Tag
A practitioner asks how to maintain and deploy customer-specific code generated by an agent harness, ideally keeping customer variants in sync with the core app without dedicated VMs per customer. The post seeks existing tools or platforms that handle end-to-end deployment of agent-modified, per-tenant codebases.
Helo is an independent email API launched on Product Hunt by former Postmark engineers, targeting developers and platforms that send email on behalf of their customers with per-tenant isolation, deliverability safeguards, and usage-based pricing starting at $0.00035 per email.
A multi-tenant dashboard for small businesses and teams to share and manage AI agent platforms, featuring single sign-on, Docker deployment, and integration with various backends.
A developer is seeking advice on choosing between Hermes/OpenClaw and LangGraph/Mastra for building a multi-tenant AI agent SaaS, focusing on production concerns like isolation and observability.
The article explains how agent memory systems can leak data due to post-filter tenant scoping in vector search and recommends scoping at write time to prevent cross-tenant data exposure.
A self-hosted, multi-tenant company OS that integrates Claude Code and Codex AI agents for business operations, available for free under a Fair Source license.
Oberik is a free backend and SDK launched to address common infrastructure challenges in building AI agent systems, such as document handling, multi-tenancy, and security, and is now open for developer testing and feedback.
Verity is a new open-source, permission-aware memory layer for multi-tenant AI agents, preventing cross-tenant data leaks by enforcing access controls directly in retrieval queries rather than relying on model behavior.
This AWS article outlines five best practices for multi-tenant SaaS architecture, focusing on tenant isolation via IAM, per-tenant cost attribution, and compliance evidence to help ISVs pass enterprise procurement reviews.
HeraSys is a collaborative LLM serving system that optimizes end-to-end performance of concurrent workflows by eliminating cross-workflow computational redundancy and using load-aware joint scheduling, achieving up to 2.17x P99 latency reduction and 1.85x throughput improvement.
Animam is a multi-tenant AI agent platform that lets agencies deploy personalized AI agents for clients via widget, API, voice, and MCP. The builder seeks feedback on its infrastructure approach from production users.
JoyNexus proposes a unified service for multi-tenant VLA model post-training, decoupling training, inference, and environment services with shared base models and tenant-specific slots, improving efficiency through group batching and scheduling.
This paper introduces Cost-Governed RAG, an architecture combining a codebook-oblivious vector index (TurboVec) with a multi-tenant LLM governance gateway to enable per-tenant cost attribution across retrieval and generation, achieving 99.96% attribution accuracy with minimal overhead.
Helicone implemented a feature called HQL allowing customers to write raw SQL queries against a shared ClickHouse database. They use ClickHouse row policies and custom settings to enforce multi-tenant isolation, ensuring each organization can only see its own data.
Sharing 5 key takeaways from Google Cloud's multi-tenant agent AI system reference architecture, which is inspiring for indie developers and small teams to productionize Agents.
AWS Lambda announces MicroVMs, a new serverless compute primitive that provides isolated, stateful execution environments with VM-level isolation and near-instant launch, powered by Firecracker.
This article reviews the design highlights and shortcomings of the OpenClaw Agent framework, and shares the author's experience in designing a better agent framework, FastClaw, emphasizing principles such as cloud-native, lightweight, and multi-tenancy.
The author built an open-source, MIT-licensed platform for creating and managing AI agents, featuring provider-agnostic support, MCP integration, memory, skills, scheduled triggers, and Kanban boards, deployable via Docker Compose.
EvalStop is a scheduling primitive for multi-tenant RLHF platforms that detects and corrects reward overoptimization by monitoring downstream evaluation scores and terminating jobs on consecutive declines, achieving 98% precision and 99% recall while improving job completion time by 9% and cutting wasted compute by 22%.
A year-long reflection on the hard parts of shipping AI agents for real service businesses, highlighting that infrastructure and edge cases matter more than the AI layer.