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What is research and screening?
Research and screening turns an investment mandate into a documented view of which opportunities merit further work. Reuben AI connects that view to sources, open questions and the diligence that follows.
Written by Katriona Lee, Founder, Reuben AI
Last reviewed
Research and screening is a structured part of an investment process, with an identifiable question, an evidence base and an accountable handoff. Its purpose is not to produce more paperwork. It is to make the reasoning behind a recommendation understandable to someone who did not conduct the original research. The scope should reflect the investment mandate, the asset or entity under review and the decision being requested. A useful record separates facts, assertions, assumptions and unresolved questions. It also states the limits of the work, including areas that require specialist review. This guide describes a practical process rather than a promise about investment outcomes.
Reuben AI is decision infrastructure for private capital. It brings diligence, research and the investment committee into one connected record, so every decision is consistent, evidence-based and traceable to its source. Judgement stays human. The process becomes disciplined.
Write down the customer problem, relevant geography, investment structure and reasons an opportunity might not fit. Distinguish exclusions from preferences so a promising narrative cannot quietly change the brief. Agree what evidence would justify further investigation and what would require a pass.
Describe buyers, suppliers, substitutes, distribution and the practical constraints on adoption. Keep the scope of each source visible, including its publication context and the segment it actually covers. A broad industry report does not establish demand for a particular company or product.
Ask each opportunity to answer the same mandate questions. Record direct evidence separately from management assertions and analyst assumptions. Where a comparison is not meaningful, explain why rather than filling a blank with a confident description.
Write a short recommendation to investigate, defer or pass, with the reasons and unresolved questions attached. Carry the original thesis into diligence so the next reviewer can see what must be tested. Screening is a prioritisation decision, not investment approval.
These mistakes have a shared cause: the summary becomes detached from the work behind it. Before a handoff, ask a colleague to trace a material conclusion back to its source and explain what would change the recommendation. If they cannot do that, clarify the reasoning before polishing the presentation. A concise qualification is more useful than an unsupported conclusion, and an explicit open question is more useful than an empty field that looks complete.
Illustrative example, not a client case study: consider a specialist business serving industrial customers. The team begins by writing the decision question and linking the initial thesis to the material available. A management presentation supports the proposed opportunity, but a supporting document leaves an important assumption uncertain. The analyst records the disagreement rather than smoothing it into a positive summary. The workstream owner requests the underlying evidence and explains how the answer could change the recommendation. When the response arrives, the reviewer checks whether it addresses the actual question, records its limitations and updates the finding. The committee sees both the revised view and what remains open. If it proceeds subject to a condition, that condition moves into ownership with a named owner. A later review compares new information against the same assumption. The example illustrates the chain from evidence to judgement without assuming that the investment succeeds or inventing commercial results.
A reference guide is useful only if a reader can distinguish what is known from what is inferred. Give each important claim a source, explain the source’s relevance and keep any qualification beside the conclusion it affects. A source can be genuine and still be insufficient for the decision. For example, a statement about a broad industry may not apply to a particular customer segment, contractual arrangement or jurisdiction. The reviewer should be able to follow the reasoning without guessing which passage mattered. Where sources conflict, explain the conflict and the next question rather than silently selecting a preferred version.
Name the person responsible for the next action and explain what would count as a satisfactory response. A request to obtain more information is not complete until someone has considered what that information means. The review should distinguish a closed question from an accepted risk and from a matter outside scope. Preserve the reason for each status so another colleague can continue the work. If the scope changes, record the change explicitly. This makes the process usable when responsibilities move between research, diligence, committee preparation and portfolio oversight, without suggesting that a standard template replaces professional judgement.
Use only information the team is authorised to access and share. Confirm the appropriate audience before circulating a source or a summary derived from it, particularly when external advisers or platform partners are involved. Keep the decision record separate from any suggestion that software provides legal, tax or investment advice. Teams remain responsible for their governance arrangements and the decisions they make. Deployment and integration requirements should be scoped with Reuben AI rather than assumed from a workflow description. A useful evaluation starts with the team’s evidence and review requirements, then checks how the proposed setup supports them.
Data residency is available in APAC, EMEA or the Americas, with the region agreed during onboarding.
How does this work connect to the next decision? Use the other topic guides to follow the evidence through research, diligence, committee preparation and ownership review.
Discover companies, funds and managers. Choose a directory that matches your investment research, then bring a clear mandate to the next stage of diligence.
Discovery starts the living decision record. Sources, mandate fit and initial questions travel with an opportunity into living diligence instead of being recreated after sourcing.
Start your company research with the Reuben AI startup directory. For venture investors, angel groups and investment teams, discovery begins with understanding which businesses merit a closer look.
Explore directoryResearch established businesses through the Reuben AI mid-market directory. A starting point for private equity, acquisition and corporate development teams assessing companies against a defined mandate.
Explore directoryFind a starting point for fund and manager research. The Reuben AI funds and managers directory serves a different question from company discovery: which investment organisations warrant further assessment for your allocation strategy?
Explore directoryDiscovery initializes the Living Record for every prospect. Start with the investment question: a company to assess, an established business to research, or a fund manager to evaluate. A useful shortlist captures why an organisation is relevant, what evidence is available and what still needs to be checked. Carrying these open questions into diligence ensures the record remains connected from the first touch.
Reuben AI's platform unifies discovery, diligence and governance into the Living Record. Directory research initializes this record, ensuring that mandate fit and open questions are carried forward into the diligence cluster rather than lost in separate documents.
Private markets market research usually arrives as a one-off report: a sector deck, a manager shortlist, a list of companies. By the time diligence starts, parts of it are already out of date and nobody can say which source each conclusion came from.
Continuous market research works differently. Companies, funds, managers and sectors are tracked against the team's thesis, and new evidence attaches to the same record. When an opportunity moves into diligence, the team starts from a current, sourced view rather than from a stale document.
AI market research for private equity is most useful in the collection and comparison steps: gathering sources, extracting claims and setting supporting and contrary evidence side by side. People still decide what matters and what the thesis is.
How it works on one record: Reuben AI connects evidence across the asset or portfolio company, deal, vehicle, fund, manager, portfolio. A thesis finding about a sector can carry straight into diligence on a company in that sector, with its sources intact. The same fully sourced record carries context from discovery through diligence, committee decisions and ownership review. Judgement stays human. See the six levels of private markets diligence, from thesis to vehicle and the continuous diligence guide.
Software that runs continuous market research on companies, sectors, managers and themes, and links each finding to its source so it can feed screening, diligence and investment committee decisions.
The ongoing tracking of companies, funds, managers and sectors against an investment thesis, with new evidence added to the same record instead of producing a new report each time.
A report is a snapshot. Continuous research keeps the view current and keeps every conclusion linked to its source.
AI can gather sources, extract claims and compare evidence. Investment professionals still set the thesis and judge what matters.
No. Use directory information as a starting point for research. Verify current information directly, assess suitability against your mandate and complete your own diligence before making an investment decision.
Living research is market, manager and company research that keeps updating as conditions change, instead of a report that ages the day it is published. Each finding stays tied to its evidence and to the deals it informs.
Reuben AI runs living research across 314 sub-asset classes in 68 asset classes. Investment teams use it to screen against their mandate; platforms embed it so their investor clients see current research on the funds and assets they hold.
How it works on one record: Reuben AI connects evidence across the asset or portfolio company, deal, vehicle, fund, manager, portfolio. A change in a manager's team updates the research record and flags the fund under review. The same fully sourced record carries context from discovery through diligence, committee decisions and ownership review. Judgement stays human. See the six levels of private markets diligence, the intelligence layer and Reuben AI for platforms.
Market, manager and company research that keeps updating as funds, managers and markets move, with each finding tied to its evidence.
A report is fixed at the date it was written. Living research is re-checked as new information appears, so decisions use the current view.