3CK โ€” a narrowing into estate & bequest administration

AI agents for bequest administration.

When someone leaves a gift in their will, the paperwork lands on a desk. Most of it takes an afternoon. Some of it takes years โ€” and you can't tell which until someone has read the file.

Try the demo โ€” no login required โ†“
Pre-revenue Pre-build Working prototype

What bequest administration actually is

Someone dies. They left money to a university. Now somebody has to sort it out.

1

Read the will

A 20 to 50 page document arrives. Somewhere inside is one paragraph naming the university โ€” how much, to which department, and what it must be spent on.

2

Work out what it means today

The will might be thirty years old. The department it names may have merged, been renamed, or closed. Someone has to work out what it is called now, and prove it.

3

Make sure the money arrives, and is spent as promised

Chase the executor for two years. Check what arrives against what was owed. Then keep the gift spent the way the donor wrote it, for as long as the fund exists.

All three are done by hand today, by people with too many files. We build the AI agents that do the reading, the matching and the watching โ€” and hand a human the evidence to decide on.

Built for institutions holding restricted gifts

Universities Hospital foundations Large charities Community foundations

The demo

A resolved restriction, with evidence, in under a minute.

Live, not a mock-up. A language model reads every document below โ€” every field scored, with the sentence it came from. Scans go to a vision model, and the result names the model that ran. Entity matching is deliberately not a model: a guess is not evidence.

Every gift, tracked from will to distribution

We never touch it. Probate does.

No custody, no fiduciary duty. We make sure the funds are handled correctly at two stages.

Stage 1

At administration

We verify the money actually arrives, on time and in full.

Stage 2

Across the endowment's life

Institutions evolve. Faculties merge, programs close. The original gift terms do not. We monitor their published changes against every gift agreement they hold, and protect the money two ways.

Forward

Catch mismatches before funds are misapplied โ€” a loss prevented.

Backward

Find funds already stranded, sometimes for decades, and redirect them to the closest active program the institution still runs โ€” cash unstuck. Nobody re-checks these. We do, across the whole corpus.

The institution that never loses a gift.

Post-death is where the field thins. Most software stops when the will is written. We watch what happens after โ€” so a gift naming a department from 1994 still finds its way, and a fund nobody has checked in twenty years gets found.

How it works

We surface and evidence. A human decides.

Three agents run today, live, on every document. More join the corpus as we build.

Identifies what kind of document just arrived โ€” a will, a codicil, an executor's accounting โ€” and routes it to the right case.

Extracts donor, executor, gift type, amount or share, named designation, restrictions and dates โ€” with a confidence score and the exact source sentence for every field, so nothing is a black box.

Asks one question โ€” does this restriction still work? โ€” matched against our historical entity map, with the archive evidence chain attached. A curated map, never a model guess.

Coming next โ€” roadmap, not yet built

Probate Agent

Watches probate registries and death notices, and matches them against the institution's own history โ€” including names it hasn't used in decades.

Watcher Agent

Reads the institution's published changes โ€” mergers, closures, renames โ€” and flags every instrument each one touches.

Dormancy Agent

Screens the standing endowment corpus for funds whose purpose no longer maps to anything the institution does.

Asset Verification Agent

Reads an executor's interim accounting and checks it against what actually arrives.

Time saved

Hours become minutes.

Today
With 3CK
Restricted gift 80โ€“90% of wills
8โ€“15 hr
Under 1 hr
Defunct entity or drifted purpose
40+ hr, sometimes years on a shelf
Minutes, with the proof trail
Capacity
~120 files/yr per officer. Past that, files don't get done slowly โ€” they don't get done
No ceiling. Agents run in parallel

One person does one file at a time, which is why files sit for months. Agents do not queue.

Money saved and made

And the numbers behind them.

The average bequest is $48,000. Today the hard ones go to a law firm on a 3% contingency โ€” $15,000 on a $500,000 estate, and again on the next one. We are flat: about $36,000 a year for a large university, however many estates come in. Two or three hard estates and we have paid for ourselves, before finding them anything.

Today
With 3CK
Hard estate, outsourced to counsel
3% contingency. $15,000 fee on a $500,000 estate
No fee. Inside the subscription
A bequest they were never told about
$0 recovered. 86% of bequest donors were never known to the institution
Recovered. $48,000 on average
Gift names an entity that no longer exists
Lapses to the family. $0 retained
100% retained. $48,000 on average
Endowment purpose drifts, and the Attorney General the regulator for endowments
Money repaid with interest, plus legal and remediation cost, then ongoing supervision
Nothing repaid. Flagged at the change, while it is still an internal correction
Where the 120 files a year comes from

Roughly 1,840 working hours a year against 8โ€“15 hours per restricted file is a hard ceiling of about 120โ€“230 files a year โ€” and that assumes an officer does nothing else.

How we charge

  • Annual subscription, tiered by instruments monitored โ€” restricted funds, endowments, and outstanding bequest intentions.
  • ~$9,000 small college. ~$36,000 large university. $120,000+ largest endowments.
  • Plus a fixed fee when we surface an estate the institution had no record of.

Team

Matthew

Legal researcher on wills and bequests, University of Sydney Advancement Services and Office of General Counsel. Founding engineer at Fluent Forever (0 โ†’ $2.5M ARR).

Phuong

UNSW Centre for Social Impact.