Loading video...

Video Failed to Load

Go Home

Complete visibility into your onchain payments with Requests v3 At real volume, the gap between what happened and what you can see is an operational problem. The Requests page in the Relay Dashboard now closes it: near real-time data on every request, filters you can compose across status, chains,...

10,832 views • 1 month ago •via X (Twitter)

16 Comments

Relay's profile picture
Relay1 month ago

Under the hood: Requests v3, rebuilt on Elasticsearch. One term finds any request: ID, wallet, deposit address, or any tx hash. Near real-time data that v2 couldn't give you. Cleaner responses with quoted vs actual on every fee. Per-key access, so heavy usage never slows anyone else. Everything the Dashboard can do, your own tooling can do directly via GET /requests/v3.

Relay's profile picture
Relay1 month ago

requests/v2 is deprecated as of today, with a 4-month migration window before it retires. The migration guide covers every change, and updated SDKs (RelayClient and RelayKit) do most of the work: Note: Requests v3 authenticates with an API key. Create one in the Dashboard.

Arminrume's profile picture
Arminrume1 month ago

LFR💜🥺

yag's profile picture
yag1 month ago

add arc bridge @RelayProtocol pls!!

Ink ⚡'s profile picture
Ink ⚡1 month ago

Please add @arc bridge

Vicky Schepel's profile picture
Vicky Schepel1 month ago

Should active users expect any airdrop?

Artem Valmus's profile picture
Artem Valmus1 month ago

@RelayProtocol Hi Team, we added Relay to XFlow ( our cross-chain explorer. The data doesn't quite add up. Worth comparing analytics to see why?

QTee99's profile picture
QTee991 month ago

when we can bridge to ARC?

AGNT.SOCIAL's profile picture
AGNT.SOCIAL1 month ago

when adding tokenized stocks on RH?

Homeros's profile picture
Homeros1 month ago

gRelay 💜

eduardovictory's profile picture
eduardovictory1 month ago

Users that are affected are eligible for compensation as part of our previously approved TOS policy Support Dashboard:

JΞSSΞ's profile picture
JΞSSΞ1 month ago

When arc?

0xkaka's profile picture
0xkaka1 month ago

pls we need @arc

eduardovictory's profile picture
eduardovictory1 month ago

Affected users are eligible for compensation as part of our previously approved TOS policy. If you are affected, compensation management is available on our Support Dashboard below ⤵️

eduardovictory's profile picture
eduardovictory1 month ago

Users that are affected are eligible for compensation as part of our previously approved TOS policy If you are affected, Support Dashboard:

eduardovictory's profile picture
eduardovictory1 month ago

Users that are affected are eligible for compensation as part of our previously approved TOS policy If you are affected here is our Support Dashboard:

Related Videos

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 views • 10 months ago