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Mentat

Features

Everything the protocol ships in the box.

Mentat is not a single product — it is a full stack: AI drafting, human curation, cryptographic settlement, and Solana-native economics, all MIT-licensed. Here is what each layer gives you.

AI authoring

A DSPy pipeline that drafts markets

Scout gathers context and sources, Draft writes the formal spec, Validator re-checks it against a rubric. The output is structured JSON — never free text — so it drops straight into the curator console and the on-chain schema.

  • Scout → Draft → Validator agents
  • Model-agnostic (OpenAI, Anthropic, local vLLM)
  • Structured JSON output
  • Policy filters pre- and post-generation

Human curation

A console that treats AI as a draft

Curators review every draft with a side-by-side diff, validation scores, bulk approve/reject, and full version history. Nothing reaches Solana without a human sign-off — the adversarial layer AI markets need.

  • Diff view + validation scores
  • Bulk approve / reject
  • Complete version history
  • Curator reputation + stipend

zkTLS settlement

Cryptographic resolution, no oracle

Outcomes resolve when a zero-knowledge TLS proof attests to a canonical source. The Solana MarketSettlement program verifies the proof and triggers payout — no jury vote, no optimistic dispute window for the routine case.

  • TLSNotary-style proofs
  • On-chain verification
  • Source allowlist per market
  • Bounty for the fastest valid proof

Solana economics

Fees that work for the long tail

MarketFactory and MarketSettlement are Anchor programs. Trades settle at sub-cent Solana fees with sub-second confirmation, which is what makes small, specialized markets economically viable at all.

  • Anchor programs
  • Sub-cent fees, sub-second confirms
  • Canonical market schema
  • Rust event indexer (rkyv + sled)

Full list

Feature by feature.

01

AI market drafting in ~15 seconds

A DSPy pipeline of Scout, Draft, and Validator agents turns a one-line idea into a full market specification — question text, resolution criteria, source allowlist, timestamps, and economics. Output is structured JSON ready for curation.

02

zkTLS settlement, no trusted arbiter

Outcomes resolve when a zero-knowledge TLS proof attests to a canonical data source — Reuters, CoinGecko, official APIs. The on-chain Solana program verifies the proof and triggers payout. No UMA jury, no optimistic dispute window for routine markets.

03

Curator console with diffs and bulk actions

Human curators stay in the loop with side-by-side diff view, bulk approve/reject, validation scores, and complete version history. The console treats AI output as a draft, not a verdict.

04

Solana-native economics

MarketFactory and MarketSettlement programs are written in Anchor. Trading happens at Solana fee tiers — sub-cent transactions, sub-second confirms — not Ethereum L1 prices that price out small bettors.

05

Canonical market schema

Every market — binary or multi-outcome — conforms to the same standard: question, resolution criteria, source list, trigger condition, fallback, invalidation clause, economic parameters, state machine. Indexers, UIs, and integrations all speak one format.

06

Permissionless and open source

The whole stack — Vue frontend, FastAPI backend, DSPy agents, Solana programs, Rust indexer, proof service — is MIT. Self-host the protocol; bring your own AI keys; settle on your own Solana cluster if you want.

07

Audit trail by default

Every AI prompt, curator decision, and proof submission is logged. The on-chain market account stores a BLAKE2 hash of the AI rationale, so anyone can verify the off-chain narrative against the on-chain bytes.

See it end to end.

These features connect into one flow: AI draft → human curate → zkTLS resolve → Solana settle.