AI Transcription for M&A Due Diligence Calls: What to Look For (2026)

Short answer: for M&A due diligence calls, the best AI transcription setup is the one that meets four tests, not the one with the longest feature list. It must be allowed by your NDA and the people on the call, it must keep the audio and text somewhere you can name and delete, it must label who said what, and it must let you search every call at once and jump to the exact sentence. A transcript is a working copy of what was said, not a finding. A finding is a claim you can trace to a timestamp, a speaker and, ideally, a document.

Tool facts below were read on each vendor's own pages on 8 November 2026. They change often, so each one is dated and linked in the table. Where a vendor page could not be read or did not state something, we say so or leave it out.

What you actually need to capture

A deal produces more spoken information than most teams admit. Three kinds of call matter, and they ask different things of a transcription tool.

Management calls. These are the sessions with the seller's CEO, CFO and operations lead. Numbers get quoted from memory, definitions shift between speakers ("recurring" can mean contracted or merely repeated), and answers are often promises to follow up. You want a speaker-labelled record, because the same sentence means something different coming from the owner than from the bookkeeper.

Expert and customer calls. You speak to a former employee, a customer, a supplier or an industry specialist to test what the seller told you. Here the risks are confidentiality and consent. Many expert networks and customer arrangements restrict recording, and some forbid it. Read the terms before you press record, not after.

Q&A sessions with advisers. Calls with the seller's broker, accountants or lawyers are where the working capital definition, the add-backs and the representations are argued. They are the calls you will most want to quote later, and the ones where a wrong paraphrase costs the most.

Across all three, the transcript has one job: let you recover exactly what was said, by whom and when, without relying on anyone's memory of the call.

Test 1: are you allowed to record and transcribe it?

This comes before any product comparison, and no software answers it for you.

• Your NDA and the process letter. Some prohibit recording management sessions or storing seller information in third-party tools. If the document is silent, ask in writing. A one-line yes from the seller's adviser beats an assumption.
• Consent. Rules on recording calls differ by country and, within some countries, by region. Some places need every participant to agree. Announce the recording at the start, put it in the invitation, and let anyone say no. We are not lawyers and this is not legal advice; confirm the rule for each participant's location with your counsel.
• Expert networks and customers. If an intermediary arranged the call, its terms usually apply. Ask before using any bot that joins the meeting as a visible participant.
• Privileged calls. For calls with your own lawyer, ask the lawyer first. Putting a privileged discussion into a third-party system is a decision for them, not for the tool's defaults.

A habit worth adopting: if a call cannot be recorded, take notes by hand and date them as notes. Do not reconstruct a transcript from memory and call it one.

Test 2: where do the audio and the text go?

A transcription platform is a processor of confidential deal information. Ask the same questions you would ask of a data room.

1. Where is the data stored, and can you choose? Some vendors offer region or private storage only on top-tier plans.
2. Who can read it? Check default sharing. Many tools make a meeting visible to everyone in a workspace unless changed.
3. Is it used to train models? Vendors differ, and the wording matters. Read the exact sentence.
4. Can you delete it, and does deletion really delete? Look for the retention period after deletion and for admin-level deletion.
5. What is the legal basis? If the call includes personal data about employees or customers, your counsel will care about processor terms.

Here is what two vendors say on their own pages, read on 8 November 2026. We chose these two because both publish enough detail to compare; this is not a ranking, and we have not run a security assessment of either.

Read the Otter row on training twice. De-identified is not the same as excluded, and for a confidential acquisition you may want a plan or a setting where your calls are not used at all. That is a question to put to the vendor in writing, and the answer belongs in your deal file. The Fireflies page makes a different claim, "by default", which raises its own question: what does the non-default look like, and who can change it?

Neither page, as read, tells you what happens to a transcript once you export it into email, a shared drive or a chat tool. The export is yours to control.

Test 3: does it label speakers well enough to quote?

For diligence, speaker labels are not cosmetic. A sentence attributed to the wrong person is a false quote.

What to check in a trial, on your own audio and not the vendor's demo:

• Does it separate speakers without prior setup? Test with a call that has four or more voices and some interruptions.
• Can you name and fix speakers after the fact? Otter's pricing page lists "speaker identification" on every plan and, from the Pro plan, "team vocabulary and taggable speakers", which is relevant when the same names and company terms recur across calls. Fireflies' pricing page lists speaker talk-time analytics, which is a sales-call feature rather than a diligence one, and does not by itself say how labels are corrected.
• Does it handle accents, numbers and jargon? Test on a segment where someone reads out figures. Transcripts get numbers wrong more often than ordinary words, and a transposed digit in a revenue figure is exactly the error you cannot afford.
• Does it keep timestamps? Without them you cannot jump back to the audio to settle a dispute.

Plan limits matter here too. Otter's page states per-meeting limits of up to 90 minutes on Pro and up to 4 hours on Business, which could matter for a long management presentation. Check limits against your longest call before buying anything.

Test 4: can you search across every call?

On a live deal you may have 15 to 40 calls over a few weeks. The question is rarely "what was said in call 7"; it is "every time anyone mentioned the largest customer, the price increase or the warehouse lease."

Look for three things.

1. Cross-call search. Fireflies lists meeting search and global search on its pricing page, and Otter lists advanced search on its Pro plan. Whether the search is keyword or meaning-based, and how well it copes with names, is something you test on a sample.
2. Search that lands on the sentence. A result that opens the call at the right second is worth far more than a summary that says the topic was discussed.
3. Export. You need the full text with speakers and timestamps in a file you control, so your deal record survives a cancelled subscription.

If you use an AI chat box over your transcripts, apply the same rule you would apply to a CIM: every claim comes with a quote. Our guide to using Claude for due diligence describes the method, and the comparison of Claude and ChatGPT for diligence explains why the model matters less than the discipline.

Turning transcripts into cited findings

A transcript on its own creates a different risk: a lot of confident-sounding text with no verification. A usable workflow looks like this.

1. Name the claim. Write the claim as a sentence: "Customer A is about a fifth of revenue."
2. Find the sentence. Link the quote, the speaker and the timestamp.
3. Check it against a document. A spoken number is a lead until the CIM, the ledger or a contract confirms it. If they disagree, record both.
4. Mark who said it and in what capacity. A founder's estimate is not a representation in the purchase agreement.
5. Turn gaps into questions. What a seller promised to send becomes a line on the follow-up list with a date.

A simple findings table keeps this honest:

The two columns that matter most are the quote and the document check. Anything with an empty quote column is an impression, and anything with an empty document column is an unverified statement. This is the same cite-or-cut idea we use for documents: a claim without a source line does not go in the memo.

A short shortlist method

Instead of trusting a list that ranks products for you, build your own in an afternoon.

1. Write your four tests as pass or fail lines, with your NDA terms next to them.
2. Pick two or three candidates, and only count claims you can read on the vendor's own site, dated.
3. Run the same 30-minute recorded sample, with permission from the speakers, through each. Include a section with figures read aloud and a section with overlapping voices.
4. Score speaker accuracy, number accuracy and search on that sample, and keep the scores.
5. Send the vendor the confidentiality questions in writing and file the answers.
6. Only then check price and plan limits.

If your deal volume is small, it is reasonable to conclude that the right answer is a transcript made inside the video-call platform you already use, because it adds no new processor of the data. That is a legitimate option and sometimes the safest.

Where Deal OS fits, and where it does not

Deal OS does not transcribe calls. It reads deal documents, such as a CIM, and returns a brief where each figure is traced to its source page. It is a document reader, so it complements a call-transcription tool: the call tells you what the seller said, the document tells you what is written, and the gap between them is where questions come from. Its pricing page, read on 8 November 2026, states that the first CIM is free with no card, then $99 per CIM, and plans start at $249 per month. Prices are in USD and exclude VAT. See Deal OS for the current terms, and our due diligence software buyer's guide for the wider picture.

Frequently Asked Questions

What AI transcription platforms are best suited to M&A due diligence? The best fit is the one that passes four tests: recording is allowed under your NDA and consent rules, data storage and deletion are clear, speakers are labelled accurately, and you can search all calls and export the text. We do not rank products. Two vendors, Otter and Fireflies, publish enough detail to compare, and the table above dates what each page says.

Which platforms are worth shortlisting for searchable due diligence transcripts? Shortlist two or three that list cross-call search, speaker labelling and export on their own pages, then test them on the same recorded sample. Otter and Fireflies both list search features. Check plan limits, such as maximum meeting length, against your longest call before you pay.

Which AI tools make due diligence calls easier to capture and search? Meeting-recording tools that join your video calls and transcribe them, plus the transcription built into your call platform. The capture is the easy part. The value comes from timestamps, correct speaker names and a search that lands on the exact sentence.

Where can M&A teams find dependable AI transcription for deal research? Dependable means you have tested it on your own audio, read its storage and training terms, and have the answers in writing. No directory can give you that. Use the shortlist method above and keep the test scores in the deal file.

Is it safe to put a confidential deal call into an AI transcription tool? Only if your NDA allows it, every participant has agreed, and you have read the vendor's terms on storage, training and deletion. If any of those is unclear, ask in writing first, or take hand notes instead.

Can I trust an AI transcript as evidence of what a seller said? Treat it as a working copy. Transcripts can mishear names and numbers, so confirm important quotes against the audio at the timestamp, and confirm any figure against a document before it goes into a memo.