The rows worth reading.
Galileo is an evaluation and observability platform: it scores agent and RAG outputs against metrics like hallucination and groundedness, and its Protect product can guard against some known-bad output patterns in real time. What it doesn't do is turn a caught failure into a backtested, enforced rule, or hold a risky action for human approval. Zespan is built around that closed loop — detect the failure, test the fix against real traffic, enforce it in-process, and turn every decision into an auditable record — with Galileo-style evaluation as one part of the detection layer, not the whole product.
| Zespan | Galileo | |
|---|---|---|
| Evaluates agent/RAG output quality | 12 built-in judge templates | Core feature |
| Turns a failure into an enforced rule | One action from a flagged trace | Not available |
| Backtests a rule on your own past traffic first | Catch rate + false-positive rate | Not available |
| In-process enforcement, no proxy hop | SDK evaluates locally | Proxy-based (Protect) |
| Approval holds for risky actions | Named reviewer, recorded decision | Not available |
| Audit trail mapped to compliance controls | Actor-attributed, SOC 2-mapped | Not available |
| Multi-agent delegation graph | Partial | |
| Closed-loop fix proposal, replayed against captures | Not available | |
| Starting price | $29/month | Contact for pricing |
| Free tier | 50K traces/month | Contact for pricing |
Which one fits
Pick Zespan when
You need a failure you've already caught to become an enforced, tested rule — not just a lower score on a dashboard.
You want to backtest a guardrail against your own history before it can block a real customer.
Your agents include real-time or voice use cases where a proxy hop's added latency isn't acceptable.
You need approval holds and an audit trail for actions with real financial or compliance consequences.
You want transparent, self-serve pricing starting at $29/month rather than a sales-led quote.
Pick Galileo when
Your primary need is deep evaluation metrics and scoring research, independent of enforcement.
You're earlier in your agent's lifecycle and evaluation, not enforcement, is the current priority.
You have existing Galileo infrastructure and evaluation workflows already built around it.
Common questions
Does Zespan score agent output quality like Galileo does?
Yes. Zespan runs 12 built-in LLM-as-judge and rule-based evaluators automatically on every trace. The difference is what happens after a low score: in Zespan, a flagged trace can become a backtested, enforced guardrail in one action, not just a metric on a dashboard.
What does 'closing the loop' mean compared to Galileo?
Galileo's core workflow is detect and score. Zespan's is detect, turn the failure into a policy rule, test that rule against your own past traffic, enforce it in-process on every future request, and — when a fix is proposed — replay it against the exact failures that caused the incident before a human approves it.
Is Galileo Protect the same as Zespan's guardrails?
Both aim to stop a bad output before it reaches a user. The difference is architecture and scope: Zespan's rules are evaluated in-process inside your own service with no proxy hop, cover business-logic violations specific to your policy (not just known-bad content categories), and are required to pass a backtest against real traffic before they're allowed to enforce anything.