saascode
web3 & on-chain infrastructure·run 034 · Apr 2026

Mempactor

A token-unlock scenario API that versions vesting evidence, liquidity and holder assumptions, calibrates impact ranges, and supports reviewer-owned reserve decisions.

Genesis score7.59/10
Make Mempactor real.0/500
500 more votes and Mempactor is authorized for build.
0%500 to authorize
Backing is the vote. When an idea crosses 500, we pull it into the build pipeline and ship it for real — the votes decide what gets built next, not an editor.
The opportunity
500/moFree API calls
$99–$799/moObserved paid range
3/4Verified interfaces
The case

Unlock calendars tell an allocator when supply may arrive, but not how a particular portfolio, treasury, venue mix, or risk limit responds. Existing tools track schedules and some estimate historical impact. The opening is a fund-context scenario layer that preserves source uncertainty and backtested ranges, while keeping hedge and reserve actions with investment professionals rather than emitting automatic recommendations.

Who pays — and why

The digital-asset fund manager, treasury risk lead, market maker, or research team managing exposure to scheduled token supply changes.

Market signal$99–$799 monthlyobserved Token Metrics market reference, set your own
What it unlocks
A versioned unlock calendar with source, token, beneficiary cohort, amount, and uncertainty
Liquidity- and portfolio-aware impact scenarios with intervals and comparable historical events
Reviewer-approved watch, rebalance, hedge, or no-action records without automated trading
How Genesis scored it
7.59across seven criteria
tension 7temporal 9blindspot 6buyer 7leverage 9convergence 5why-not 8
9
Temporal window

Large ongoing unlock volumes and a current institutional analytics market create urgency.

9
Asymmetric leverage

Schedules, event studies, alerts, and APIs scale through software.

5
Convergence

A few links support the concept, while grounded convergence remains modest.

Why it scored well

Real unlock data products, a specific institutional context gap, and a compounding observed-event calibration corpus support a leveraged data product.

What's holding it back

The buyer remains broad, one interface is unverified, causal price impact is difficult, competitors estimate supply impact, and recommendations create regulated risk.

Signals detected5 sources crossed
Signaldevelopers.tokenmetrics.com

Signaltoken.unlocks.app and tokenomist.ai

Signalsmartmoneyapi.com research

Signalcompetitor scan carried in Genesis

SignalGenesis capability review

Direction briefmempactor.md
mempactor.md
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