CaseRecall
Persistent investigation memory
for onchain intelligence teams
Evidence-first. Human-gated. Persistent across cases.
Event
A public onchain event enters the system.
Actors
Participants are remembered across events.
Evidence
Facts, receipts, hashes, and negative findings persist.
Thread
The same investigation survives across time.
Reactivation
A later factual delta resurfaces the old case.
The demo question
Would persistent case memory improve a real investigator's workflow?
Problem
Investigations fragment. Memory disappears.
Context gets rebuilt across explorers, spreadsheets, screenshots, and whatever the investigator still remembers.
Without case memory
- Prior relationships get rediscovered by hand.
- Dead ends and negative findings vanish.
- Case context lives in scattered notes.
- Evidence and interpretation blur together.
One living thread
- Facts, receipts, and negatives stay on the same case.
- New events reactivate an old investigation.
- External context stays separate from chain evidence.
- Human decisions remain explicit and auditable.
The business question
Does this save a skilled investigator enough time, or surface enough missed context, to be worth paying for?
System
What the technology does
A bounded, human-gated workflow built to remember investigations over time.
Public chain event
Start from a wallet, token, transaction, or retained event.
Remember actors
Attach prior factual appearances to persistent memory.
Surface recurring structure
Find repeated actors, groups, relationships, and prior case overlap.
Human-gated deep investigation
Authorize bounded history, transfers, funding, creator links, exits.
Persist the package
Receipts, hashes, negatives, and unresolved questions stay on one thread.
Boundary. The machine surfaces facts and relationships. It does not infer intent, identity, ownership, or guilt.
The thread
What persists between cases
Investigation 003
PERSISTENT THREAD · REVISION 7
Recurring actor overlap
3 remembered participants reappeared in a new event. Prior thread reactivated on factual delta.
What persists is not a dashboard snapshot. It is the investigation itself, including everything it ruled out.
Epistemics
Three layers stay separate
The system is built to prove facts, not collapse evidence into accusation.
Onchain evidence
Transactions, signatures, balances, timing, memberships, receipts.
External context
Human-approved public sources, URLs, timestamps, exact query provenance.
Human interpretation
Judgment, hypotheses, conclusions, disposition, next action.
Explicit non-goals
- No automatic accusations
- No insider claims
- No ownership or control inference
- No trading recommendation
This separation is part of the product, not part of the presentation.
Validation
What is actually proven
Technical capability is validated. Commercial value is not.
Validated
- Persistent investigation threads
- Generic shallow + deep chain workflows
- Evidence packages with hashes and receipts
- Negative findings retained
- Human thread controls
- Factual-delta reactivation
- Blind testing on unseen real data
Unvalidated
- Will investigators pay?
- Does persistent memory save meaningful time?
- Does it surface relationships a skilled investigator would miss?
- Is the workflow differentiated enough from incumbent tools?
The next evidence should come from real investigators, not more engineering.
Live demo
Ten minutes, one real case
Show the workflow, not a feature tour.
Start from a public event
One real bounded case, chosen in advance.
Surface remembered actors
Show what the system already knew before this session.
Authorize the deep step
The gate is explicit. Scope is bounded and visible.
Show the evidence
Hashes, provenance, and what the investigation did not find.
Show reactivation
A later factual event returns the investigator to the same thread.
Demo rule. No trading claims. No accusations. No identity claims. Facts and provenance only.
Pilot
Who should see this
Only people who already investigate crypto cases.
Independent investigator
Repeated casework where actor and context memory matters.
Protocol or security analyst
Needs evidence-backed packages for incidents and suspicious flows.
Forensic consultant
Sells investigations; values reproducibility, provenance, auditability.
Risk or intelligence desk
Maintains memory across recurring actors, assets, creators, incidents.
The commercial test
Run it alongside their normal workflow on a real bounded case.
Feedback
What to ask afterward
The objective is evidence of pull, not compliments.
Their real workflow
- What would you normally do to investigate this?
- Where do you lose time or context?
- What would count as a useful result?
Against what they already use
- Did it save meaningful time?
- Did it surface a relationship or prior finding they would have missed?
- Did retained negatives prevent repeated dead-end work?
Success signal
They ask to use it on a second case.
If real investigators do not pull the product forward, keep it parked.