0
%
Overall efficiency improvement versus the manual approach
0
+
Companies researched for employee count sourcing
200
hr
Manual hours reduced through AI-assisted lookup
Screening 3,000+ Companies to Build a Comprehensive Employee Count Sourcing List
About the Client
A boutique investment bank scaling its deal origination process
engaged TresVista to support the scaling of its deal origination process by building a comprehensive sourcing list of target companies and investors. The engagement required collating accurate employee counts across 3,000+ companies, drawing from multiple credible databases and maintaining consistent quality throughout.
Business Challenge
Four barriers to scalable, accurate list building
• Manual research at scale
Manually sourcing employee counts for 3,000+ companies across multiple databases was highly time-intensive, placing significant strain on the team’s capacity
• Quality control burde
Verifying data against credible sources such as FactSet, CapIQ, company websites, and annual reports created a significant quality-control burden across the full dataset
• Consistency across thousands of entries
Maintaining a consistent sourcing methodology, formatting standard, and documentation approach across thousands of individual entries was difficult without a structured framework
• Resource constraints on repetitive work
Limited team capacity restricted the ability to execute large-scale, repetitive data collection efficiently, slowing the pace of list building
Strategic Approach
TresVista's Solution: AI-assisted list building powered by structured prompts and human oversight
TresVista designed and implemented an AI-assisted list-building framework, combining structured prompt-driven lookup, automated extraction from credible sources, and standardized output formatting, with analyst oversight applied at the validation and edge-case layer
01
AI-Assisted Company Research
TresVista used ModelML with structured prompts to execute employee count lookups across every one of the 3,000+ entries, automating the most repetitive and resource-intensive phase of the research process
02
Automated Data Extraction
Data was systematically extracted from credible sources including FactSet, CapIQ, company websites, and annual reports, with source references logged against each entry for traceability
03
Standardized Formatting and Documentation
TresVista applied a consistent formatting and sourcing methodology across the full dataset, ensuring the output was clean, comparable, and immediately usable by the client's origination team
04
Human Review and Validation
TresVista analysts reviewed outputs for domain validation, source checks, and edge cases where automated lookup produced incomplete or conflicting results, applying judgment where automation reached its limits
TresVista Impact
3,000+ companies. A reusable framework. 40% less time.
Before
200+
hours
After
120
hours
40%
less time
~80 hrs Saved per engagement
Reinvested in higher-value origination work.
Outcome
- Reduced execution time by approximately 40%, cutting the engagement from 200 hours to around 120 hours while covering the full universe of 3,000+ companies
- Automated initial lookup across all 3,000 entries, eliminating most of the resource-intensive manual work and redirecting analyst time toward verification and judgment-intensive tasks
- Standardized data formatting and sourcing methodology delivered a clean, audit-ready output usable directly for prospecting and deal origination
- Enabled faster re-runs and list refreshes using the same prompt framework, giving the client a scalable tool for future sourcing needs
Tools & Technologies
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