The Galileo alternative
that doesn't need a sales call
Galileo is great for enterprise hallucination detection in NLP pipelines. For AI engineers who need deterministic PR gates without a procurement cycle, Refine AI is self-serve and ships in 5 minutes.
At a glance
Why teams choose Refine AI over Galileo
Galileo solves a real problem for enterprise NLP teams. These are the gaps when the problem is agent CI enforcement.
Hallucination detection ≠ agent regression detection
Galileo excels at detecting hallucinations in single LLM calls. Agent regressions are structural — your agent suddenly takes 4× more steps, calls a deprecated tool, or enters a retry loop. These aren't hallucinations; they're behavioral changes that hallucination scores won't surface.
LLM judges have a confidence problem
Galileo uses an LLM judge to score outputs. A 92% reliability score is useful for analytics but not for a CI gate — where do you set the threshold? Refine AI returns PASS or FAIL. No ambiguity, no threshold calibration, no judge drift to worry about.
Enterprise procurement for a developer workflow
Getting started with Galileo requires a sales demo and enterprise pricing negotiation. For an AI engineer who wants to add behavioral regression testing to a GitHub Actions workflow this afternoon, the sales cycle is a hard blocker. Refine AI is self-serve: install the Action, define thresholds, done.
How Refine AI is different
Structural, not probabilistic
step_count either exceeded the threshold or it didn't. No confidence scores, no ambiguous grades.
Self-serve in minutes
No demo, no sales call, no enterprise onboarding. Free to start and self-configuring via YAML.
CI-native design
Built around the GitHub PR workflow. The output is a check status, not a dashboard.
Agent-native failure surface
Catches step explosions, tool call regressions, loop risk — failure modes agents actually have.
Who each tool is built for
Use Galileo if…
- →You're in a regulated enterprise focused on hallucination reduction
- →You need a compliance story around LLM reliability scoring
- →You have budget and timeline for enterprise procurement
Use Refine AI if…
- →You want fast, self-serve CI enforcement without a sales cycle
- →You're focused on structural agent behavior, not hallucination scoring
- →You need deterministic PASS/FAIL gates, not confidence percentages
Get started in 5 minutes
No sales call. Just add the GitHub Action.
- name: Assert agent behavior
uses: agentdbg/agentdbg-action@v1
with:
baseline: main
checks: step_count,tool_calls,loop_risk,cost,latencyPASS or FAIL. No ambiguity.
Deterministic CI gates for agents. No enterprise procurement, no confidence scores — just automatic PR enforcement.
Add to GitHub Actions