CAIN-42 MCPGateAGENTIC AI 75 · #5
Open-world multi-agent mathematical discovery
The Station study let agents independently choose research directions, experiment, collaborate and build on one another's findings.
Last reviewed 2026-11-11
Agentic AI 75 / #5
2026 status: Research preprint · Category: Mathematical research
The 2026 development
The Station study let agents independently choose research directions, experiment, collaborate and build on one another's findings.
The governance gap
Independent agents building on each other's results create a provenance problem: which lemma came from whom, which proof was checked, and which claim was only asserted. Collaboration without attribution turns errors into foundations.
Where CAIN-42 fits: Moat 3 — Trust Graph
Core question: How is everything connected? Entities, resources, delegations and effects as a graph that can be traversed and audited.
Represent the research programme as a trust graph of claims, proofs, agents and dependencies. Each edge records whether the dependency was verified, and a downstream result cannot inherit more confidence than its weakest checked input.
How the wiring works
- Register each claim and proof as a node with author, checker and status.
- Record every dependency edge when one result is used by another.
- Refuse to promote a result whose checked dependencies are incomplete.
- Export the graph with the paper so a reviewer can walk the derivation.
What is real today
LIBRARY Production code and tests exist in this repository; there is no hosted route for this exact use.
The graph and certificate code is real and tested. The specific multi-agent mathematics workflow is a mapping, not a deployed research system.
| Component in this repository | What the module says it is |
|---|---|
cain/causality/graph.py | CAIN CAUSALITY — Causal Event Graph (Prompt CAUSALITY, Phase 3). |
cain/causality/certificate.py | CAIN CAUSALITY — Causal Accountability Certificate (Prompt CAUSALITY, Phase 12). |
cain/runtime/swarm.py | CAIN Sovereign — Adversarial Agent Swarm (Prompt 7, Phase 29). |
keystone/ledger.py | Durable, tenant-scoped, rotating ledger for KEYSTONE records (L-09). |
Descriptions are the first line of each module's own docstring, read without importing it. A module path is a pointer into this repository, not a hosted endpoint. Its existence is checked by the test suite; its status for this use is the label above.
Check it yourself
- Run the live swarm delegation demo
/swarm-keystone - Fire a live decision through the CAIN-42 pipeline
/fabric/try— the same enforcement path every product sits behind.
Commercial package
| Offer | Research Provenance Review |
|---|---|
| Buyer | AI research labs and academic consortia |
| Price (proposal) | $3,500–$7,500 per review |
| Bundle | Swarm & Multi-Agent — Delegation you can follow across every hop. |
| Operator stream | Stream 2 of the 10-stream operator playbook |
Agent orchestrator vendors, research labs, enterprise platform teams is the bundle buyer. The entry offer for this bundle is Swarm delegation audit; collusion and drift review; the range is $3,500–$7,500 per audit; $2,500–$4,000/month retainer. A price on this page is a proposal, not a validated rate, and no customer is claimed.
Buy this as a product or service
CAIN-A75-005 — Research Provenance Review DELIVERABLE
A bounded engine run on the buyer's sample: findings, a written report, and a SHA-256 artifact manifest. The manifest is unsigned: it is not a signature and not an attestation.
Kind: Assessment · Price (proposal): $3,500–$7,500 per review · Lead time: 5 business days.
Open the product page · all 75 products
What this page does not claim
What this page is not. CAIN-42 is not affiliated with, endorsed by, integrated into, or shipped with the organisation named in the 2026 item. The item is public context; the page describes how CAIN-42 would govern that class of capability. No page here claims a customer, a partnership, a certification, a patent, or a production integration. Prices are proposals. Built by a three-person team.