AI workspace for M&A due diligence that turns sell-side dumps into source-linked findings, financial models, and investment memos for buy-side teams — not another data room.
Colabra AI uses GPT-6 Astra throughout its M&A due-diligence workflow. Astra preprocesses uploaded deal documents into structured evidence, then powers an agent that cross-checks contracts, financial statements, ownership records, and supporting files. It builds contract and debt registers, reconciles revenue and cap tables, identifies change-of-control clauses and missing evidence, and produces source-linked findings, financial models, and investment memos. Buyers can inspect the documents behind a finding and follow its impact through the analysis—for example, an unsupported earnings adjustment carried into the financial model and investment memo.
A finding is only useful if you can check what supports it and carry it into the work your team needs to do.
That's what we're building with Colabra, and AI workspace for M&A due diligence that turns sell-side dumps into source-linked findings, financial models, and investment memos for buy-side teams.
Our latest product, Colabra AI, is a Codex/Claude Cowork-style harness built for M&A diligence. It's connected to the data room data, allows you to seamlessly cross-check all the information cited in final reports, and deterministically ensures that the AI agent considers ALL available data before it produces its answer.
If you work on acquisitions, I'd love to hear which part of your diligence process still needs the most manual cross-checking.
Report
Maker
Hi, I’m Aoi, the other co-founder of Colabra.
We built Colabra because deal teams spend too much time piecing together information across spreadsheets, contracts, and reports to work out what they can rely on.
Due diligence requires understanding how the documents fit together. A single number in a financial model may depend on a customer contract, a later amendment, or supporting evidence that hasn’t been provided yet.
With Colabra AI, deal teams can now investigate a question across the entire data room and turn that analysis into custom financial models and investment memos they can check against the original documents.
I’d be interested to hear from people using AI for acquisitions today: how confident are you that your AI has considered all the relevant evidence before you rely on its analysis to make an investment decision?
My Signature Dish
My Signature Dish
Hi, I'm Philip, co-founder of Colabra.
A finding is only useful if you can check what supports it and carry it into the work your team needs to do.
That's what we're building with Colabra, and AI workspace for M&A due diligence that turns sell-side dumps into source-linked findings, financial models, and investment memos for buy-side teams.
Our latest product, Colabra AI, is a Codex/Claude Cowork-style harness built for M&A diligence. It's connected to the data room data, allows you to seamlessly cross-check all the information cited in final reports, and deterministically ensures that the AI agent considers ALL available data before it produces its answer.
If you work on acquisitions, I'd love to hear which part of your diligence process still needs the most manual cross-checking.
Hi, I’m Aoi, the other co-founder of Colabra.
We built Colabra because deal teams spend too much time piecing together information across spreadsheets, contracts, and reports to work out what they can rely on.
Due diligence requires understanding how the documents fit together. A single number in a financial model may depend on a customer contract, a later amendment, or supporting evidence that hasn’t been provided yet.
With Colabra AI, deal teams can now investigate a question across the entire data room and turn that analysis into custom financial models and investment memos they can check against the original documents.
I’d be interested to hear from people using AI for acquisitions today: how confident are you that your AI has considered all the relevant evidence before you rely on its analysis to make an investment decision?