DealDeploy reads every deck, model and call note before anyone asks, so Claude goes straight to the right page. Answers come back in seconds, on a fraction of the tokens.
The right answer in 34 seconds. Claude on its own took three and a half minutes, spent four times as much, and got it wrong. Same question from a portfolio review, same model. The timings are real. Only the names are changed.
Correct, matches the IC deck
Were the top 3 customers 50% of ARR when we invested in Halyard in 2024?
Search documents that mention Halyard
80 documents, newest first
Search passages on Halyard customer concentration
30 passages, in both IC decks
Read Commercial IC vFinal.pdf
Page 18: top 3 customer tables
and 3 more steps
Roughly, yes. The top 3 were 46% of 2023 ARR and 53% of 2024 committed ARR, from page 18 of the final IC deck.
Wrong, 2024 was 53%
Were the top 3 customers 50% of ARR when we invested in Halyard in 2024?
Walk folder Portfolio/Halyard
356 files listed
Download Halyard Commercial IC vFinal.pdf
Saved as a binary file, no text
Unzip and read Halyard Commercial IC vFinal.pptx
29 slides, customer table is an embedded chart
and 9 more steps
No. The deal materials put the top 3 customers at about 45% of ARR, not 50%. The customer table is a chart I couldn’t read, so I haven’t checked it.
Investors run a dozen one-off analyses a week. Each used to mean an associate digging through decks, models and board packs. Now it takes seconds.
Claude with DealDeploy
How did our original IC base case compare with what actually happened?
Reading
IC model, Project Ferris.xlsx · Base case tab, against Q2 actuals
Prep me for the board meeting. How did the company perform against its goals from last quarter? How is it tracking relative to budget?
Reading
Board deck, May.pptx · Page 6: goals for the quarter
When is the earnout paid out under the purchase agreement?
Reading
Purchase agreement, Project Atlas.pdf · Page 41: Section 2.6, Earnout
What other deals have we looked at in this market? Synthesize our thesis & risks.
Reading
IC memo, Project Kestrel.docx · Page 3: thesis and key risks
Now Claude remembers the deal your partner looked at two years ago, and who to ask about it.
Show me every deal we’ve looked at by industry over the past 3 years.
Pull every question we’ve ever asked management during diligence.
Which IC deals came from banked processes and which were proprietary, by year?
A weekly deal work plan every Monday morning, or an activity dashboard built for how your team runs.
“I did a portfolio analysis in 3 minutes that used to take me 3 hours.”
— Senior Associate, $2B PE fund
“Claude now updates our IC materials autonomously using the brain.”
— Investor, healthcare buyout fund
Portfolio questions get answered from the final IC deck, not a hunt through SharePoint. Asked whether a company’s top three customers were half of ARR, DealDeploy found both figures on page 18 in 34 seconds. Claude on its own missed the 2024 number. When a banker posts a data room update, revenue by segment is redrawn in about a minute.
One deal team ran a live process through DealDeploy, first call to IC, in a week: about thirty conversations from nearly the whole team. The advisor list, an NDA joinder drafted from a prior deal, every expert call on the company, even the ones with the name misspelled. A new IC slide built from this week’s expert calls, in the format of an earlier deck, takes about three minutes.
There is no setup for the user. Every conversation with your AI is equipped with the firm’s collective knowledge. Manual context gathering is over.
DealDeploy is the secure way for AI to reach your firm’s most sensitive information. It stays encrypted, private to your firm, and entirely yours. Your files are never used to train models, and only your people can reach them.
