Greene Comply
Control layer for agent spending
Greene Comply launched on May 12, 2026 with 3 votes, #3,449 of 20,538 launches that month and more than 50% of that year's launches.
What it does
The authorization, trust, and audit control plane for agent-initiated spend. Set policy, hold risky spends for review, ship webhooks and team RBAC—prove every decision.
Circle ships the rails; Greene Comply decides what agents are allowed to spend, holds what needs a human, and proves what happened. Guard rails, audit, ledger, MCP, and USDC settlement via Vesper. Non-custodial. Start free.
Greene Comply is the authorization, trust, and audit layer for agent spend. Circle ships the rails; we decide what’s allowed, hold what needs a human, and prove what happened — over MCP or the REST API. We never hold your funds. Demo data — real authorizations, denials & USDC settlement (testnet) live in your account. If your agent spends money and something goes wrong, can you prove a human was in the loop? Most teams can't. One bad prompt and an agent burns through a budget in minutes. By the time your alert fires, the damage is done. Agents transacting with no live feed and no denials. When something looks off, you find out hours later — in a log file. When auditors ask for proof of…from greenecomply.com
Does a similar job
all alternatives →


BOSAI Control PlaneJul 2026 · bosai.syncguard.fr · ▲3Govern AI agents with approval gates and audit trails

More ai this month
the category →



Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 29d ago · world.pixverse.video

Source: Product Hunt launch ↗
Launched alongside, May 2026
the whole month →

Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai



Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com

🌱 Private, quiet space for thinking. Simple app for .md files. - zakirullin/files.md
Dev tools · May 2026 · github.com