The prompt engineer vs the pre-trained analyst

ChatGPT The blank slate

To do diligence in ChatGPT, you must be the "prompt engineer." You have to upload the file, write the detailed instructions ("Review this for change of control..."), and manually verify the output. It is a powerful reasoning engine, but it is "stateless"—it does not know the context of your deal, your risk threshold, or the relationship between the 5,000 files in the zip.

Colabra The buy-side playbook

Colabra comes pre-loaded with the M&A intelligence. We automatically run hundreds of specialised prompts against the data room to categorise files, map entities, and flag risks. You do not need to tell us what to look for; our models already know that a "unilateral termination for convenience" clause is a red flag.

Why "building it yourself" is dangerous

Hallucination control

ChatGPT is designed to be helpful, which sometimes means inventing plausible answers. Colabra is designed to be accurate. We enforce a strict "No citation, no claim" architecture. Every risk we flag is physically linked to the source text. If the evidence isn't there, we don't flag it.

Entity resolution

ChatGPT sees "Acme Corp" and "Acme Inc" as text strings. It cannot reliably tell you if they are the same legal entity. Colabra uses a dedicated graph database to resolve entities, mapping the complex web of subsidiaries and ownership stakes that a simple text processor will miss.

Data isolation

Even with Enterprise privacy controls, uploading sensitive deal documents to a general-purpose chatbot carries optical and security risks. Colabra provides a dedicated, SOC 2 Type II compliant environment where your deal data is logically isolated, encrypted, and never mixed with consumer traffic.

See Colabra in action →