0
%
Reduction in deal logging execution time
0
%
Accuracy achieved with analyst review and validation
0
%
Increase in deal coverage through AI-enabled processing
From Manual Logging to an AI-Validated Deal Repository: Scaling Pipeline Intelligence for PE
About the Client
A lower-middle market PE firm scaling its deal-tracking infrastructure engaged TresVista to streamline the capture and management of deal-related information across its investment pipeline, with the goal of creating a standardized repository of deal data, improving execution efficiency, and enhancing the scalability of deal-tracking workflows.
Business Challenge
Four barriers to efficient, scalable deal logging
• Manual extraction from fragmented sources
Manual extraction of deal information from teasers, CIMs, presentations, and emails required significant analyst effort, with relevant data scattered across inconsistent document formats
• Inconsistency and error risk
The process was susceptible to inconsistencies and errors, necessitating extensive review and validation before deal records could be relied upon
• Time-consuming record maintenance
Maintaining complete and accurate deal records across the pipeline was time-consuming, particularly as the volume of active deals grew
• Scalability under rising deal volume
Growing deal volumes created challenges around scalability and turnaround times, limiting the team’s ability to keep pace without expanding headcount
Strategic Approach
TresVista's Solution: A Microsoft Copilot-based deal logging agent built on a Human-in-the-Loop model
TresVista designed and deployed a deal logging agent leveraging Microsoft Copilot, combining automated extraction with structured human-in-the-loop validation to deliver accurate, standardized deal records at scale.
01
AI-powered deal information extraction
TresVista deployed a Copilot-based deal logging agent to extract and structure key deal information from teasers, CIMs, investment presentations, and email content, automating the initial capture phase across the pipeline
02
Standardized deal data repository
TresVista built a standardized repository for deal data across the pipeline, ensuring all extracted information followed a consistent structure regardless of source document type
03
Human-in-the-loop validation
Analysts reviewed and validated agent-generated outputs, ensuring accuracy, completeness, and quality before deal records were finalized in the repository
04
Transition to thematic deal summaries
TresVista shifted the workflow from manual field-by-field data entry toward agent-driven thematic deal summaries, improving both the depth and usability of the output for investment teams
TresVista Impact
Faster logging. Higher coverage. A scalable model.
Before
100%
Baseline Effort
After
70%
Of Baseline Effort
18%
less time
~30 hrs Reduction in execution time per engagement
Reinvested in higher-value deal evaluation work.
Outcome
- Reduced end-to-end deal logging execution time by 30%, freeing capacity for higher-value evaluation work
- Improved execution accuracy, achieving over 85% accuracy with analyst review and validation built into the workflow
- Increased deal coverage by approximately 30% through AI-enabled processing, allowing the team to track a larger share of pipeline activity
- Supported faster deal evaluation and review cycles, enabling teams to manage higher deal volumes without proportional increases in resourcing
- Created a scalable model that can be adopted across clients without disrupting existing processes, positioning the framework for broader rollout
Tools & Technologies
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