Building in public · Join the waitlist

Agents that actually run in production.

The production runtime for AI agents. Deploy, monitor, and iterate on agent workflows that work at scale — with full observability, intelligent retries, and zero infra reinvention. Built for engineers who ship.

Request early access

⬡ You're on the list. We'll reach out before public launch.

No spam. First access notification only.

—

On waitlist

Beta
Soon

Status

Free

Early access

What's in the runtime

Key differentiator

Velorith supports multi-provider fallback chains — if Claude fails, fall to GPT-4o. If that fails, fall to Gemini. Your agent never goes down because of a single provider outage.

01

Agent execution engine

Define in config. Velorith runs it reliably at any scale — no boilerplate.
02

Multi-provider fallback chains

Claude → GPT-4o → Gemini. Automatic failover across providers. No single point of failure, ever.
03

Step-level trace observability

Every LLM call, tool use, cost — captured and queryable. Full visibility.
04

Intelligent retry engine

Retry with exponential backoff. Agents survive timeouts and rate limits silently.
05

Webhook + cron triggers

Run on events or schedules. No custom scheduler infra needed.
06

Cost + ops dashboard

Real-time status, spend per agent per day, full trace drill-down.

velorith.config.yaml Live preview

name: "sales-research-agent"
model: "claude-opus-4-5"
fallback: "gpt-4o-2024-11-20"
fallback_2: "gemini-2.5-pro"
max_retries: 3 | trigger: "webhook"
trace_steps: true | cost_tracking: true

$ velorith deploy sales-research-agent
✓ Runtime active · Traces streaming
✓ Fallback chain armed · 3 retries configured

The problem we're solving

🔦

Critical

Zero observability

Agents fail mid-run. Nobody knows at which step, why, or what it cost.

💥

Critical

Reliability theater

Works in dev, dies in production. One timeout kills the entire workflow.

💸

High

Cost blindness

Surprise $10K LLM bills. No attribution per agent or job.

🔁

High

Perpetual reinvention

Every team rebuilds executor, queue, logger. Sprint after sprint wasted.

How it works

Define

Describe your agent in a config file — model, tools, retry policy, trigger, and observability settings.

Deploy

One command. Velorith handles the runtime, queueing, scaling, and execution layer entirely.

Monitor

Full step-level traces, cost per run, failure alerts, and rollback — live in your dashboard.