content/case-studies/aws-document-processing/index.html)

100% of our implementations are in production or on track.