Ordinate: Multi-Agent Safety Orchestrator

Riga, Latvia

A control system that makes running AI agents feel safe, not scary.

Project Details

Ordinate is an open-source system for multi-agent AI development. As AI agents become more autonomous and teams start running multiple agents in parallel, we're seeing a new category of risks and challenges occur.

Ordinate adds a safety middleware layer between developers and their AI agents. It provides sandboxed execution, file-level locking, real-time budget caps, heartbeat monitoring with automatic kill for stuck agents, human-in-the-loop validation and git backups. Think of it as Kubernetes for AI agents with safety as a first-class primitive.

My goal is to make Ordinate a step toward more reliable, safe, and comfortable multi-agent systems.

The project will be released under MIT license. Any team will be able to audit the safety mechanisms and contribute improvements.

Theory of Impact

The biggest bottleneck in AI agent adoption is not capability - it's trust. Developers try agents, get burned by an uncontrolled incident, and walk away. Ordinate solves this by making work with AI agents safe, reversible and predictable by default.

When you set up an agent in Ordinate, you don't add safety as an afterthought - you configure it as part of the agent's identity: damage control level, file permissions, budget cap, validation workflow. The dashboard shows you exactly what every agent is doing, in real time. This transforms the developer's relationship with AI agents from "hope nothing breaks" to "I can see everything and I'm in control."

I see the impact as two-sided:

Safety side: every agent running under Ordinate is sandboxed, budget-capped, and monitored. Incidents are prevented, not reacted to.

Adoption side: developers who were burned out will have a reason to try again. Teams that were hesitant to run multiple agents will have a control plane. The total number of agent-hours under safe orchestration grows and with it, the productivity gains of AI-assisted work reach more teams.

People

Sergey Zaharenko

Team Member

Funding Details

Start Date: Feb 27, 2026
End Date: -
Expected Duration: 3-4 months for stable open-source
Funding Raised to Date: -
Annual Budget: -
Monthly Burn Rate: -
Current Runway: -
Funding Goal: -
Funding Stage: seeking first grant
Fiscal Sponsor: -

Grants Received– no grants recorded

Add grant

Funding Asks

grantmaking.ai Launch Round

Applied

Minimum

$5,000

Ideal

$10,000

What this ask is

My goal is to make Ordinate a step toward more reliable, safe, and comfortable multi-agent systems.

The project will be released under MIT license. Any team will be able to audit the safety mechanisms and contribute improvements.

How the money will be spent

Mostly it'll go on development, debugging and API costs.

In case of minimal funding 700-1000$ will be spent on marketing through social media reviews and articles.

In case of ideal funding i'll be able to spend up to 3000$ on gaining traction on the project online.

Discussion

No comments yet. Be the first to share your thoughts.