Verified result browser
479 navigation rows across two isolated ledgers, with method and trust metadata.
Browse verified resultsverification workspace for AI research
KeyAI keeps formal claims, evidence, decisions, negative results, verifier outcomes, and provenance in one inspectable state. The current reference deployment is ECDLP and curve research, not an ECDLP solution.
Reference deployment The repository demonstrates the full research-state loop on one difficult domain, but it is not yet a self-serve hosted product.
0 sorry · 0 custom axioms
104 rows disclose compiler trust in ledger metadata
0 native experiments selected
1 exact synthetic-toy run completed
AUTH-HYP-M16-FIXED-TARGET-YIELD-001-20260730-01
Evidence first
The public interface now exposes theorem names and exact source anchors before asking visitors to interpret the product thesis or the research workflow.
479 navigation rows across two isolated ledgers, with method and trust metadata.
Browse verified results17 canonical ECDLP routes with explicit dispositions, evidence, blockers, and reconsideration triggers.
Inspect the route mapCounts, architecture, and machine-readable provenance remain generated from repository sources rather than copied into marketing prose.
Open STATUS.md Read the architecture mapThe missing layer
Individual agents already write proofs and code. A long research program needs a durable answer to a different question: what should the next agent trust, challenge, or stop doing?
Bind each task to a source, exact scope, route, and falsifiable exit condition.
Record what the declared verifier accepted and what remains a semantic or empirical assumption.
Retain accepted results, negative evidence, stop conditions, and a reproducible rollback path.
Product loop
The current repository implements this loop through machine-readable contracts. The next product step is to make the same loop configurable for an external team.
Pin the corpus, sources, target, and verifier contract.
Convert material into claims, dependencies, barriers, and threat models.
Select, park, or reject routes under explicit evidence gates.
Give a human or model one bounded task with a falsifiable exit condition.
Run the declared verifier and an independent result validator where needed.
Promote accepted results and preserve negative evidence, provenance, and rollback.
Active validation / TASK-011
We are recruiting one formal-research team to test the current workspace, map one repeated workflow, and make an evidence-based build, change, stop, or pending decision.
Reference deployment
secp256k1 is the test case, not the product claim. It forces KeyAI to distinguish a theorem, an experiment, a threat model, a failed route, and a practical attack.
RS-2026-07-24-001 · 2026-07-24
Completed the bounded, non-experimental GLV-SEMAEV-ITER-001. Only the diagonal C3 scalar polynomial covariance survives for S3 and S4; the naive independent-cube premise and the S4 fixed-target coordinate-scaling premise are bounded negatives. The S4 certificate isolates r=0, and Lean proves that no F_p-rational affine secp256k1 target inhabits that slice. No route or hypothesis is promoted, no solver run is authorized, and the primary ECDLP objective remains unchanged.
What exists now
Each capability below links to a live artifact in the reference repository.
Inspectable in the reference repository and checked by the repository gates.
VERIFIED.mdInspectable in the reference repository and checked by the repository gates.
repo/ECDLP_DECISION_SUBSTRATE.jsonInspectable in the reference repository and checked by the repository gates.
experiments/framework/candidate_run.schema.jsonInspectable in the reference repository and checked by the repository gates.
tasks/NEXT.mdCurrent capability
Not yet
The next product milestone
A non-owner research team can connect a second project, obtain a trustworthy initial map, run one candidate through its verifier, and understand the resulting decision without editing KeyAI's generator code. A technical MVP still does not establish a repeatable buyer or willingness to pay.
A new collaborator identifies current state, blockers, and next action in 10 minutes or less.
Every promoted result links to its source, task, verifier result, and trust boundary.
Zero stale generated or public artifacts after a canonical state change.
At least one external team completes the core loop and returns for a second session.