0
%
Overall efficiency improvement versus the manual approach
0
+
Detailed company profiles prepared for buyer identification
60
hrs
AUM of the global PE firm served
From 60 Hours to 42: AI-Assisted Buyer Profiling for a Bulge-Bracket Investment Bank
About the Client
A bulge-bracket investment bank accelerating buyer identification
engaged TresVista to prepare timely, comprehensive buyer profiles that would accelerate buyer identification and outreach for a portfolio company sale process, covering 40 potential buyers across diverse sector exposures.
Business Challenge
Four barriers to fast, high-quality profile creation
• Depth of research required per profile
Creating 40 detailed company profiles covering business descriptions, key corporate facts, financial snapshots, products and services, M&A history, and synergy alignment required extensive manual research for each entry
• Standardization without sacrificing quality
Output needed to be standardized across all 40 profiles while preserving the relevance and quality expected in a live buyer identification process
• Fragmented data sources
Sourcing and synthesizing data from multiple sources including filings, news, and industry reports was time-intensive across the full buyer set
• Rigor in synergy assessment
Maintaining analytical rigor in synergy assessment was challenging given the diverse sector exposures represented across the 40 potential buyers
Strategic Approach
TresVista's Solution: AI-assisted profile creation powered by targeted prompts and human-led refinement
TresVista designed and implemented an AI-assisted profile creation framework, combining targeted prompt-driven research, structured data-dump generation, and standardized templates, with human-led refinement applied to sharpen the acquisition thesis for each buyer.
01
AI-Assisted Initial Company Search
TresVista used ModelML with targeted, consistent prompts to generate structured data dumps for each of the 40 potential buyers, automating the initial research and collation phase.
02
Pre-formatting to Output Criteria
Information was pre-formatted against expected output criteria and preferred sources, aligning each data dump to the standardized profile structure before analyst review
03
Standardized Profile Templates
TresVista applied a consistent template covering business description, key corporate facts, financial snapshot, products and services, and M&A history across all 40 profiles
04
Human-in-Command and Thesis Refinement
TresVista analysts reviewed each profile to validate relevance, sharpen the acquisition and synergy thesis, and handle exceptions where automated research required additional context
TresVista Impact
40 profiles. A reusable framework. 30% less time.
Before
60+
hours
After
42
hours
30%
less time
~18 hrs Saved per engagement
Reinvested in sharpening buyer outreach strategy.
Outcome
- Reduced execution time by approximately 30%, cutting the engagement from 60 hours to around 42 hours across all 40 profiles
- Eliminated the manual data collation step through AI-assisted initial research and structuring, freeing analyst time for higher-value synergy analysis
- Standardized company profile structure and presentation quality, ensuring consistency across the full buyer universe
- Improved scalability for larger profile sets and faster future refreshes, using the same targeted prompt framework
Tools & Technologies
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