Recall Network

Recall Network — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

Recall Network — an AI/Agents | Infra project: a “decentralized skill market for AI”, where AI agents/models compete in arenas, and users stake/“boost” participants and receive rewards. Token: RECALL (ERC‑20 on Base).

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

What it is: a platform of competitions/rankings where participants “stake” tokens on the best performers and receive rewards based on competition results.
Who it’s for: curator users (predict the winners), developers (run agents in competitions), communities (fund skill markets).
Why onchain/token: the RECALL token is needed for staking/boosting, reward payouts and the settlement “stake” that makes results verifiable and economically meaningful.
What you can actually touch (Tier‑1): the web app https://app.recall.network/stake and the “Paper trading API guide” https://docs.recall.network/competitions/build-agent/trading.

How it works (very briefly)

The user does: stakes RECALL and allocates Boost to agents/models (curation/voting).
The system does: runs competitions (arenas/competitions), updates the ranking based on verifiable results and records the distribution of rewards.
The user gets: rewards in RECALL if the selected participants show a higher result in the competition.
Where the blockchain is: the token and the staking/reward distribution contracts are deployed on the Base network (addresses are listed in the docs).
Token role: participation/access to the mechanics (stake → Boost), incentives and security (stake/rewards/onchain settlement).

Quick links: AI thesis fit

Project passport

Field	Value
Project name	Recall Network
Also known as (aliases)	Recall; RECALL
Logo (logo)	../assets/76_recall-network_logo.jpg
Token symbol (ticker)	RECALL
Category	AI/Agents \| Infra
Primary chain (chain)	Base
Type	EVM
Network status	mainnet
Consensus (consensus)	L2 (Optimistic Rollup, Base on Ethereum)
Launch date (launch_date)	2025-10-15
Project status (status)	active
Token (standard)	ERC-20
Token contract	0x1f16e03C1a5908818F47f6EE7bB16690b40D0671
Token model (token_type)	utility (payments + staking + governance)
Max supply	1,000,000,000
Issuance	fixed
Tokenomics (tokenomics, brief)	distribution: 10% airdrop; 10% foundation; 30% community; 21% contributors; 29% investors
Governance	company
Admins/keys	multisig
Audit	yes
Bug bounty	—
Team (team)	Recall Labs / Recall Foundation
Funding (investors/funding)	$40M raised (USV, CoinFund, Multicoin Capital, Consensys)
AI component (ai_component)	decentralized skill markets for AI (competitions + rankings)
Use‑case (use_case)	AI agent competitions + staking-based rankings
DecAI Fit — AI thesis fit	5/6 — high alignment with the Decentralized AI thesis
DecAI Fit component summary	ai_score 3 / onchain_score 3 / token_score 1 / evidence_score 3
Last verified	2026-02-11

Links (links_*)

Type	Link
Website	https://recall.network/
Docs	https://docs.recall.network/
GitHub	https://github.com/recallnet/
Releases / Changelog	https://recall.network/changelog
Whitepaper	—
Roadmap	—
Security advisories	https://github.com/recallnet/contracts/security/advisories
Explorer	https://basescan.org/token/0x1f16e03C1a5908818F47f6EE7bB16690b40D0671
App / Demo	https://app.recall.network/stake
X	https://twitter.com/recallnet
Discord	https://discord.com/invite/recallnet
Telegram	https://t.me/THCx1
Medium	—
Audit report(s)	https://code4rena.com/audits/2025-02-recall
Bug bounty	—
CoinGecko (profile, reference)	https://www.coingecko.com/en/coins/recall
CoinMarketCap (profile, reference)	https://coinmarketcap.com/currencies/recall-network/

General project overview

Recall describes itself as a decentralized skill market for AI, where communities fund “skills/arenas”, developers run AI agents/models in competitions, and users stake the token and receive rewards for correctly “curating” the winners.

The key product thesis is “verification of AI performance” through competitions where results are backed by economic incentives: participants put capital at risk, and the settlement of rewards is claimed to be onchain.

Features/modules

Skill markets / arenas: competitions on specific skills (trading, coding, etc.) with leaderboards and ratings.
Staking → Boost: staking RECALL gives Boost credits for “voting/curating” participants; Boost is refreshed for competitions.
Developer layer: documentation on registering and building agents + the competition API (example: paper trading API).
Onchain layers: the token and the staking/reward distribution contracts on the Base network (addresses are listed in the docs).

Typical scenarios

Scenario 1 (curator): stakes RECALL → allocates Boost to agents → receives RECALL rewards if the selected participants win.
Scenario 2 (developer): registers an agent and connects to the competition API → executes trades in the simulator/competitions → gets onto the leaderboards.
Scenario 3 (community): funds/signals demand for skill markets via staking, in order to incentivize developers to build the needed AI skills.

Getting started (wallet/network)

What you need: web access to app.recall.network; an EVM wallet for staking; for the dev scenario — agent registration and an API key.
Network/chain: Base (RECALL — ERC‑20 on Base).
Fees: onchain Base fees for token/staking transactions; offchain — competition API calls (for agents).

Architecture/tech (non‑AI)

Components: web app (arenas/leaderboards/staking), competition API, token/staking/reward smart contracts (addresses published).
Participant roles: curators/stakers (Boost), agent developers (compete), market/competition organizers (parameters/rules), security council/foundation (privileged roles).
Where logic runs: token ownership and reward settlement — onchain on Base; competitions/simulators and metrics — offchain, with publication/settlement of the result.
Dependencies: Base L2; external data/price sources for the simulator (the docs mention DexScreener as the price source for the trading simulator).

Token/economics (expanded, no forecasts)

Token utility: in the documentation RECALL is described as the native asset of the markets: fees/rewards, staking for participation, ensuring honest evaluations and (prospectively) governance.
Who pays fees / receives rewards: market participants pay/earn in RECALL; curators receive rewards if the boosted participants win.
Issuance/burn: total supply is fixed at 1B (per the docs/blog).
Incentive mechanisms: stake RECALL → Boost (1:1) → curation/voting; rewards are distributed based on competition results; the documentation separately describes “Conviction Rewards” for airdrop stakers.
Distribution: the allocation structure (airdrop/foundation/community/contributors/investors) is published in the tokenomics post.
Treasury: part of the supply is reserved for the foundation and community/ecosystem; the specific spending processes are outside the scope of the current verification.

Governance

Who makes decisions: Recall Foundation / security council (privileged roles); the current token governance layer is described as “over time” (plan/intent).
How protocol parameters change: the docs describe privileged roles (upgrade/mint/pause) and that they are protected by multisigs.
Where: public documents/repositories and the changelog.
Keys/multisig: “privileged roles … secured by multisig wallets” (in the docs).

Security and incidents

Audits: a Code4rena audit has been published (2025‑02 Recall).
Bug bounty: no confirmation of a public program was found per Tier‑1 → —.
Incidents: no confirmed postmortems/incidents were found per Tier‑1 → —.
Threat model: risks of the staking/reward smart contracts and the risk of the “rules of the game” (offchain simulator/metrics), as well as the risks of privileged roles (upgrade/mint/pause), even if they are claimed to be protected by multisigs.

Project status and timeline

Current status: active; the RECALL token — ERC‑20 on Base (per the docs), the app is launched.
Key releases/milestones: TGE/token launch — 2025‑10‑15 (per the website/blog); a public changelog with release notes (2025).
Roadmap: there is no Tier‑1 roadmap page in links_* → —.

Ecosystem/integrations

Integrations: Base (ERC‑20), web app, developer guide for integrating agents and the trading API; the docs mention DexScreener for the price simulator.
Partners: the overview/website lists “Trusted by” integrations/ecosystems (see Evidence).
Where it’s actually used: leaderboards/arenas and competitions in the app + the “build an agent” developer layer.

AI component of the project

What is real AI here? AI agents/models take part in competitions (arenas/skill markets), and the platform is positioned as a skill market for AI with a rating system.
What is truly onchain? The RECALL token and the staking/accounting/reward distribution contracts are deployed on Base; the docs list the addresses and describe onchain settlement.
Why is a token needed? Participation and incentives: staking → Boost for curation/voting; rewards and fees in RECALL; the “economic stake” is used to protect the rankings.
Red flags (based on the information found): a significant part of the evaluation/competitions (simulators, metrics, ranking) is inevitably offchain; governance “over time” looks like an intent (confirmation of real onchain governance is needed).

DecAI Fit component summary

DecAI Fit: 5/6 — high alignment with the Decentralized AI thesis

Component	Level	Score
AI reality	high	3
Onchain necessity	high	3
Token necessity	low	1
Evidence	Tier‑1 present	3

Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

AI_0 (decision): 0
Claim (one line): AI is not an “intent” but the current subject area of the product (a skill market for AI).
Evidence: Tier‑1 — https://docs.recall.network/overview
Why sufficient / why not (one line): AI is described in Tier‑1 as the core of the current product, so this is not “intent”.
Conflict note (if any): —

AI_1 — what the AI does (1/0)

AI_1 (decision): 1
Claim (one line): AI agents/models take part in skill competitions (e.g., trading competitions) and are ranked by results.
Evidence: Tier‑1 — https://docs.recall.network/overview
Why sufficient / why not (one line): Tier‑1 describes “agents compete … performance determines visibility”.
Conflict note (if any): —

AI_2 — demos/examples (1/0)

AI_2 (decision): 1
Claim (one line): there is a live app (staking/arenas) and reproducible dev guides on connecting an agent and the trading API.
Evidence: Tier‑1 — https://app.recall.network/stake ; https://docs.recall.network/competitions/build-agent/trading
Why sufficient / why not (one line): you can “go in and try it”, and there is a guide with requests/a code example.
Conflict note (if any): —

AI_3 — metrics/quality (1/0)

AI_3 (decision): 0
Metrics: —
Context (version/date/how measured): —
Evidence: Tier‑1 — — (no formal metrics/quality evaluation protocols for “Recall Rank” were found per Tier‑1)
Why sufficient / why not (one line): without a formalized methodology and metrics, the component is not counted.
Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

AI_4 (decision): 1
Claim (one line): guides on building agents and the API for the trading simulator (endpoints, code examples) are published.
Evidence: Tier‑1 — https://docs.recall.network/competitions/build-agent ; https://docs.recall.network/competitions/build-agent/trading
Why sufficient / why not (one line): the dev documentation describes agent integration and the basic workflow.
Conflict note (if any): —

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

OC_1 (decision): 1
Chain: Base (Ethereum L2).
Addresses/identifiers: RECALL token 0x1f16e03C1a5908818F47f6EE7bB16690b40D0671; staking 0x37Ee1FE41231b631d62658372b457235b9b884e0 (and other addresses in the docs).
Evidence: Tier‑1 — https://docs.recall.network/reference/token-reference ; https://basescan.org/token/0x1f16e03C1a5908818F47f6EE7bB16690b40D0671
Why sufficient / why not (one line): Tier‑1 provides specific addresses, confirmed by the explorer.
Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

OC_2 (decision): 1
What useful logic is onchain: staking → Boost and settlement of results/rewards per round; separate contracts (staking/reward allocation) are published in the docs.
Evidence: Tier‑1 — https://docs.recall.network/get-started/staking-and-boosting ; https://docs.recall.network/reference/token-reference
Why sufficient / why not (one line): the existence of separate staking/reward addresses and the description of onchain settlement go beyond “just a token”.
Conflict note (if any): —

OC_3 — onchain is critical (1/0)

OC_3 (decision): 1
“Replace the blockchain” test: without onchain stakes/settlement, the key property of “economic honesty” of the rankings and reward distribution is lost.
Evidence: Tier‑1 — https://docs.recall.network/overview ; https://docs.recall.network/get-started/staking-and-boosting
Why sufficient / why not (one line): Tier‑1 links “economic stakes” and onchain settlement to the honesty/trustworthiness of results.
Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

TK_0 (decision): 0
Claim (one line): the project has a token, RECALL (ERC‑20, Base).
Evidence: Tier‑1 — https://docs.recall.network/get-started/token-overview
Why sufficient / why not (one line): the docs specify the ticker, standard, supply and contract address.
Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

TK_1 (decision): 1
Claim (one line): RECALL is used as the “native asset”: participants pay fees and receive rewards in RECALL.
Evidence: Tier‑1 — https://docs.recall.network/get-started/token-overview
Why sufficient / why not (one line): the Utility section explicitly states fees/rewards in RECALL.
Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

TK_2 (decision): 1
Claim (one line): RECALL is staked for participation and for “market security” (honest evaluations/resolution of outcomes).
Evidence: Tier‑1 — https://docs.recall.network/get-started/token-overview ; https://docs.recall.network/get-started/staking-and-boosting
Why sufficient / why not (one line): the docs describe the stake mechanics (stake → Boost) and the security role of the stake.
Conflict note (if any): —

TK_3 — governance (1/0)

TK_3 (decision): 0
Claim (one line): token governance is described as “over time” (a plan), but a specific working onchain governance mechanism is not confirmed per Tier‑1.
Evidence: Tier‑1 — https://docs.recall.network/get-started/token-overview
Why sufficient / why not (one line): the wording about governance is given as a future role, without a voting process/contracts.
Conflict note (if any): —

TK_4 — token is replaceable (1/0)

TK_4 (decision): 1
Claim (one line): Tier‑1 does not show that the economic model technically requires RECALL specifically (fees/rewards/stake could use another asset, e.g., USDC).
Evidence: Tier‑1 — https://docs.recall.network/get-started/token-overview
Why sufficient / why not (one line): Utility describes stake/fees/rewards but does not show the technical necessity of RECALL specifically as the asset.
Conflict note (if any): —

Evidence (table)

Tier	Source	What it proves
Tier‑1	https://docs.recall.network/overview	What the “decentralized skill market for AI” is, how the “stake → competitions → rankings” logic is structured, and why “on-chain transparency” is claimed.
Tier‑1	https://docs.recall.network/get-started/token-overview	Ticker/standard/total supply/token address on Base and utility (fees/rewards, stake to participate, market security, governance over time).
Tier‑1	https://docs.recall.network/get-started/staking-and-boosting	The “stake RECALL → Boost (1:1) → rewards” mechanics, and that results “settle on-chain”.
Tier‑1	https://docs.recall.network/reference/token-reference	Addresses of the token, staking and reward allocation on Base + description of privileged roles (multisig, pause/upgrade/mint).
Tier‑1	https://basescan.org/token/0x1f16e03C1a5908818F47f6EE7bB16690b40D0671	Onchain confirmation of the RECALL token (ERC‑20, Base).
Tier‑1	https://app.recall.network/stake	Live app: entry into the staking/Boost mechanics (demo for AI_2).
Tier‑1	https://docs.recall.network/competitions/build-agent/trading	Reproducible developer guide for the trading API (demo/example for AI_2).
Tier‑1	https://blog.recall.network/recall-tokenomics	Tokenomics (distribution of tokens across pools).
Tier‑1	https://code4rena.com/audits/2025-02-recall	Public audit/security competition (Code4rena).
Tier‑1	https://recall.network/changelog	Changelog (product release notes).
Tier‑1	https://github.com/recallnet/contracts/security/advisories	The existence of Security Advisories in the official repository (no publications yet).