AI-native Postgres observability: 45+ automated health checks, query and config tuning, agent-ready JSON and MCP output. Open source.
Results for “ai-agents”
61 tools found
AI eval and observability platform: tracing, LLM and human scoring, quality gates. Used by Vercel, Notion and Replit.
Python framework for role-based multi-agent teams: Crews plus event-driven Flows, from MIT open source to enterprise suite.
TypeScript framework for AI agents and workflows: typed tools, graph orchestration, memory, RAG and 90+ model providers.
AI-powered security platform combining automated pentesting, code review and cloud vulnerability scanning to find and fix exploitable issues before attackers do.
Feature flag and release management platform letting teams turn features on or off in production instantly, without redeploying code.
Sandboxed cloud execution infrastructure for AI agents to safely run code in under 90ms, across Python, TypeScript, Go, Ruby and Java.
Gives AI coding agents disposable cloud Linux environments to actually run and test the code they write, capturing screenshots and recordings as proof instead of just claiming "done".
Internal developer portal that gives engineering teams a self-service software catalog, golden-path automation, and scorecards, positioned as faster to stand up than Backstage.
Testing environment that gives AI agents realistic, stateful clones of GitHub, Slack, Stripe and other SaaS tools so bugs get caught before production.
Cloud infrastructure for running autonomous AI agents at scale, with millisecond sandbox startup and near-zero idle cost.
Cloud infrastructure of real, headless browsers that AI agents can control to browse, click and fill out forms like a human would.
Secure, disposable cloud sandboxes that let AI agents safely execute generated code without touching real production systems.
Web scraping and crawling API that turns entire websites into clean, structured data ready for AI models to read.
Gives AI agents their own email address, phone number and iMessage identity, so they can send, receive and act on real-world communication.
AI DevOps agent that watches your CI/CD pipeline, investigates failures, reviews code and triages incidents around the clock.
API that instantly merges AI-generated code edits into your actual files, so coding agents can make changes without rewriting whole files.
Open-source gateway that lets AI agents call APIs without ever seeing your real API keys — real secrets are injected transparently at the network level.
AI-native observability platform that lets engineers debug production issues by asking questions in plain language instead of digging through logs.
Real-time voice AI models built for near-instant, natural-sounding speech — the audio layer behind voice agents that need to feel like a real conversation.