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Evidence Infrastructure for Data Resources

From analysis reports to
reusable, tradable knowledge units

Turning life-science data resources into evidence-based, tokenized data assets.

World Model — not just a database or knowledge graph, but a continuous knowledge structure that understands the inner logic of life-science data. It constrains every LLM inference under verifiable rules, attaching an evidence chain to each conclusion, moving from black-box output to auditable evidence.
90%+
industry cost down
compute once, cards reused forever
Second-level
evidence audit
trace every conclusion to data & path
¥1.2
verify a proposition
small to verify, right to dig deep
Value

What we do that traditional analysis cannot

Verifiable

Every conclusion carries a full evidence chain — traceable and auditable.

Cumulative

Analyze once, reuse forever — more valuable with every use.

Controllable

From ¥1.2 verification to deep synthesis — pay as you go.

Adjustable

Quick check to deep synthesis, adjusted to your need.

Compare

Not cheaper — freer

Spend a little to validate a hypothesis; spend right to dig into a proposition.

CoreCraft LabsTraditional bioinformatics
BillingOn demand, from about ¥1.2 per run (~US$0.17)Packaged per project, prepay tens of thousands
DepthDeep or shallow: quick check → deep synthesisFixed package, depth locked
TargetingAround your proposition, dig preciselyStandard pipeline; questions bend to it
IterationFollow up, keep digging, traceableNew request → re-queue, re-pay
Granularityabout ¥1.2 to verify a proposition, or from ¥9.9 for 8 deep analysesStarts at tens of thousands; no small-scale trial
KnowledgeAuto-archived, ever deeper, ever more valuableOne-off; start from zero next time
Redundant computeCompute once, cards reused forever, cutting industry-wide cost by 90%+Same question, repeated compute across teams
Capabilities

A research partner that grows on its own

From data to knowledge, from analysis to trade — every step built for research efficiency.

01

Private World Model

Upload data to build a living map that understands its inner logic — ask directly about any pathway, subpopulation, or gene.

From data files to an interactive knowledge system
02

Auto Proposition

The world model actively scans its knowledge structure to surface propositions worth digging — no need to wonder where to start.

From finding propositions to propositions finding you
03

Evidence Distillation

Every conclusion is traceable; deep digging rests on trustworthy evidence with three checks: traceable data, verifiable reasoning, quantifiable conclusion.

From black-box output to auditable evidence
04

Public World Model

With compute, dig into open propositions in public world models without providing your own data.

From data-required to idea-verified
05

Knowledge Trading

Knowledge cards from your digging can be monetized and reused, building your knowledge assets.

From reports to tradable knowledge units
06

Transparent Billing

See exactly where every unit of compute went — transparent, budget under control.

From packaged fees to transparent billing
Knowledge Cards

Knowledge cards = verifiable knowledge asset units

Not just a paragraph — a self-contained evidence unit.

Evidence chain

trace to data & reasoning path

Structured

searchable, comparable, composable

Reusable

generate once, reuse forever

Tradable

monetize insight, build on others

Three Proposition Modes

Three drivers that keep the knowledge system growing

User propositions → accumulate knowledge → auto propositions → more bounties → more explorers.

User Proposition

Dig precisely around your proposition

Researchers / data owners

  1. 1Upload data to build a private world model
  2. 2The deep-analysis engine digs into your proposition
  3. 3Traceable conclusions distilled into knowledge cards
Auto Proposition

The world model surfaces what is worth digging

All users

  1. 1Auto-scan for high-value propositions
  2. 2Autonomously run analysis and distill evidence
  3. 3Cards accumulate and grow in value
Bounty Proposition

System or commissioned bounties, explorers compete

System-published or externally commissioned

  1. 1Post paid propositions with escrowed reward
  2. 2Explorers compete with independent analyses
  3. 3Sponsor picks a winner — 80% reward, cards stay listable
Explore & Trade

Produce tradable knowledge with compute

1

Get a key

Plaintext returned once; only the sha256 hash is stored.

2

Open or choose

Owners can open their model; explorers pick an open proposition.

3

Launch exploration

Drive deep analysis with a self-hosted LLM or system compute.

4

Produce and trade

Title, summary, and evidence chain — list it and resell it.

Knowledge value belongs to its creators

60%
20%
20%
Explorer (producer)60%
Data owner (contributor)20%
Platform (infrastructure)20%

Every dig builds monetizable knowledge assets for you.

Use Cases

Who uses CoreCraft Labs?

Basic Research

Academia

Quickly find directions from omics data, validate hypotheses, accelerate publication.

Clinical Research

Clinicians

Extract verifiable knowledge from clinical data to support decisions.

Drug Discovery

Early R&D

Target validation, pathway analysis, screening — lower trial cost.

Bioinformatics

Bioinformaticians

No more repeated analysis — compute once, focus on insight.

Free Knowledge

Knowledge cards, free to use

Publicly available knowledge cards are free — enter the Knowledge Center to mine reusable knowledge; for deeper insight, ask for synthesis or unlock paid cards.

Hold data, build your private world model;
have compute, produce the next knowledge card

Start from a specific proposition at about ¥1.2 (~US$0.17) and validate your first hypothesis; every unit of compute is transparently billed and auditable.