Thand – open-source, distributed, JIT, PAM and provisioning platform

Hacker News

Hey HN! We are building Thand, an open-source, distributed platform for Just-in-Time (JIT) access, authorization (PAM), and provisioning. Why? I’ve been at various companies now; either having to raise tickets, waiting on internal processes to get access to systems, resources or SaaS tools. Or, having extremely elevated accounts all in one place and as a single point of failure when services go down just as you need them. None of the available PAM tools seemed easy to work with, so it got me seeking an alternative. What is Thand? Thand is a lightweight, open source and self-hosted agent that runs locally or in your cloud environment. It orchestrates and distributes requests via durable workflows (via Temporal and CNCF Serverless workflows) to grant temporary access to resources or provision resources via its “providers”. Unlike other tools, that are locked into particular cloud environments or SaaS providers. With Thand you deploy the agents with their respective access. Wherever, you need to get access to. Temporal can route the workflow execution to elevate or provision resources across multiple environments (cloud and local) and identities. What's with the name? Thand is Sindarin, (‘Shield/Guard of the Forest’). We are currently in preview and looking for feedback. GitHub: https://github.com/thand-io/agent Docs: https://docs.thand.io Website: https://www.thand.io/ Thanks!

Visit product View on Hacker NewsNov 25, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, single · Missing: mac, macos, cursor

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

84%84% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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