Pick
Choose a firm and a desk, press Run.
Find
Four sources searched at once.
Screen
AI judges fit and ranks seniority.
Verify
Evidenced emails, free phone check.
Review
✓ or ✗ with a reason, logged.
Reach out
Phones on request, status tracked.
Case study · Private Credit
The full picture of a target firm, in seven minutes.
A Kuala Lumpur private credit firm needed to work specific desks inside banks, law firms and advisers for a new fund. We built a company intelligence tool that maps each firm: the people on each desk, ranked by seniority with evidenced emails, plus what the firm has done lately and who it’s hiring.
193
Qualified desk contacts
94
Evidenced emails
0
Guessed emails
~7 min
Per firm
Current run
run → Bank · Non-bank lending desk
activity → 5 deals in 90 days · sources linked
screened → Yes · Director · reason logged
email → Verified · firm website
flagged → LinkedIn only · needs review
Executive summary
The 30-second version
To source deals for a new fund, a Kuala Lumpur private equity and private credit firm needed the people on specific desks inside 63 target firms, not just who works there. Finding them by hand meant LinkedIn trawling, guessed emails and lists that went stale. We built a company intelligence tool that maps a firm and desk in about 7 minutes, alongside the firm’s latest deals and open roles, at about US$0.05 per qualified contact, with zero guessed emails. It was in daily use five weeks after the brief.
Challenge
Desk-level, by hand
A big bank has tens of thousands of staff. The desk the fund needed was a handful, with vague titles and no public emails.
Solution
Company intelligence tool
Pick a firm and a desk, press Run. Each person is screened against the team’s brief and ranked by seniority, next to the firm’s latest deals and open roles.
Key results
~7 min a firm
193 qualified desk contacts from the first 7 runs, at about US$0.05 each, with every email backed by a source.
Outcome
>90% coverage
Based on public data, the tool finds more than 90% of the people on each target desk, alongside each firm’s latest deals and open roles.
Client overview
Who we built this for
The firm and its fund aren’t named. The profile below reflects the real engagement.
IndustryPrivate equity & private credit
Business typeKuala Lumpur investment firm
Team involvedDeal sourcing
Why nowSourcing deals for a new fund
Target list63 firms · 24 desks · 136 targets
MarketMalaysia only
Existing toolsLinkedIn, spreadsheets, Google Sheets
Project scopeCustom AI company intelligence tool
TimelineBrief to v3 in five weeks
StatusLive, in daily use
The business challenge
“Who works at this bank?” is easy. “Who sits on this desk?” isn’t.
A new fund meant a new target list: bankers who lend to non-bank lenders, lawyers in banking and Islamic finance practices, deal teams at advisory firms. That came to 136 firm-and-desk targets across banks, law firms, advisers, investors and industry bodies.
Desk-level, not company-level
Malaysia’s largest bank has tens of thousands of people on LinkedIn. The desk that lends to non-bank lenders is a handful of them.
Titles say almost nothing
“Director” or “Vice President” doesn’t tell you which desk someone sits on, so every profile had to be read and judged.
LinkedIn goes stale
People move on and keep the old employer on their profile, so a list could be wrong before it was finished.
Emails aren’t public
Guessed addresses bounce, and every bounce eats into the sender reputation the fund needs for real outreach.
The wrong senior people
Investor relations and client coverage roles look senior, but they aren’t the people an investing desk needs to reach.
Regional teams leak in
Firms list regional staff on the same pages. The fund only wanted people working in Malaysia.
Before · the manual workflow
Six manual steps for every firm and desk
This is how firms like this one usually build a target list: an analyst, firm by firm, starting again whenever the list goes stale.
Search
Trawl LinkedIn firm by firm, reading profile after profile.
Guess
Infer which desk someone sits on from a vague job title.
Email
Guess the address from a pattern, or buy it unverified.
Record
Paste it into a personal spreadsheet, with no record of why.
Research
Google each firm’s recent deals and hires, if there’s time.
Redo
Start again from scratch when the list goes stale.
Objectives
What success needed to look like
The goal wasn’t more names. It was a shorter list the team could trust and act on.
Desk-level targeting
Judge each person against the desk brief the team wrote, not against a keyword list.
Target: a written reason for every verdict
No guessed emails
Keep an address only if a source can back it up, and show how sure it is.
Target: zero pattern guesses
Decision-makers first
Rank every list by seniority so the people who can say yes come first.
Target: a seniority level on every person
Pay only for fit
Spend enrichment money only on people who belong on the desk.
Target: cents per qualified contact
Read each firm’s direction
See what each firm has just done and what it’s hiring for, so the team brings the right deal at the right time.
Target: deals, hires and open roles on every firm
The team keeps the judgement
Every person gets a human ✓ or ✗, and every review is kept.
Target: a permanent review log
Solution overview
A company intelligence tool, not another contact database
The firm first looked at building a full investor database from scratch and dropped it as too ambitious. What the team actually needed was narrower and harder to get: the people on this desk, at this firm, with an email they can trust.
Contact databases answer “who works at this company”, and generic AI scrapers guess. So we built a company intelligence tool where the team picks a firm and a desk and presses Run. About seven minutes later it has the people on that desk, screened against the team’s own brief and ranked by seniority. Each person has a work email only where a source can back it up, and a phone number one click away.
The firm’s Google Sheet stays the system of record. Every run uses the firm’s own data-provider accounts, so it sees every cent and owns the data.
How it works
From a target list to the full picture of every firm
The team works from the target list they already wrote. The automation finds, screens and enriches the people. The team reviews the result and decides who to approach.
01The target listIn the team’s own words
Sections, desks, firmsThe target list, exactly as the team wrote it
Desk briefWho they want on each desk, and why
Add a companyType one firm and get its suggested desks in about 20 s
Similar firmsSuggested for each desk, each with a verified LinkedIn page
02Automation layerAI + workflow
FindLinkedIn, ContactOut, Hunter and the firm’s own website, searched together
CleanDuplicates merged, people outside Malaysia dropped
Screen & rankYes / Maybe / No against the desk brief, plus one of six seniority levels
Verify & enrichEvidenced emails, cheapest trustworthy source first, plus a free phone check
Recent activityDeals, funds, hires and open roles from the last 90 days
Monitoring & spendHourly status checks, failure alerts, cost per run and feature
03The team’s workspaceDashboard + Google Sheet
Company pages
Results table & CSV export
Reviews & outreach status
Spend & provider balances
Google Sheet (system of record)
04Outcomes
About 7 minutes per firmUnattended; firms queue one after another
About US$0.05 per contactPer qualified contact, on the firm’s own accounts
Zero guessed emailsEvery address labelled by its evidence
Decision-makers firstEvery list ranked by seniority
A full audit trailEvery AI verdict and human review kept
Timing signalsWho just led a deal, raised a fund or hired
End result
The team stops researching and starts reviewing. Every decision, whether the AI’s or a person’s, is on the record.
After · the automated workflow
The same desk, in about seven minutes
The tool does the finding, screening and checking. People decide who is right for the desk and who to approach.
Pick
Choose a firm and a desk from the target list and press Run.
Find
LinkedIn, two contact providers and the firm’s website are searched at once.
Screen
AI judges each person against the desk brief and ranks by seniority.
Verify
Emails kept only with evidence; a free check for a direct phone line.
Review
The team marks each person ✓ or ✗ with a reason, and it’s logged.
Reach out
Phone numbers revealed on request; outreach status tracked per person.
Company intelligence
Where a firm is heading decides which deal to bring it
A list of names only tells you who to call. A private credit firm bringing a deal to a bank, law firm or adviser needs to know where that firm is moving: what it has just done, which desks it’s building, and what it has the capacity for. That direction is one of the strongest signals there is for which deal to bring, to whom, and when.
Recent deals
What they’re doing now
A bank that has just led a syndicated financing has a live team and an appetite for that kind of deal. That’s the moment to bring a similar one.
Job openings
Where they’re going next
A firm hiring into leveraged finance or Islamic banking is building that desk, and it will need deal flow to keep the new team busy.
Senior hires
Who decides now
A new head of a desk often arrives with a new mandate and wants early wins. That makes them one of the most open doors in the firm.
Funds & expansion
What they can take on
A new fund, financing programme or office means fresh capacity, and often a market the firm is actively trying to grow in.
For the client
The difference between sending a deal and sending the right deal: what the team brings now matches where each firm is already heading.
How it shows up
Every firm’s direction, on one page
Every firm gets its own page. Next to the people on each desk, it shows what the firm has been doing lately, read from its own LinkedIn posts and the news.
Recent activityDeals, funds raised, senior hires and expansion from the last 90 days, each linked to its source.
Open rolesWhat the firm is hiring for right now: an early sign of which desks are growing.
Company libraryEvery firm with its industry, size, latest deal or hire, and how many of its people are reachable. Sort by newest activity to see who is busy this week.
11
events surfaced on one bank’s page in 90 days, 5 of them deals, for about 10 US cents.
Commercial bank
Banking · Kuala Lumpur · 3 desks tracked
Recent activity 11 in 90 days
DealLead arranger on a syndicated Islamic financingNews · 6 d
DealTerm facility for a non-bank lenderLinkedIn · 3 wk
HireNew head of leveraged financeLinkedIn · 5 wk
FundAnchor investor in a new sukuk programmeNews · 7 wk
Open roles 3 open
Vice President, Financial Institutions Kuala Lumpur
Associate, Leveraged & Acquisition Finance Kuala Lumpur
Manager, Islamic Corporate Banking Kuala Lumpur
Illustrative view. Firm and event details are anonymised.
Solution breakdown
What makes it different
Finding names is the easy part. These are the parts that make the list worth acting on.
Judged against the team’s own brief
The AI reads each person’s current role against the desk brief the team wrote in their own words, and returns Yes, Maybe or No with a written reason.
No guessed emails, ever
An address is kept only if a source can back it up, and it’s labelled Verified, Found or Likely. We tested pattern guessing and rejected it. With no evidence, the field stays blank.
The firm’s own website beats LinkedIn
When a firm publishes its team, that page outranks what people say on LinkedIn. Anyone found only on LinkedIn is labelled “LinkedIn only” so the team knows to check.
Rules for investing desks
Investor relations and client coverage roles are kept off investing desks, regional staff are filtered out, and the most senior people always stay on the list.
Phones only when you’ll call
Every run checks for free whether a direct number exists. The team pays US$0.20 only for the numbers they choose to reveal.
Decision-makers first
Every person carries one of six seniority levels, from board and C-suite down to support. Lists put decision-makers at the top, and paid enrichment goes to them first.
Implementation
From brief to daily use in five weeks
Three versions, each shaped by the client testing the one before it on their real target list.
Early Sep · Brief
Scope & first tests
Narrowed the brief from a full investor database to desk-level contacts. Early tests showed searches were missing most of each firm. Better queries took one test from 1 profile found to 13.
10 Sep · v1
First version
A Google Sheet-driven tool with one source and evidenced emails, handed to the team to try on real targets.
15–22 Sep · v2
Multi-source engine
Four sources searched together, an AI screen built on the team’s desk brief, emails paid for only when a person fits, and a live dashboard. Moved onto the client’s own accounts.
5–7 Oct · v3
A tool the team works in
Company pages, seniority ranking, rules for investing desks, ✓ / ✗ reviews with a permanent log, similar firms, open roles, phones on request and spend by feature.
Technology stack
Sources first, AI second
The AI only judges data it was given. It never invents a person or an address.
n8n
About 15 workflows on our self-hosted server covering runs, sourcing, emails, phones, activity and spend.
OpenAI
Screens and ranks people, and pulls deals and hires out of posts and news.
LinkedIn data
Profiles, company pages and posts, collected through Apify.
ContactOut, Hunter & Apollo
Email and phone providers, tried cheapest trustworthy source first.
Firm websites
Team pages read directly: the strongest signal of who actually works there.
Web dashboard
A login-protected workspace for desks, companies, results and spend.
Google Sheets
The client’s system of record. Every result lands there too.
Telegram
Alerts the moment a run fails, plus an hourly check that every service is up.
Key takeaways
Why it matters
~7 min a firm
Desk-by-desk LinkedIn research became a run that finishes in about seven minutes, unattended. The team’s time now goes into reviewing people, not finding them.
0 guessed
Every email is backed by a source and labelled by how sure it is. For a fund doing real outreach, a blank field is better than a bounce.
Direction first
Recent deals and open roles show where each firm is heading. The team brings deals that fit what a firm already wants to do next, instead of cold-pitching a name on a list.
Explore
The solutions behind this build
The same building blocks can be put together for your own target lists and research.
Sales & Marketing Automation
Target lists, enrichment and outreach tracking that keep pace with your pipeline.
Learn more →Data & Analytics Automation
Live dashboards for runs, coverage and spend, updated as the work happens.
Learn more →Custom API Integrations
LinkedIn data, contact providers, AI and Google Sheets connected into one system.
Learn more →Explore all solutions
See the full range of AI automation we build across sourcing, operations and data.
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