Infryn

Infryn brings private AI infrastructure and a shared credit economy into one platform connecting participation with practical AI use.

[Infryn @infryncompute]

$INFRYN IS LIVE

Infryn brings private AI infrastructure and a shared credit economy into one platform, connecting participation with useful AI work.

At its core are AI credits: earn through staking, buy what you need, trade what you don’t use or transfer credits to another wallet. Put them to work across applications, developer tools and AI agents.

Choose models for your workload, manage access and set spending limits. Protected and Confidential options offer different levels of privacy for supported models, helping you choose how sensitive work is handled.

From credits to compute, Infryn puts access, spending and privacy at the center of your AI experience.

CA: 0x7D0A37c6eDA00cde7171b06B793C7D36fA9600bB

Web: https://t.co/Ai7pkrDloH
X: https://t.co/9olp8TaJUR

[Infryn @infryncompute]

Good ideas travel.

Here’s a preview of $INFRYN referrals and community leaderboard. Share your referral link, track eligible commissions and request payouts from your dashboard.

Choose a public alias for the leaderboard. Your wallet address, API keys, spending and AI activity stay off it.

Watch the walkthrough below.

Product preview with simulated account data and transactions.
https://t.co/OOPKIapQny

[Infryn @infryncompute]

Take part in the community while keeping your account details private.

Infryn’s leaderboard uses a public alias you choose. Your wallet address, API keys, spending and AI activity stay off the public board.

Points recognise qualifying referrals, giving you a way to follow your participation without displaying your private usage.

Your contribution can be visible. Your account details stay yours.

https://t.co/Ai7pkrDloH

[Infryn @infryncompute]

@nottouchingrass No, it’s not agent-only. Users will be able to access Infryn directly too. We’re rolling out credit purchases and transfers and we’ll show how staking fits into usage in the demo video.

[Infryn @infryncompute]

A closer look at Infryn’s API key flow.

This demo shows how developers can create separate keys for agents with explicit permissions, expiry and spending limits. Agents can use the access they need while each key remains independently controlled and revocable.

Inference access does not grant authority to purchase or trade credits, or change privacy settings. Read-only tools can check a balance, list connected models and inspect requests made with the same key.

Useful access. Clear boundaries. Your control.

Watch the demo ↓
https://t.co/S4ZlGwLfXS

[Infryn @infryncompute]

@nottouchingrass Not yet. will share an update on it later

[Infryn @infryncompute]

Participate Through Staking

Staking connects participation with funded AI credit rewards on Infryn.

Rewards depend on available funding, with no fixed yield. Those credits connect participation to useful AI work.

https://t.co/OOPKIapQny

[Infryn @infryncompute]

For now, you can start by connecting your agent through API/MCP using its own key, with permissions, spending limits, expiry and access you can revoke anytime. It can discover models and check balances and request status today. The text API supports streaming, tool calling and structured JSON on compatible models, with live inference after you buy credits. Agents cannot sign transactions or spend from your wallet by design which you can choose to override if you want autonomous signing and spending.

For privacy, your account identity and IP aren’t forwarded to the model provider. Protected mode requires routes with no-training and no-content-retention policies. You set a minimum privacy level; requests are refused if it cannot be met.

[Infryn @infryncompute]

Choose Privacy for the Work

Different workloads call for different protection.

Infryn offers Protected and Confidential options for supported models, making privacy a choice you can assess before sending sensitive work.

[Infryn @infryncompute]

Give Agents a Budget

Set the spending boundaries before your agents start working.

Infryn brings agent budgets and access controls together so automation operates within limits you define.

[Infryn @infryncompute]

@CTgymrat https://t.co/hPSkiw6Nqy

[Infryn @infryncompute]

Connect Through MCP

Bring Infryn into your AI tooling through Model Context Protocol (MCP).

Alongside API access, MCP provides another way for compatible tools and agents to interact with the platform.

[Infryn @infryncompute]

Introduce Others to Infryn

Know someone building with AI?

Infryn’s referral features give you a way to introduce others to the platform and participate in its growth from developers connecting tools to teams exploring private AI.

https://t.co/OOPKIaqod6

[Infryn @infryncompute]

When you create an Infryn API key for an agent, you choose what it can access, set an expiry and cap its spending.

The agent uses that key to make inference requests and where permitted, check its balance or inspect requests made with the same key. That key does not give the agent control over purchases, trading or privacy settings.

You can revoke its access when needed.

[Infryn @infryncompute]

Give agents useful access with boundaries.

Watch us create an API key in the $INFRYN with explicit permissions, expiry and spending limits.

These controls are implemented. Agents can check balances, list connected models and inspect requests made with the same key. Inference access does not grant permission to purchase credits, trade or change privacy settings.

Every automation needs revocable permission and its own limits.

Your AI. Your infrastructure. Your control.

[Infryn @infryncompute]

When Verification Fails, Stop

Invalid verification should stop a confidential request.

Infryn rejects requests when the required verification fails, preserving the privacy boundary you selected.

[Infryn @infryncompute]

Protection on the Return Journey

Confidential AI involves both the request and its response.

$INFRYN supported confidential flow combines client-side encryption with encrypted responses, keeping protection part of the exchange.

[Infryn @infryncompute]

Verify Before You Trust

$INFRYN checks evidence from a Trusted Execution Environment (TEE) as part of its confidential inference flow.

Verification helps establish that sensitive work is going to the expected protected environment.

[Infryn @infryncompute]

Put Unused Credits to Work

Your credit needs can change. $INFRYN marketplace lets you buy credits when you need more or offer unused credits for sale. Transfers give you another way to move credits where they’re needed.

[Infryn @infryncompute]

Encryption Starts With You

For supported confidential workloads, $INFRYN encrypts sensitive content on the client before sending it for execution.

Privacy begins where your request begins.

https://t.co/OOPKIapQny

[Infryn @infryncompute]

AI agents are becoming autonomous.

Their infrastructure should become private.

$INFRYN combines confidential AI inference, verified TEE execution, client-side encryption and agent controls with an on-chain AI credit economy.

@orbiodotso helped prove the demand for tokenized AI inference.

Infryn takes the next step: making that infrastructure private and verifiable.

Your agents. Your data. Your control.

https://t.co/OOPKIaqod6