∞Direct answer
Direct answer
An investment thesis is a plan for the firms an investor wants. AI can turn it into clear rules and a founder list. It can show facts that fit and facts that do not. A person must check the list. AI can speed sourcing and prep. It cannot pick an investment, replace due diligence, or promise funding.
1. Turn the mandate into a clear brief
Make a one-page plan card. A team mate should be able to use it. Add stage, country, sector, and check size. Add share needs, follow-on plans, and no-go rules. State what proof puts a firm in scope. Split firm rules from wants. AI cannot fix a vague thesis.
Turn each rule into a clear sign. Add a rule for doubt. A stated country may be a filter. An assumed customer mix stays unproved until a person checks it. Give each yes, no, and unknown a code. This is a work guide, not investment advice.
2. Set data rules before collection
Keep a source list. Note the source and terms. Note allowed use, fields, date, owner, and refresh rule. Use public data only if the terms allow it. Local law must allow it too. A public profile does not allow copying, adding data, or contact.
For personal data, note the aim. Note the lawful basis. Give the right privacy note. Keep only what you need. The ICO says the basis and aim must be in that note [2]. Seek advice if data is sensitive. Do the same if it crosses borders.
3. Build a company ledger
Give each firm a set ID. Keep its name, web domain, known country, and source links. Keep the date and proof. Check the domain first. Check the legal name too. Then use AI to find close matches. Send merges and conflicts to a reviewer. Do not merge them in secret.
Facts grow old. Funding status can shift. So can product focus and team roles. Date each key fact. Set a time to check it. Mark old or missing proof. Show what the system does not know.
4. Show proof for and against the fit
Show plan fit and proof links. Show gaps. Show conflicts. Show facts against the fit. Ask AI to find such facts. It may flag a wrong stage. It may flag a barred country or unclear model. A reviewer should reject a firm with no need to decode a hidden score.
Keep proof strength apart from appeal. It shows the source. It also shows the date of proof. It does not show that a firm will do well. NIST offers a voluntary AI risk guide [1]. Keep prompts, test sets, reviewer changes, and error logs.
5. Keep sourcing, due diligence, and introductions apart
Sourcing finds firms. Due diligence means checks before investing. It tests claims and risks. It also tests key facts. Keep it apart from sourcing. A sourcing note may give key questions for a data room or founder call. It is not proof.
Before an introduction, check who may share what. Write down the choice. These checks are not full investor due diligence. They are not regulated advice.
Keep networking apart from regulated placement work. In the United States, the SEC says some work may show broker activity. It includes finding investors. It includes helping with securities trades. It also includes taking pay tied to a trade. Regulation D placement agents are not always free from broker-dealer registration [3]. This is a U.S. example, not legal advice. Get qualified advice for each country. Review the pay plan and task.
Master Collective’s AI due-diligence feature can sort facts. It can help plan checks. The platform can help with useful networking and introductions. It does not give full investor due diligence. It does not give regulated advice. It does not promise funding.
6. Measure the work, not returns
Review this flow on a set plan. Track firms that reviewers approve. Track analyst time. Track proof age. Track duplicate and wrong-merge rates. Track records with facts against fit. Set each measure first. Keep the review set.
Do not use fund returns as the only score. They come late. They show firm choice and cash split. They also show price, follow-on calls, and the market. Test changes on the same plan and review rule. Check errors. Change one control at a time. This can improve the work. It does not prove investment gains.
FAQ
Frequently asked questions
What sources can an AI sourcing flow use?
Use sources that your firm may access and use for the stated aim. Keep terms and source. Keep the date and contact or privacy limits. For personal data, check the law and country. Public access does not end your duties.
Can a high AI score replace due diligence?
No. A score can sort proof by the plan. It cannot check claims. It cannot solve legal or business risk. It cannot make an investment choice. Use it as a review queue. Take key questions into due diligence.
When should a company get an introduction?
When a person checks plan fit and proof age. They must also check data that may be shared. The introduction should be useful and agreed. It is not an endorsement. It is not investment advice or a sign of funding.
How can an investment team tell if the flow gets better?
Track reviewer-approved fit and analyst time. Also track proof age and errors. Test like-for-like plans. Keep returns apart from sourcing quality.
REF
Sources
- 1
National Institute of Standards and Technology (NIST)
AI Risk Management Framework ↗ - 2
Information Commissioner's Office (ICO)
A guide to lawful basis ↗ - 3
U.S. Securities and Exchange Commission (SEC)
Guide to Broker-Dealer Registration ↗