OpenAI Agents API
The Agents API lets developers build and run cloud agents with the same harness and infrastructure that powers Codex, fully managed by OpenAI. A production-ready agent can be created with a single API call by specifying the task, model, tools, and environment, while OpenAI hosts and maintains the agent harness. Developers can choose where agents run: in an OpenAI-hosted sandbox, on their own infrastructure, or through supported sandbox partners. OpenAI-hosted sandboxes provide secure environments where agents can run code, work with files, use packages, skills, and plugins, and produce artifacts. The API is designed for long-running work, with automatic context compaction that preserves relevant information as sessions span multiple context windows. Tool search loads relevant tool definitions only when needed, while programmatic tool calling lets agents run calls in parallel, chain related operations, and filter or combine results in code.
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Contextually
Contextually is an enterprise AI platform designed to help organizations build and deploy production-ready AI agents that can reason over complex, domain-specific data using advanced context engineering. It provides a unified context layer that connects AI models to large volumes of enterprise knowledge, including documents, databases, and multimodal data, enabling agents to deliver accurate, grounded, and relevant outputs. It allows users to define and configure agents quickly through prebuilt templates, natural language prompts, or a visual drag-and-drop interface, supporting both dynamic agents and structured workflows tailored to specific use cases. It includes tools for ingesting and processing massive datasets from multiple sources, transforming unstructured and structured information into retrievable knowledge with intelligent parsing, metadata generation, and continuous updates.
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TinyFish
TinyFish is the web operating layer for AI agents, providing the infrastructure agents need to reliably access and operate across the live web. As AI applications evolve beyond text generation into autonomous systems that gather information, navigate websites, and complete multi-step tasks, fragmented automation stacks and custom-built infrastructure become difficult to maintain.
TinyFish unifies web search, content extraction, browser infrastructure, and agentic web interaction within a single platform. Agents can search the live web, extract clean LLM-ready content from modern websites, render JavaScript-heavy pages, and execute authenticated workflows without stitching together multiple vendors or maintaining custom infrastructure.
Built for production AI systems, TinyFish emphasizes accuracy, efficiency, freshness, and scalability. By providing clean web context and dependable execution across dynamic web environments, the platform helps developers build AI applications that
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StateFabric
StateFabric a small infrastructure layer for AI agents that need more context than chat history.
Once an agent starts using tools, running for longer sessions between restarts, ‘keep the messages in memory’ doesn’t really cut it. You need to know:
- what happened?
- what state changed?
- which tools were called?
- what context should go into the next model turn?
StateFabric stores an append-only event log for agent runs, then derives working context from it.
Today it supports:
- Durable sessions and event storage
- User/model/tool event timelines
- Reconstructed session state from stored events
- Compacted model-facing context
- A dashboard for inspecting sessions, raw payloads, compaction artefacts, and usage
- Google ADK integration via @statefabric/adk
- Direct Node/REST usage via @statefabric/client (for custom runtimes)
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