Pre-Close
Workforce data is in every data room. The expertise to interpret it may not be.
Bohdi processes the workforce data in your data room and delivers deal-level intelligence. Specific, named, dollarized, and connected to the investment thesis.
What Bohdi sees
Every deal has a workforce story. Bohdi reads it.

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What Bohdi surfaces
Not HR findings. Deal model inputs.
Compensation Exposure
A compensation gap you know about before close is a planning input. One you find after close leaves you with few good options.
- Underpay critical roles and people leave
- People leaving means lost institutional knowledge and broken customer relationships
- Attention shifts to backfilling instead of executing the value creation plan
Key-Person Risk
Does the org have the capabilities the value creation plan is betting on?
- Critical capabilities may exist in only one person with no backup
- Missing capabilities you don't know about become surprises in the execution plan
- If you know before close, it's a build or buy decision - and a financial model input
Management Claims
Management presents the best version of their organization during diligence. The data tells the full story.
- Claims about lean operations, competitive comp, and bench strength get tested against actual workforce data
- Every discrepancy is a conversation that needs to happen before close
- Some change the price. Some change the thesis.
Org-Thesis Alignment
The org you're buying may not be built for the plan you're betting on.
- Too many layers that slow decisions
- Spans of control that dilute accountability
- Reporting relationships aligned to how a founder wanted to run their company, not to how value gets created
The value
A conversation that creates clarity.
Bohdi
Workforce Diligence
Bohdi engages each analyst individually and the deal team collectively in a conversation about the workforce behind the deal. Every risk he surfaces comes with the source data behind it. Every management claim is tested against what the data room actually shows.
He helps the team model scenarios, tracks every open item, and stays in the conversation until the deal is done. What comes out is clarity on the workforce behind the deal, a financial model that reflects what the data actually shows, and a complete picture your operating partner can execute against from day one.
How Bohdi is different
Deep HR M&A expertise. Embedded. Repeatable. Available to every firm.
Starts inside the data room
Bohdi starts inside the data room - not outside it.
- Every job description, compensation file, org chart, and HRIS export becomes deal intelligence before close
- Most diligence relies on market benchmarks, industry surveys, and management interviews - Bohdi starts with the actual data
- When data is missing or incomplete, Bohdi tells you - and tells you what it means for the analysis
Person-level, not aggregate
Bohdi works at the level where risk actually lives - the individual role.
- A compensation benchmark that looks fine across Engineering can mask three critical roles significantly below market
- An org chart that looks stable in summary can hide single-threaded dependencies that put the thesis at risk
- Averages hide things. Bohdi surfaces them.
Compounds across deals
Most diligence starts from scratch on every deal. Bohdi doesn't.
- Every engagement builds pattern recognition across your portfolio
- What workforce structures correlate with execution risk. What management claims most often diverge from the data.
- That intelligence compounds into an edge no single firm builds on its own
Your data is safe
A standard of data security built for private equity.
Fund-level isolation
Every fund's data is isolated. What Bohdi learns within your portfolio stays within your portfolio - informing every subsequent engagement, never shared outside your fund.
Private infrastructure
PropulsionAI is built on private infrastructure - not shared cloud environments. Your data never lives alongside another firm's.
SOC 2 Type II certified.
GDPR in progress.
Built to the standard the transaction already demands.