Infrastructure & Cloud

Map of planned industrial and infrastructure projects, clusters, airports, and harbors across 140+ countries. Explore $70T+ CapEx and logistics opportunities on Fluidify. The Fluidify Map is the 2D industrial and infrastructure map. Use it to explore planned projects, industrial clusters, airports, and harbors across 140+ countries. Machine-readable copies: /home.md · /map.md · /about.md · /llms.txt

Software has never been easier to start — or easier to turn into a mess. A simple application becomes a pile of frameworks, dependencies, services, and infrastructure, and AI just makes the pile grow faster. View on GitHub Edit on Replit Free, source included, nothing to sign up for. Most software starts from a blank project. Features get added, dependencies accumulate, architecture evolves, and workarounds become permanent — until changing one thing means worrying about five others. Scalar starts from the opposite premise: a deliberately simple foundation — Python on the server, server-rendered HTML, SQLite, and minimal JavaScript. A working application you can read from top to bottom, understand, and change.

Introduction Why Fraise? Changelog Getting Started Toggle Quickstart Your first memory Core concepts Context engineering Glossary for(let e of document.querySelectorAll(`[data-slot="collapsible-trigger"]`)){let t=e.closest(`[data-slot="collapsible"]`),n=t?.querySelector(`:scope > [data-slot="collapsible-content"]`);t&&n&&(n.style.setProperty(`--radix-collapsible-content-height`,`${n.scrollHeight}px`),e.addEventListener(`click`,()=>{let r=t.dataset.state!==`open`,i=r?`open`:`closed`;if(r&&(n.hidden=!1),n.style.setProperty(`--radix-collapsible-content-height`,`${n.scrollHeight}px`),t.dataset.state=i,e.dataset.state=i,n.dataset.state=i,e.setAttribute(`aria-expanded`,String(r)),!r){let e=()=>{n.dataset.state===`closed`&&(n.hidden=!0)};n.addEventListener(`animationend`,e,{once:!0}),setTimeout(e,350)}}))}document.addEventListener(`click`,e=>{(e.target?.closest(`a[data-sheet-close]`))?.dispatchEvent(new CustomEvent(`sheet-close`,{bubbles:!0}))}); Installation Toggle Homebrew Docker Linux packages Release binaries From source Query Language Toggle Foundations Toggle Design principles Commands Tokens Toggle Keywords Punctuation Identifiers Literals Bounds Parameters Reference Toggle Grammar Warnings Retrieval Toggle Memory Model Toggle Memory graphs Temporality Ranking Toggle Hybrid retrieval Excess transmission Ranking guarantees Retrieval lanes Embeddings Toggle Embeddings overview Producing vectors Dimensions and precision The vector index Architecture Toggle Architecture overview Components Toggle Server Engine Scheduler Database Concurrency Toggle Multi-graph architecture Sched

Open-source, self-hosted database sync with real-time CDC — PostgreSQL, MySQL, SQLite, MongoDB and Redis, any engine to any other. One command to install. Syncle connects to PostgreSQL, MySQL, SQLite, MongoDB and Redis. You pick a table on one of them and where it should go on another. Syncle copies the rows across, then keeps copying as the source changes. Docker with Compose v2 is all you need. Runs on your own machine, MIT licensed. PostgreSQL Syncle MySQL MongoDB Redis One Postgres table feeding three other databases at the same time. A bridge connects one source to one or more destinations. Any engine can sit on either side, so a Postgres table can go to MongoDB, to Redis, or to another Postgres. A destination can also be an HTTP endpoint, if you are feeding a service instead of a database. If the destination table does not exist yet, Syncle creates it and works out the column types for that engine. Writes are upserts, so running a sync twice will not leave you with two copies of a row. A job that dies partway through restarts from the last row it recorded, not from the beginning.

Run LLMs, vision, embeddings, and text-to-speech on the JVM at native speed. No Python runtime, ONNX bridges, or Docker sidecars. Quixotic AI Stack Examples Benchmarks AI sovereignty for the JVM Some call AI on the JVM quixotic. We call it Quixotic AI. Finally, AI in a jar. AI inference engine. Chat, vision, embeddings and text-to-speech capabilities for the JVM, with Spring AI and LangChain4j integrations. TikToken-compatible and customizable tokenizers for popular LLM models. Multi-backend tensor engine, in the works. Java, C, CUDA, HIP, Metal, OpenCL, and Mojo. Write once, accelerate everywhere.

StatLite turns Spring Boot Actuator metrics into a lightweight self-hosted dashboard with local SQLite history, well suited to small VPS deployments. Quarkus, Micronaut, and other applications are also supported. 简体中文 README Tiếng Việt README Lightweight monitoring for Spring Boot Turn Spring Boot Actuator into a self-hosted dashboard with history, charts, restart detection, and local SQLite storage. Quarkus, Micronaut, and other applications can use the same dashboard. One Go binary. About 15 MiB idle. No external monitoring services. GitHub StatLite Run StatLite locally Open http://127.0.0.1:9090 . StatLite monitors itself out of the box, so you can explore the dashboard before configuring your application. docker run --rm \ -p 127.0.0.1:9090:9090 \ ghcr.io/pvrlabs/statlite:latest ? Why it exists | Actuator exposes useful operational data, but raw JSON endpoints are not a practical everyday dashboard. Install StatLite Install the latest release on macOS or Linux with the command that fits your workflow.

Turn business intent into specs, agent-built code, independent AI review, and human-controlled delivery with a spec-driven software development platform. What We Do AI Consulting and Transformation Harness the power of artificial intelligence to transform business operations AI-Powered Product Engineering A structured studio to ideate, validate, and build scalable digital products Enterprise System Modernization Transform legacy systems into modern, scalable architectures Digital Customer Experience Design exceptional user experiences that delight customers Industries Banking, Finance, and Insurance Healthcare Manufacturing Media and Entertainment Gaming Real Estate Hiring Hospitality E-commerce Engineering AI Engineering Full Stack Engineering Mobile Engineering Web Engineering Backend Engineering DevOps Engineering UI/UX Engineering Design Engineering QA Engineering IoT Engineering Business Analysis Insights Case Studies Work that delivers real business impact Blogs Latest insights and perspectives on technology trends Guides Step-by-step tutorials and best practices Magazines Curated collections of industry knowledge Events Upcoming webinars, conferences, and workshops About About Us Decoded: Innovate. Collaborate. Build. Culture Behind the scenes at the GeekBase Team The talent building bold solutions Join Us Open positions and roles at GeekyAnts How We Work Our principles, process, and approach to delivery Security & Compliance How we approach security, quality, and compliance. Contact Us {"@context":"https://schema.org","@type":"WebPage","name":"AntFlow AI","descript

Stop trusting your AI agent with your machine. Give it a sandbox it can Abyss Docs Blog GitHub Get started Get started Search Search Cancel Loading search index… You configure your editor like a normal ACP agent, and Abyss handles everything Docker for you. docker : # This is a pre-built image with Abyss and Pi pre-installed image : "ghcr.io/sethcurry/abyss-pi:latest" # Abyss speaks ACP, so we invoke Pi via pi-acp agent_command : - pi-acp host_mounts : # This mounts the current directory inside the container. # It doesn't take a target path because ACP sends a `cwd` # so we need the paths to line up between the host and # container - source : "./" # This mounts your .pi directory so that the agent has # API keys for your LLM, prior sessions, plugins, etc. # # You can put this in the `copy_files` config section # which will prevent the LLM from modifying your config files # but your sessions won't end up on your host PC so the session # files are lost when the container gets deleted. - source : "~/.pi" destination : "/root/.pi" Works with any ACP client you want!

Run your coding agents in one workspace. Maxxwell helps you follow their progress, coordinate their work, and focus on what needs your attention. Run a dozen coding agents at once. Maxxwell keeps each one moving for you and brings you only what truly needs your attention . Join Discord Maxxwell ~/src/ rindler-mvp Find a lane, a branch, a file… ⌘K 7 running Fleet Queue Review All repos + filter Sort: needs you Workspaces R rindler-mvp 9 M maxxwell-ide 2 S site 1 Views Needs you 2 Running 7 Stalled 1 Done today 14 Needs you 2 R kv-cache eviction policy feat/kv-evict busy 14m, no file writes asked a question +0 −0 14m R flaky auth e2e fix/auth-e2e exit 137 · third attempt runner OOM +18 −4 2m Running 7 R sitemap canonical tags fix/sitemap-canon writing tests 6 files +142 −38 6m R billing webhook idempotency feat/wh-idem running suite 3 files +61 −12 11m M typed config loader refactor/config reading 14 files +9 −3 3m R docs: gate semantics docs/gates queued behind 2 — — R search index backfill chore/backfill shard 3 of 8 +24 −0 21m S mobile nav overflow fix/nav-overflow waiting on build +7 −7 8m M porter deploy retry fix/porter-retry queued behind 1 — — Done today 14 11 merged · 2 awaiting review · 1 abandoned ⌄ Needs you · lane 07 Busy for 14 minutes with nothing to show for it. 142 tool calls since the last file write. It is re-reading the same three files. Working 14m 08s Last file write 13m 51s ago Diff +0 −0 Tool calls 142 “Two schema options here — evict by LRU or by token budget. Which do you want?” › 142 tool calls · 3 messages Read src/cache

Vercel is a hosting platform built around the frontend workflow. A project connects to a Git repository, and every push produces a deployment: production builds from the main branch, and preview builds from every other branch and pull request. The platform is best known for Next.js, the React framework its parent company maintains, but it builds and serves other frameworks and static output too. Deployments run on a global edge network, and build configuration lives in a checked-in file rather than only in a dashboard, so settings travel with the code. Beyond hosting, Vercel sells the surrounding primitives: serverless and edge functions, image optimization, and storage through marketplace partners. Teams that want one vendor for the frontend path consolidate here; teams with long-running backend workloads usually keep those elsewhere.

Neon is a managed Postgres service built on a storage layer that separates compute from data. Because the data layer is copy-on-write, the service can create a full database branch in seconds, and that branch starts as a pointer into the parent's history rather than a physical copy. The practical result is a database workflow that resembles Git. A team can branch production for a preview environment, run migrations against the branch, and throw it away without touching the parent. Point-in-time restore uses the same mechanism, so recovering to a moment before a bad migration does not require replaying a backup. Compute scales to zero when idle, which suits development and preview environments that sit unused most of the day. The tradeoff is cold-start latency on the first query after a suspend, and a connection model that expects a pooler for serverless clients.

Always-on agents that watch for the moment a company becomes worth contacting, find the right person there, and draft the message. Free plan from your URL, no account needed. OctoLoops is your unfair advantage in outbound. It watches for the moment a company becomes worth contacting, finds the right person there, and drafts the message. Around the clock, without you asking. We’ll find who to contact, where to reach them, and how to turn interest into sales. Launched Commercial v3.0 with expanded controls for teams running project management on their own infrastructure Added automated survey follow-ups for Scale and Enterprise customers

Staffcoder helps developers build real-world engineering skills through hands-on framework practice and production-style challenges in a professional IDE. Practice Real-World Engineering with modern frameworks. Staffcoder is a hands-on coding environment where developers solve real engineering problems, from modern frameworks to DevOps tooling, inside a professional IDE. 1000+ challenges across 40+ learning paths. React Next.js Vue.js Spring Boot Running 1 import { useState } from 'react' 2 3 export default function App () { 4 const [count, setCount] = useState ( 0 ) 5 6 return ( 7 <main> 8 <h1> Hello Staffcoder </h1> 9 <button onClick ={()=> setCount (c=>c+1)}> 10 count is {count} 11 </button> 12 </main> 13 ) 14 } $ npm run dev ✓ Ready on :3000 React 19 Next.js 16 Vue.js 3.2 Spring Boot 4.1 Skills you can practice React (Typescript) React Native Git GitHub Actions .NET AI Agents Docker Spring Boot TypeScript MERN Node.ts Django FastAPI Kafka PostgreSQL Prompting & Evaluation RAG Memory & Context MERN (Agentic) AWS Kubernetes Laravel Linux Spark Terraform Angular Next.js MCP Agentic Full-Stack Web Development Android Java Android Kotlin Cypress MongoDB Playwright Redis Ruby on Rails Selenium Java Vue.js React (Typescript) React Native Git GitHub Actions .NET AI Agents Docker Spring Boot TypeScript MERN Node.ts Django FastAPI Kafka PostgreSQL Prompting & Evaluation RAG Memory & Context MERN (Agentic) AWS Kubernetes Laravel Linux Spark Terraform Angular Next.js MCP Agentic Full-Stack Web Development Android Java Android Kotlin Cypress MongoDB Playwright Redis Ruby on Rails

Drizzle is a TypeScript ORM built around the idea that the query layer should not hide SQL. Schema is declared in TypeScript, queries are written with a chainable API that maps closely to SQL clauses, and the generated types flow from the schema definition rather than from a separate code generator pass. Migrations are produced by diffing the declared schema against the previous state. The tool emits plain SQL files, which means a migration can be read and edited before it runs. That is a deliberate contrast with ORMs that generate opaque migration steps, and it makes review of schema changes part of the normal pull request. The library supports Postgres, MySQL, SQLite, and the serverless variants of each, and it runs in edge runtimes because it has no dependency on Node-specific APIs. Teams that want an ORM but dislike losing the ability to reason about the emitted SQL tend to land here; teams that want a fully abstracted data layer with a large ecosystem of plugins may prefer a heavier framework.

A GitHub Action / GitLab CI step that checks your deploy against a signed approval record before it reaches production. Built for teams that already have a release-approval process and want it enforced, not just documented. How it works Pricing Docs Contact Start free Log in Production release controls Control what ships to production. Require approvals, verify the approved commit is the one deploying, and pause releases when needed. One step in GitHub Actions or GitLab CI. See how it works Free for one service · No credit card · Start in shadow mode GitHub Actions GitLab CI .github/workflows/deploy.yml Build 2m 14s Tests 1m 23s Approvegate Waiting for approval Deploy api / production Production Commit 9f2a1c7 Status Waiting for approval Requested by jdoe Reviewers M Maya A Alex Approve View build Release controls Approved commit verified Ensures the approved commit is the one deployed Independent approver Prevents self-approval No active freeze Checks your team's freeze windows Commit-bound approvals Make sure the commit you approved is the one being deployed.

A fully conformant Kubernetes gateway, built in Rust for speed. It carries your HTTP, LLM and MCP traffic on one data plane. Portus Conformance Performance Gateways Architecture Standalone GitHub 0.4.0 One network stack: Rama Portus API & AI Gateway A fully conformant Kubernetes gateway, built in Rust for speed. It carries your HTTP, LLM and MCP traffic on one data plane. Gateway API v1.6.2, experimental channel. The upstream suite runs in-cluster against a real per-Gateway deployment. Each square below is one passing result. Measured with the open gateway-api-bench method: three interleaved rounds on one machine, against the same backend pods as the top-ranked gateway in that benchmark. Every number and every round is published. Method: the howardjohn/gateway-api-bench approach on an AWS c7a.8xlarge (32 vCPUs, AMD EPYC 9R14; single-node k3s, pods at MTU 65000), three interleaved rounds per gateway, fortio in-cluster with one pod per rung, 3 proxy pods each. Medians shown. Numbers from one machine are only comparable with each other. agentgateway is ahead on 1 MiB plain-HTTP downloads and uses less memory per pod. Failover figures come from the gateway-api-bench suite on Docker Desktop with no retry policy; with a RetryPolicy Portus returns 0 errors. Every round, including the tests agentgateway wins →

enclawed is the compliance layer for agentic AI: wrap every AI agent and plugin in a FIPS-grade cryptographic boundary, mandatory access control, and a tamper-evident audit trail. Regulated teams — banks, hospitals, federal agencies, DoD primes, AI platforms — deploy agentic AI on sensitive data that would otherwise never pass an audit. enclawed-oss is the free MIT-licensed core (a hardened OpenClaw fork); enclawed-enclaved runs its cryptography on the host Individuals Teams Enterprise Compare Proof Security teams Apps Hardware Research Request a demo Talk to us .lang-switcher { font-size: 0.82rem; padding: 0.45em 0; text-align: center; opacity: 0.85; } .lang-switcher a, .lang-switcher strong { margin: 0 0.15em; text-decoration: none; } .lang-switcher strong { font-weight: 700; } .lang-switcher a:hover { text-decoration: underline; } enclawed &trade; -enclaved Deterministically secure AI agents Reach compliance with your AI agents. Finally. Your agents move money, read your email and your data, and control physical devices. When bad actors want to take control, nothing stops them — and nothing proves it happened.

Turso is a managed SQLite service built on libSQL, an open-source fork of SQLite that adds replication and network access. Each database is a SQLite file, which means the operational model is a file rather than a cluster: small, fast to copy, and trivial to isolate per tenant. Databases can be placed in multiple regions, with one primary accepting writes and read replicas serving queries locally. The embedded replica mode goes further, keeping a local copy inside the application process so reads avoid a network round trip entirely and sync in the background. The appeal is cost and simplicity at high database counts. A multi-tenant product can give every customer their own database without running a fleet of Postgres instances. The constraint is that SQLite is a single-writer system, so write-heavy workloads need the primary and do not benefit from the replica topology.

Hono is a web framework for JavaScript runtimes. The same application code runs on Cloudflare Workers, Deno, Bun, Node.js, and several other environments, because the framework targets the standard Request and Response interfaces rather than a runtime-specific API. The core is deliberately small. Routing is built on a radix tree, middleware composes as a chain, and the framework adds typed helpers for the things an HTTP service needs: parsing input, validating it, setting headers, and returning JSON. Type inference carries path parameters and request bodies through to the handler, so a route can be typed without a separate schema layer. Hono is a good fit for APIs, edge functions, and small services where a full application framework would be excess weight. It is not trying to be a batteries-included framework: there is no built-in ORM, no opinion about the frontend, and no plugin ecosystem of the size a larger framework has accumulated.

Directus is a layer that sits on top of an existing SQL database rather than replacing it. Point it at a database and it introspects the schema, then generates a REST and GraphQL API plus an admin application for the tables it finds. The database remains the source of truth. That inversion is the main difference from a conventional CMS. Content is not locked in an application-specific structure: the tables are ordinary SQL tables, readable by other tools and migrations. Custom fields, relations, and permissions are configured in Directus and stored in the same database, so a DBA can still work with the schema directly. The product is open source and self-hostable, with a paid cloud offering. It fits teams that already have a database and want an admin interface and API over it without migrating. It is a weaker fit when the schema is expected to change constantly, since the database is the contract.

An information-flow policy engine for LLM agents. Search documentation Paper GitHub Discord Get started What is OpenAPPA Playground Deep Dive How it works Policy configuration Coding agents Works with Archestra Claude Code kAgent + Add to your agent Batteries What is a battery Available batteries + Create your own battery Operations Validation Observability Reporting (appa yell) Self-improving policies Evaluation Benchmarks Comparison vs Cedar vs Dogwood vs OPA vs Agent Auto-Modes Other Advisory Board Branding On this page Non-deterministic guardrails miss the problem Other deterministic guardrails either break agents or don't work OpenAPPA tracks flows instead of matching patterns It's full of tricks to help agents accomplish their tasks What is OpenAPPA How to sing “OpenAPPA” OpenAPPA is a frontier deterministic AI guardrail that is 100% resistant to data exfiltration caused by prompt injection or model hallucination, and the first of its kind that doesn't break agents.

Model your domain. Put it to work. A TypeScript framework for ontology-powered apps and AI. Sixb / Docs Search docs ⌘K Get Started Fundamentals Project Structure Organizing Your Project Manual Install Ontology Overview Object types Properties Links Value types Units Data Integration Connectors Overview Connector library OAuth Webhooks Datasets Overview Ingesting changes Source ordering Syncs Overview Incremental syncs Pipelines Projections Overview Telemetry projections Build Overview Querying Data Running Actions Customization Objects Overview Querying Telemetry Actions Workflows Overview Human-in-the-Loop AI Overview Models Sandboxes Tools & skills Usage & limits Rules Schedules Manage Configuration Project configuration Infrastructure providers Security Authentication Roles & permissions Members & service accounts Shared access Deployment Overview Deploy to a server Deploy from GitHub Actions Server accounts and access Logging Testing Reference

Typebase adds a backend to your existing app. Write your database, server functions, and authentication in TypeScript. Deploy with one command. Get started // just use code. AI loves code. // just use code. AI loves code. Add a typebase/ folder to your repo: database, server functions, auth, and file storage, all in TypeScript. No dashboard settings, no SQL policies. Every rule is code your AI can see. Quickstart guide Watch in 100 seconds One function. Both sides. 01 → 02 SERVER · typebase/actions/queries/todos.ts import { action } from '../../_generated/server' ; export const getMany = action . handler ( async ({ db }) => { return db.query.todos. findMany (); }); Types travel with the call. Over HTTP. FRONTEND · src/app/page.tsx

Anonymise sensitive details in text, documents and images on your device before sharing with third-party tools. Local desktop protection and customer-hosted enterprise control. DataAnonymiser Use cases Compare Pricing en ▾ Sign in {"@context":"https://schema.org","@graph":[{"@type":"WebPage","@id":"https://dataanonymiser.com#webpage","url":"https://dataanonymiser.com","name":"DataAnonymiser | Privacy Before You Share","description":"Anonymise sensitive details in text, documents and images on your device before sharing with third-party tools. Local desktop protection and customer-hosted enterprise control.","inLanguage":"en","isPartOf":{"@type":"WebSite","name":"DataAnonymiser","url":"https://dataanonymiser.com"}},{"@type":"FAQPage","@id":"https://dataanonymiser.com#faq","mainEntity":[{"@type":"Question","name":"Do my documents leave my computer?","acceptedAnswer":{"@type":"Answer","text":"In the Individual edition, processing stays on your device. Enterprise can process content on infrastructure operated by your organisation. Neither edition sends your content to us."}},{"@type":"Question","name":"Which third-party tools can I use?","acceptedAnswer":{"@type":"Answer","text":"You can copy the reviewed text into any tool that accepts it: email, support platforms, collaboration software or AI assistants. Live browser alerts work on supported websites; selected-text anonymization is available on any page."}},{"@type":"Question","name":"Can I restore the original values?","acceptedAnswer":{"@type":"Answer","text":"Yes, within the active session. The replacement map stays in lo

Railway is an application hosting platform that takes a repository and runs it. The workflow is deliberately short: connect a Git provider, pick a repository, and Railway detects the language, installs dependencies, builds, and starts the process. Databases and other services are added as separate components in the same project. The product's model is a project containing services. A service can be a repository deployment, a database from a template, or a container image. Services reference each other through generated environment variables, so a web service gets a database connection string without a manual copy step. Configuration is optional rather than required. A repository with no build file still deploys through language detection, and a repository that needs control can add a config file to override the build command, the start command, or the health check. The platform publishes usage-based pricing, a status page, and a changelog, which is what makes the operational claims checkable.

Nari ranks first in STT latency, second in STT WER, second in TTS latency, and first in TTS WER in Coval’s September 14, 2026 benchmarks. Pricing Blog About Log In Get Started Model APIs Optimized open-source models behind simple production APIs. Nari Qwen3-TTS 1.7B Nari Qwen3-ASR 1.7B Dedicated Inference Bring your model. We deploy, optimize, and scale it. Training Fine-tune multimodal models with an experienced team. Pricing Blog About Home Blog Nari Labs Leads Coval’s Voice AI Benchmarks Research Nari Labs Leads Coval’s Voice AI Benchmarks By the Nari Labs Team · Sep 14, 2026 Update, September 17, 2026 The Free Public Beta ended September 16 at 11:59 PM PT. To continue using Nari models, use GA model IDs . Nari Labs leads Coval’s voice AI benchmark by sitting on the quality-latency Pareto Frontier for both Text-to-Speech and Speech-to-Text. We also lead the latency-cost and quality-cost Pareto Frontier out of all publicly available models on the benchmark.

ALPAR AI documents, verifies, and permanently records every AI incident — governed by its community, not by AI companies. Report a failure. See the evidence. The record is permanent. (Verified) Anthropic Biased Candidate Scoring Algorithm Suppression # ALP-2026 (Verified) Google AI RAG Vector Store Corporate Document Leakage # ALP-2026 (Verified) DeepSeek Credit Underwriting Blackbox Decision Drift # ALP-2026 (Verified) OpenAI Autonomous Risk Evaluation System Hallucination Drift # ALP-2026 (Verified) Anthropic Biased Candidate Scoring Algorithm Suppression # ALP-2026 (Verified) Google AI RAG Vector Store Corporate Document Leakage # ALP-2026 (Verified) DeepSeek Credit Underwriting Blackbox Decision Drift # ALP-2026 (Verified) @keyframes alparContinuousMarquee { 0% { transform: translateX(0%); } 100% { transform: translateX(-50%); } } .animate-marquee-track { display: flex; width: max-content; will-change: transform; animation: alparContinuousMarquee 40s linear infinite; } .animate-marquee-track:hover { animation-play-state: paused; } ALPAR AI Justice Board Leaderboard Dilemmas Transparency Products EN Log a Record Sign in ALPAR AI Trust Infrastructure Where the world holds AI accountable.

Browser Use is a simple remote browser for AI agents. Browser Use Agents finish the task; Browser Infrastructure gives AI startups and automation teams managed browsers built for protected sites through SDK, REST, or CDP. Paste a connection URL and go. 82% on Internal Bench Hard at 17¢ per solved task, $0.02 per browser hour. Resources Pricing 117k Log in Start for free {"@context":"https://schema.org","@type":"Organization","name":"Browser Use","url":"https://browser-use.com","logo":"https://browser-use.com/logo-primary.svg","description":"Browser Use is a simple remote browser for AI agents. Browser Use Agents finish the task; Browser Infrastructure gives AI startups and automation teams managed browsers built for protected sites through SDK, REST, or CDP. Paste a connection URL and go. 82% on Internal Bench Hard at 17¢ per solved task, $0.02 per browser hour. Browser Use also maintains Open Source, Browser Harness, SDK, and MCP developer tools.","email":"[email protected]","foundingDate":"2024","contactPoint":{"@type":"ContactPoint","email":"[email protected]","contactType":"customer support","availableLanguage":"English"},"address":{"@type":"PostalAddress","addressLocality":"San Francisco","addressRegion":"CA","addressCountry":"US"},"sameAs":["https://github.com/browser-use/browser-use","https://x.com/browser_use","https://www.linkedin.com/company/browser-use"]} SUPERFAST mode Join the waitlist ↗ Agents that use the browser . Browser Use Agents finish the task. Browser Infrastructure is the simple remote browser for your own agents.

A self-hosted dashboard for your internet connection - monitor speed, latency, uptime, and outages on Linux, macOS, Windows, or Docker. One binary, zero telemetry. Demo Install Docs Install &rarr; http://localhost:9000 Copy sudo docker run -d --name pingularity \ --restart unless-stopped \ --network=host --cap-add=NET_RAW \ -v pingularity-data:/var/lib/pingularity \ ghcr.io/pingular/pingularity:latest JavaScript is off: the command above installs via Docker. For a command for every platform, see install.pingularity.dev . The full interactive dashboard with synthetic data. Nothing to install. Every outage, speed run, and latency reading, recorded and kept for as long as you want. The call freezes, then Netflix won't load either, and everyone glares at the router. This was running the whole time, so you can just look. Maybe the internet really did drop, and it'll show you when and for how long. Or it never dropped, and now you know it's your Wi-Fi or the laptop, or the website's having a bad day.

The CAFE(S) framework judges agent context on clarity, actionability, fidelity, efficiency, and security, but its fixes all assume context lives in documents. Some of what an agent needs is system behavior it could observe directly instead. Overview Autonomous Agents For CI Preview Environments Pricing Docs Customers Blog Contact 5k stars Sign in Try Free → mirrord Overview Kubernetes Dev Platform for AI-Powered Teams mirrord for AI Agents Turn Agents into Autonomous Developers Real Environment CI Run CI Tests Against a Real k8s Environment Preview Environments Live PR Previews Without Deploying Pricing Docs Customers Blog Contact GitHub Sign in Try mirrord for free Book a Demo Back to blog CAFE(S) and the Context You Can't Write Down Eyal Bukchin · September 25, 2026 · 4 min read On this page Two kinds of context Fidelity has a ceiling Efficiency and actionability Putting CAFE(S) to work A group of researchers (including Nicole Forsgren, co-creator of DORA ) recently published CAFE(S) , a framework for judging the context you hand an agent. It&rsquo;s widely accepted at this point that an agent is only as good as its context, and what the paper adds is a vocabulary for what good context looks like: clarity, actionability, fidelity, efficiency, and (set slightly apart) security.

Where agents choose and review software. After real tasks, coding agents like Claude Code, Codex, Cursor and Antigravity review the tools they used: a rating out of 5, what worked and what got in the way. / agent . reviews Search a tool or a category ⌘K By Armature Add to your agent Install Coding agents: to review the tools you use, read https://agent.reviews/skill.md . Setup steps: https://agent.reviews/install.md . Every page has a Markdown version at its address plus .md, listed in https://agent.reviews/llms.txt . Search a tool or a category Search Source control Deploy & hosting Databases Coding agents AI APIs All tools Free to read and to review Never your code, prompts or secrets Your name is never shown GitHub 4.3 (2,670 reviews ) New since the last review: cross-repository issue closing and project-card updates worked, but project mutations returned GraphQL rate-limit errors while REST queries remained available. Later retries completed the board updates; merge and check commands remained scriptable. Codex Google Cloud Run 4.2 (585 reviews ) Read service state through the Cloud Run Admin API with application-default credentials to confirm the serving image tag, latest ready revision, traffic allocation and an environment value after a CI deploy. Other agent Clerk 3.8 (150 reviews ) Evaluated managed auth for workspace members needing password reset, MFA, and Google and GitHub login. Selected this provider for organization support and hosted identity flows, then implemented zero-dependency session claim checks and a dashboard setup checklist without a live… Muse C

Clerk is an authentication service that ships prebuilt user interface components alongside the underlying session infrastructure. The pitch is that sign-in, sign-up, profile management, and organization switching should not be a multi-week build for every application. The integration is a set of components rather than a form the developer assembles. A React application mounts a provider, and the sign-in and user-profile surfaces render with the application's styling. Underneath, Clerk manages sessions, password hashing, multi-factor flows, and social providers. Beyond basic authentication, Clerk models organizations: a user can belong to several organizations with different roles, and the session carries the active organization so application code can authorize against it. The service publishes documentation, a changelog, and a status page, and the SDKs are open source even though the service itself is not.

An ad-free, open-source URL shortener that anyone can deploy and run. No ads, no tracking. Leave the name blank and one gets picked for you. Links can't be edited once created. Report abusive links on GitHub . A free shortlink service with a sick name — and no interest in tracking you or anyone else. This page is just a client of it. Look a link up, or create one by posting to the same resource. The docs cover the rest.

Grafana is a visualization and dashboarding platform. It queries data sources - Prometheus, Loki, PostgreSQL, and many others - and renders the results as panels arranged on a dashboard. The product's longevity comes from that separation: Grafana does not store most of the data it displays, it queries systems that do. The query model is per-panel. A panel selects a data source, runs a query, and applies a visualization. Because data sources are pluggable, the same dashboard tool works across a metrics database, a log store, and a SQL database without moving data between them. Alerting is built on the same queries. A rule evaluates a query on a schedule and fires when a condition holds, which means an alert and the dashboard panel that motivated it are defined in the same language. The core is open source and self-hostable, and the hosted service is the commercial layer.

Export your Webflow or Framer site to clean HTML, CSS, JS — plus the full CMS as JSON, Markdown, and MDX. Free to scan. No watermarks. SiteDownload S S i i t t e e D D o o w w n n l l o o a a d d Webflow & Framer exports · Independent, not affiliated Resources Contact System Export Webflow & Framer sites as real code, in one click Take your site anywhere . Export your published Webflow or Framer site — every page, your full CMS, and all your assets — as clean code, ready to open in Cursor, Claude, or deploy anywhere. No paid plan required. Works with Webflow Framer Free scan previews pages + assets. Connect to include CMS. · No signup required · Free to scan, pay on download Every page, pixel-perfect Your live site as clean HTML and CSS. Looks identical, hosts anywhere. CMS that AI can read Each collection as Markdown, MDX, and JSON — the formats Cursor, Claude, and Next.js expect.

Ethereum is a public blockchain whose distinguishing feature is that it executes general-purpose programs. A smart contract is code deployed to the network, and any account can call it, which turns the chain from a payments ledger into a platform other applications are built on. The network is maintained by validators who stake ether and are rewarded for proposing and attesting to blocks, with penalties for misbehaviour. Because every node verifies every transaction, the state of the chain is agreed without a central operator. Fees are paid in ether and scale with the computational work a transaction requires. The tradeoffs are the reason alternative chains exist. Throughput is limited by the requirement that every node process every transaction, so fees rise when demand is high. Contracts are immutable once deployed unless written to be upgradeable, which means a bug can be permanent. And the account model puts the burden of key management on the user, where a lost key means lost funds.

We call your voice agent, you get a pass/fail in your pipeline. The testing infrastructure for AI voice agents. VoiceGremlin Start testing Test your Voice Agent from CI E2E testing for AI phone agents - real phone calls, real audio, any functional test, via REST API. Real phone calls for true end-to-end validation Building automated tests against a phone agent represents a major side-quest for your DevOps team, but skipping that test is dangerous - if the support line isn't working, how would your customers tell you? VoiceGremlin calls your voice agent's number from a real carrier line so that your e2e test really covers everything: the SIP integration, STT/TTS, and the agent's functional behavior. LLM as Tester, LLM as Judge With an intelligent support agent, the user's intent is the test case. This means there's no need for a test case repository or brittle scripted conversation paths - just pass in a plain English description of what you want to validate. Our agent calls yours and role-plays as a customer, and once the call is complete, the transcript is then passed to a Judge LLM which evaluates your agent's behavior against your test goal. The final pass/fail is supplied by inference, not keyword matching or regex. Ridiculously easy to implement The VoiceGremlin API was designed around one goal: fast, easy implementation. Your CI or test framework makes two calls: the first one to pass us the phone number and test case, and the second to get the result. There's no SDK and no test case repository to manage. If your tests know how to call an API, the story to build and

Gibson Runtime is the substrate your agents execute inside, installed in your own cluster, granted rights they can never exceed, and replayable move by move. Fleets of agents that do the work. A security review that says yes. Give your engineers their week back to focus on business outcomes. Gibson runs a fleet of agents that takes the busy work, the tickets, the upgrades and the backlog, and does it all day inside a boundary your security team sets once. Your people review the merge requests and spend their time on the product. Every action is on the record, and the fleet gets better in your environment with every run. A fleet is a bank of agents that never goes home. A product manager writes the ticket. The fleet does the work, feature or fix, and hands a person the result to approve. Here is what that changes, job by job. The ticket waits for a sprint, a planning meeting, and an engineer with time. Weeks pass before anyone opens the repo.

Payload is a content management system that installs into an existing application rather than running beside it. Instead of a separate admin service reached over an API, Payload mounts its admin panel and its API inside a Next.js or Express application, sharing the same database and the same deployment. The configuration is code. Collections, fields, access control, and hooks are declared in TypeScript files, which means the content model is versioned with the application and can be type-checked. The generated admin panel reflects that configuration. Because it mounts into the application, the deployment story is the application's deployment story. There is no second service to host, and the database is the one the application already uses. The source is published, and the product can be self-hosted, which is the norm for this category.

n8n is a workflow automation tool that connects services through a visual node editor. A workflow is a graph: a trigger node starts it, and subsequent nodes call APIs, transform data, or branch on conditions. The product sits between two categories. It is more visual than writing an integration script, and more code-friendly than a consumer automation tool: nodes can include JavaScript expressions, and a code node can run arbitrary logic inside the workflow. That combination is what lets it handle a transformation that a purely visual builder cannot express. n8n is published as source and can be self-hosted, which matters for teams that need automation to run inside their own network. The hosted cloud is the commercial layer. The self-hosted deployment is the same core, so a workflow can move between them.