Startup
Runloop
Devbox sandboxes and agent infrastructure for AI coding agents.
Runloop Devboxes are VM-isolated sandboxes where AI agents build, run and test code, starting in seconds and supporting snapshot, suspend and resume for long-running work. Blueprints define team-shared images; network policies restrict egress, while Agent Gateways and an MCP Hub connect agents to LLM APIs and MCP servers without exposing real credentials. The platform also lists measurement for evaluating agent performance, multi-agent coordination, Reflex debugging/observability and VPC deployment on AWS, GCP or Azure, with Python and TypeScript SDKs and a CLI.
Neighbours in the directory
San Francisco, CA · Est. 2022
The de-facto standard toolkit for building LLM applications and agents.
LangChain makes the LangChain framework and LangGraph, the low-level orchestration standard for stateful, controllable agents, plus the LangSmith platform for tracing, evaluating and monitoring them in production.
~$75M raised
Prague, Czechia · Est. 2023
Open-source sandboxes for running AI-generated code.
E2B gives agents secure, isolated cloud micro-VMs to execute code and commands — the execution runtime layer of the harness, used by many coding and data-analysis agents.
Est. 2023
Elastic sandboxes for running AI-generated code.
Daytona provides secure, OCI-compatible sandbox 'computers' that spin up in under 90ms — with snapshots for persistent agent state. In 2026 it moved core development to a private codebase while continuing to run as a commercial platform.
Connections
Relations from the Harness Hub knowledge graph, as charted in the State of Harness reports.
Built on · 1
- Model Context ProtocolProject
Sources
Verified Oct 29, 2026