factbond

Bonded assertions and information insurance for factual claims — a mechanism design for attaching economic guarantees ("someone will pay if this is wrong") to millions of ordinary facts: opening hours, database entries, knowledge-graph edges.

Status: design stage, first code 2026-09-19. The design documents are the substance; the first code is the assertion primitive's consumer-facing edge — contracts/Assertions.sol (assert with a bond at a stated confidence, dispute at the odds it sets, certify by timeout, rule only when contested, escalate when no ruling comes; a consumer contract told hold(subject) and resolve(subject, outcome)), factbond.assertions, and tests on a local EVM — built for loopmarket's escrow, whose contested claims it adjudicates (docs/plans/loopmarket-coupling.md §3b; the cross-repo gate is loopmarket's tests/test_escrow.py). The simulation (docs/DESIGN.md §10) still gates the insurance product. CLAUDE.md maps what is built to the plans.

The idea in one paragraph

Prediction markets cannot scale down to millions of mundane, near-certainly- true statements: every bet needs a matched counterparty, full-notional collateral locked for the claim's lifetime (the "99-cent problem"), and a mandatory settlement even when nobody ever disagreed. The right primitive for that regime is the bonded assertion (the optimistic-oracle pattern): one party posts a claim backed by a bond sized to the cost of adjudication, not the value at stake; the whole world is the latent counterparty during a challenge window; undisputed claims certify by timeout for free; and the expensive machinery — evidence, adjudication, real price discovery — spins up only on the ~1% of claims where someone actually disagrees, which is exactly where the information value lives. On top of that sits the consumer product, information insurance: the person (or AI agent) about to act on a fact buys a cheap hedge against it being wrong — which couples verification demand to consumption, pays exactly the right person to discover each error, and makes the pool's quoted premium a market-priced reliability signal for every fact, without anyone betting on most of them.

Documentation

• docs/DESIGN.md — the design: why markets fail at this scale, the bonded-assertion primitive, odds-weighted bonds, the insurance coupling, the five-layer architecture, the claim lifecycle, capital pools, build order, and the two hardest open problems.
• docs/INTEGRATION.md — how factbond composes with the sister stack: ontodag as the claim layer and netting fragment, recordstore/Swarm for evidence and proofs, and loopmarket as the first structured consumer (its P3 "guarantee fabric" is this design).
• docs/prediction-markets-transcript.pdf — the founding discussion (Peter Földiák with Claude, 2026; also at https://claude.ai/share/2d3c2fe8-adfc-4c01-8f36-ff3ab29baf6d), from which DESIGN.md is distilled. Where the two disagree, the transcript is the record of the discussion and DESIGN.md is the current position.

Origin

The starting ideas (bets on facts rather than future events; capital efficiency; batching; bets embedded in a knowledge graph) are Peter Földiák's, developed in discussion with Daniel A. Nagy — whose observation about capital lock-up on near-certain claims (the 99-cent problem) shapes much of the design — and, following the ETHPrague 2026 prediction-markets workshop, with Krzysztof Paruch (Token Engineering Labs) and Mark B Richardson (Bancor). The synthesis and the architecture sketch come from the transcript above.

Honest scope

Even a perfect version of this system does not certify truth. It certifies "nobody found it profitable to dispute this, under a specific adjudication procedure, at current bond and subsidy levels" — which is genuinely more than most databases offer today, and the design documents are careful to keep the distinction explicit throughout.