---
title: Use Cases - Accelerate Due Diligence Page
description: Streamline private market due diligence by transforming scattered data into structured insights, enabling investment teams to focus on analysis and decision-making.
---
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# Accelerate private markets due diligence
Turn scattered track records and VDRs into structured, comparable data — so investment teams can focus on judgment and modeling, not data wrangling.
[Schedule a call](https://tamarix.tech/contact-us)
## Who this is for
- Investment teams
- Primary and secondary investors
- CIOs and Investment Committees
## The job today
Due diligence starts with data — but most of the effort goes into preparing it.
Primary teams sift through track record files to understand historical performance and manager behavior.
Secondary teams comb through VDRs to reconstruct fund exposures, cash flows, and asset-level details.
Across both cases, the pattern is the same:
- Data is scattered across PDFs, spreadsheets, and folders
- Formats vary by manager, fund, and deal
- Teams spend most of their time normalizing data just to make it usable
By the time models are built, deadlines are tight — and the underlying data work is rarely reused.
## Why this breaks at scale
### Time
Each new opportunity restarts the same process. Teams rebuild diligence datasets from scratch, deal after deal.
### Risk
Manual data handling increases the likelihood of:
- Inconsistent assumptions
- Missed details buried in documents
- Errors that propagate into models and IC materials
### Opportunity cost
The majority of diligence effort goes into data preparation — not:
- Analyzing risk
- Comparing managers
- Developing differentiated views
***Worse, once a deal closes or is passed on, the data is often lost.***
## How Tamarix enables this use case
Tamarix removes data wrangling from the diligence process.
- 01Ingest
- 02Monitor
- 03Manage
01 Ingest
### Ingest
Track records, VDR documents, and GP materials are collected and processed automatically.
02 Monitor
### Monitor
Data is extracted, structured, and normalized into a consistent format across deals, funds, and managers.
03 Manage
### Manage
Investment teams analyze opportunities using structured data that:
- Plugs directly into models
- Supports like-for-like comparisons
- Accumulates over time into a proprietary dataset
***Due diligence moves from document-heavy to insight-driven.***
## What changes
### Before Tamarix
- Diligence means rebuilding datasets from PDFs and spreadsheets for every opportunity.
### With Tamarix
- Data is structured once, reused across analyses, and retained to inform future decisions.
## Outcomes
LPs using Tamarix to accelerate due diligence typically achieve:
- Faster turnaround on investment evaluations
- Less time spent on data preparation
- More consistent and comparable analyses
- A growing proprietary view of managers, funds, and markets
***Diligence effort shifts from data wrangling to decision-making.***
## How this fits into the broader system
This use case is powered by Tamarix’s unified ingestion, validation, and analytics layer — the same foundation that supports portfolio monitoring, pacing, and reporting workflows.
Diligence data does not disappear.
It becomes part of the system.
## Due diligence shouldn’t start from zero every time.
It should compound.
[Schedule a Call](https://tamarix.tech/contact-us)
## FAQ — Accelerate Due Diligence
Answers to the most common questions about due diligence.
Does Tamarix support both primary and secondary diligence?
Yes. Tamarix supports diligence workflows for both primary investments and secondary transactions.
What types of documents can Tamarix process?
Tamarix can process track record files, VDR materials, fund reports, and other GP-provided diligence documents.
Can structured data be reused across deals?
Yes. Extracted data is retained and normalized, allowing teams to build a proprietary dataset over time.
How does this improve modeling workflows?
By delivering data in a consistent, structured format, Tamarix allows teams to focus on modeling and analysis rather than preparation.
How quickly can teams evaluate new opportunities?
Because data extraction and structuring are automated, teams can move from documents to analysis much faster than with manual workflows.
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