HackerReposA FIELD GUIDE TO OPEN SOURCE
ProSponsor the shelf♧ 0
← Back to top all-time
Integuru-AI
Integuru
Python2024–2026
Integuru-AI / Integuru

Integuru

The first AI agent that builds permissionless integrations through reverse engineering platforms' internal APIs.

3Distinct people
3Mentions
0Explicit recommenders
4.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The first AI agent that builds permissionless integrations through reverse engineering platforms' internal APIs.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:05:26 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month3 dated mentions

Observed mentions: 2024-10-29 13:00:40 UTC to 2026-05-29 14:16:55 UTC.

012024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsOct 20242024-11-01 00:00:00 UTC to 2024-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2025-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-02-01 00:00:00 UTC to 2025-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-07-01 00:00:00 UTC to 2025-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 20252025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsMay 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC110
Nov 20242024-11-01 00:00:00 UTC2024-12-01 00:00:00 UTC000
Dec 20242024-12-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
Jan 20252025-01-01 00:00:00 UTC2025-02-01 00:00:00 UTC101
Feb 20252025-02-01 00:00:00 UTC2025-03-01 00:00:00 UTC000
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC000
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC000
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC000
Jul 20252025-07-01 00:00:00 UTC2025-08-01 00:00:00 UTC000
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC000
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC000
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC000
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC000
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC000
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC000
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC000
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC110

What Hacker News says

1 sources

Launch HN: Integuru (YC W24) – Reverse-engineer internal APIs using LLMs

Hey HN! We’re Richard and Alan from Integuru (https://integuru.ai). We build low-latency integrations with platforms lacking official APIs. We take custom requests and manage creation, hosting, and authentication. To automate our work, we built an open-source AI agent that reverse-engineers internal APIs to generate integration code. Here’s a demo: https://www.youtube.com/watch?v=7OJ4w5BCpQ0. Many products need integrations with third-party services, but platforms often lack official APIs. Examples include logistics software, financial services, electronic health records (EHRs), and government websites. To build low-latency integrations, developers must reverse-engineer internal APIs, but this can get complicated. With Integuru, you can have easier access to integrations. We started as recent college grads trying to make US income tax dat
Read the rest
a accessible. We contacted banks, brokerages, payroll software, and more to request access to their APIs, but none took us seriously. We resorted to building integrations with these systems to extract documents like W-2s and 1099s. We initially used browser automation but ran into two big problems: our integrations (1) weren’t reliable due to changing UIs and (2) had slow execution speeds due to spinning up browsers and waiting for pages to load. We experimented with AI-based automation maintenance, but it didn’t solve slow speeds. So, we concluded that browser automation is useful when execution speed isn’t essential, but reverse engineering is often the only path for performant integrations. Through reverse-engineering dozens of platforms, we noticed many internal API design patterns that LLMs could decipher. We built an agent to automate the creation of integrations. Today, Integuru can analyze a platform’s internal API designs and build an integration in minutes. The agent mimics what a human does when reverse-engineering. Say you want to download utility bills from a utility website. You’d first use Integuru to generate a file of network requests and a file of cookies. You pair these two files with a prompt about your desired action—in this case, to download utility bills. Integuru identifies the final request that downloads utility bills. The request URL might look like this: https://www.example.com/utility-bills?accountId=123&userId=4.... It then identifies parts of the request that depend on other requests. The example URL contains dynamic parts— accountId and userId—that usually are in the response of previous request(s). It then finds other requests whose response contains any of these and adds them to the dependency graph. The newly found request URLs might look like https://www.example.com/getAccountId, https://www.example.com/getUserId, and so on. This process repeats until the most recently found request doesn’t depend on any other request. Integuru then traverses up the graph, starting from the requests without dependencies while converting each request into a runnable function. Integuru supports a surprising number of use cases like downloading documents, sending money, creating virtual cards… People already use the agent to build low-latency APIs for platforms like Robinhood, transportation management systems (TMS), and more. However, the agent still has limitations due to current LLM capabilities and long-tail edge cases, but we’ve been giving each platform to the agent for the first try. When the agent does struggle, we find the generated graphs and code still helpful as references for us to complete the work manually. The agent and all integrations are open-source under AGPL-3.0. We charge for services to (1) build custom integrations when the agent struggles or for your convenience, (2) handle hosting, and (3) manage authentication using authentication cookies from authenticated browser sessions. We charge per API call with an implementation fee for new platforms. We’re currently working to increase the agent’s coverage and improve code generation. We will continue to iterate and want to one day allow developers to integrate with all platforms instantly. Integuru is still an early effort. We’re passionate about automating integrations and would love your feedback!
218 points · Open discussion

MAKE YOURSELF AT HOME

A few shortcuts

/
Search the collection
?
Open this guide
Esc
Close dialogs and navigation

Your saved repositories and interests stay in this browser.