In errors, found in four-eyes review at Goldman Sachs by reconciling capital call and distribution notices against investor-level data before they went out.
Earlier.
What moved overnight and what it means for your positions, ready before the open.
For investment and finance teams
Less checking. More deciding.
Investment and finance teams spend their mornings reading, reconciling and re-checking. MESA reads the sources, checks your records against each other, and brings your team only what needs a decision. Every step is on record.
The day
Skilled people, spending the morning on checks.
As it is
- Analysts skim dozens of sources before the open.
- Statements are reconciled by hand, line by line.
- Notices and reports are checked twice, under time pressure.
- When a number changes, nobody can say why without digging.
With MESA
- A morning brief: the events that move your book, each tied to the positions it touches.
- Reconciliation overnight: only the exceptions reach a person.
- Checks before send: every notice set against your own data before someone signs it off.
- Every figure traced back to where it came from.
Why it pays
Where a finance team gains.
Not from a chat window: from the reading, checking and reconciling done before anyone arrives, so your people spend the day on judgement.
Signal
Errors
Stopped at the door.
Notices, statements and reports checked against your own data before anyone signs them off.
Close
Faster.
Reconciliations run overnight, and people work only the exceptions.
Audit
Ready by default.
Every check and every sign-off recorded, ready for a client, an auditor or a regulator.
Capacity
More volume, same team.
The routine grows with the work; your people stay on the decisions only they can make.
Research
Trusted, not hoped.
Strategies and signals tested to be proved wrong before money follows them.
First use cases
Pick one. It runs by Friday.
Research
The morning brief.
AI reads your sources overnight, pulls out the events that move prices, and ties each to the positions it touches, with how sure it is and what would prove it wrong.
Operations
Reconciliation, exceptions only.
Statements, ledgers and reports matched against each other. What agrees is logged; what does not goes to a person with the lines that disagree.
Controls
Checked before it goes out.
Capital calls, distributions and client reports checked against investor-level data before anyone signs them off.
Strategy
An edge, or luck?
Backtests taken apart with walk-forward and placebo tests, and checked for look-ahead bias, before money follows them.
Done before
From inside the industry.
A news pipeline: AI reads them, pulls out the events that move prices, and keeps market views, each scored for confidence and paired with a test that would prove it wrong.
Systematic research built to be falsified: a trading rule tested against 30 randomised alternatives, and a look-ahead bias found and removed before it misled anyone.
Who builds it
Built by someone who has done the checking.
Essa Paracha, founder · ex-Goldman Sachs
From 2024 to 2026 I was a Client Reporting Analyst in private markets at Goldman Sachs, sending same-day capital call and distribution notices to more than 10,000 investors in private-markets funds.
- Investor Health Check: a validation tool I built that cut processing cycle time by about 30%.
- Four-eyes review: as the Checker, I caught about $2.4M in errors by reconciling notices against investor-level data.
- Platform move: I ran about six months of user-acceptance testing for the firmwide move to a new notice platform; go-live came early.
That is the work MESA is built for: checks that have to be right, done every day, with a person signing off. Since Goldman I have built AI for trading and research, and I studied econometrics at Purdue.
Start
Give your team the morning back.
One use case, live on your own data, in five days, at a fixed price agreed before we start.