Ranked summits
Every candidate has a crux, expected value, acceptance gate, dependencies, and non-claims.
Cheap-first invention operations
Create more validated invention per dollar.
A SaaS machine that turns a thesis, transcript, repo, or market question into ranked summits, cheap prep lanes, falsifiers, proof gates, and academic-ready packets before expensive model burn.
1,000summit candidates
6,000swarm task surfaces
10Opus candidates after cheap proof
$0.035visible planning cap
99.94%cap cut from first envelope
700new rows from prior inventions
The loop
1
Ideate broadly
Generate summits from prior inventions, markets, code, and research.
Generate summits from prior inventions, markets, code, and research.
2
Cut cheap
Use source, repo, and falsifier lanes before premium models see context.
Use source, repo, and falsifier lanes before premium models see context.
3
Promote narrowly
Only rows with evidence become frontier-model gate packets.
Only rows with evidence become frontier-model gate packets.
4
Distribute proof
Export buyer memos, methods packets, and academic review artifacts.
Export buyer memos, methods packets, and academic review artifacts.
Not a prompt wrapper. An invention operating system.
The machine creates a queue that can be attacked by cheap workers, strong coders, researchers, and frontier models without losing claim discipline.
Cost governor
Premium model burn is blocked until cheap lanes produce anchors, falsifiers, or a proof boundary.
Compounding graph
New inventions cite the prior inventions they reuse, so the pipeline gets smarter as it runs.
Business value in plain English.
Teams waste frontier models on fog. CIM turns fog into a small, testable climb.
- Lower premium-model waste: cheap lanes do context compression, source checks, and falsification first.
- Better strategic focus: the queue scores work by proof value, buyer value, research value, and cost reduction per dollar.
- Cleaner diligence: outputs become proof packets with commands, assumptions, and explicit non-claims.
- Faster R&D translation: prior invention, product work, and founder context become reusable structured inputs.
Private beta
$30/month + token costsOne private invention queue, summit generation, exports, usage transparency, and a clear record of what was promoted to stronger models.
Request accessTeams and labs
Studio and enterprise
Shared queues, private proof ledgers, SSO, review workflows, hosted packets, and strategic licensing for model platforms, clouds, labs, and developer tools.
Datamorphic Biography
The system began as a living biography of a builder turning transcripts, code, books, costs, failures, and research into structured invention data.
Biography becomes data
Unstructured founder context is mapped into claims, constraints, signals, and reusable invention memory.
Data becomes a machine
The machine ranks what to try next, what would kill it, and what proof a buyer or researcher can inspect.
Proof becomes distribution
Only solved or bounded artifacts move outward to customers, acquirers, or academia.
Bounded claims. Real ambition.
The trillion-dollar language is a research ambition and allocation function, not a current valuation, revenue claim, or investment promise.
No valuation claim
The site describes a product and method, not a current valuation.
No academic validation claim
Academic packets are prepared for review; acceptance is not claimed.
No autonomous money claim
Agentic-money artifacts stay bounded by named gates and non-claims.