Galileo AI alternatives

Why Teams Look for a Galileo Alternative

Four reasons come up, and weak evaluation is not one of them. Evaluation is the strongest part of Galileo: 20+ built-in evals for RAG, agents, safety and security, agentic metrics such as Tool Selection Quality and Session Success, and CLHF, which tunes a judge from as few as five labelled records.

• The runtime half is on Enterprise. Galileo's pricing page lists real-time guardrails only under Enterprise, and its docs say "Luna-2 is only available in the Enterprise tier". Free and Pro get evaluation, not hosted blocking.
• Protect is deprecated. Galileo deprecated Protect in June 2026 and tells new users to set up Agent Control instead. Anyone built on Protect has a migration to plan either way.
• A new owner and a new name. Cisco completed the acquisition in May 2026, Galileo's technology is going into Splunk Observability, and since 7 August 2026 the product is called Splunk Agent Observability. Some teams want to see where that lands before they commit.
• Sales-led above Free. Only the Free plan has a sign-up button. Pro, despite its listed $100 a month, routes to "Book a Demo", as does Enterprise, where unlimited traces, SSO, VPC or on-prem and the guardrails live.

The Options at a Glance

Seven Alternatives, and Staying Put

Failproof AI: Find Behavioral Failures, Then Enforce the Fix

Failproof AI starts by finding where agent behavior strays from the intended outcome. Code-based and LLM-based evaluations review production sessions, and audits group related failures into findings with evidence, severity and a recommended fix. When the fix is a behavioral rule, Failproof AI generates a policy, backtests it against calls the agents already made, and deploys it in observe mode before enforcement. Policies run at the hook layer of twelve supported harnesses, and the maintained coding-agent pack includes 38 prebuilt policies, with 10 enabled by default. The free tier is self-service, followed by Team at $99 and Scale at $599 a month.

• Limits. Policy enforcement is available in supported harnesses. Agents traced only through the Python SDK are monitored but not directly controlled. Self-hosted Cloud is Enterprise-only.
• Best for. Teams that want to discover behavioral failures and enforce tested policies from the same workflow.

Agent Control: Galileo's Guardrails, Self-Run

If the Enterprise gate on guardrails is why you are looking, the replacement Galileo recommends may be enough. Agent Control is an Apache-2.0 control plane that evaluates LLM and tool inputs and outputs and returns deny, steer, warn, log or allow. It has Python and TypeScript SDKs, framework integrations, built-in deterministic evaluators and model-based plug-ins. You run its server with PostgreSQL, while the managed version is for Enterprise customers. Best for: teams building their own agents that can operate another runtime service.

Future AGI: The Broad Open-Source Platform

Future AGI has an Apache-2.0 core with evaluations, its own Turing models, traceAI tracing, multi-turn simulation including voice, prompt optimization, an OpenAI-compatible gateway and Protect checks for model I/O. Tool Permissions and MCP Security cover tool calls routed through the gateway. Some repository code uses a separate enterprise licence, and self-hosting involves Postgres, ClickHouse, Redis, RabbitMQ and Temporal. Paid add-ons are published at $250, $750 and $2,000 a month. Best for: teams that want Galileo-like breadth with an open-source core and published add-on prices.

Judgment Labs: Judges and Behavior Discovery

Judgment Labs is the closest match to Galileo's evaluation core without the guardrails. Agent Judge follows a natural-language rubric over long trajectories, Code Judge runs Python checks, and Behavior Discovery surfaces failure patterns without an existing judge. The judgeval SDK is Apache-2.0. Monitoring runs after execution, pricing is not published, new users are routed to a demo, and platform self-hosting is listed as coming soon. Best for: teams that want specialist agent judges and are comfortable buying through sales.

Raindrop: Production Signals

Raindrop watches production for silent failures through plain-language Signals, recurring Issues ranked by severity and Experiments that compare cohorts of logged production events. Pro is $299 a month plus per-event pricing, and creating Experiments requires it. Hobby is free up to 1,000 events a month, after which ingestion stops. Alerts go to Slack, it detects rather than blocks, and self-hosting is a partner beta. Best for: products with enough live traffic to learn from production behavior and compare changes across cohorts.

Latitude: MIT from End to End

Latitude traces sessions over OpenTelemetry and evaluates them with rules, an LLM judge or custom JavaScript, with human annotation and an eval-to-human alignment check. Agent Dispatch sends Claude Code or Cursor to propose pull requests from failures. The whole platform is MIT and self-hostable for free, and Pro is $99 a month. It scores after the fact and does not block, while its managed cloud runs in the EU. Best for: teams that want to own the full observability stack and its operational burden.

Langfuse: Open-Source Tracing and Evals

Langfuse has a large open-source community and covers tracing, prompt management and evaluation through LLM-based checks, code evaluators, user feedback and manual labeling. The repository is MIT except its ee folders, and it self-hosts with Docker Compose, Kubernetes through Helm, or Terraform on AWS, Azure and GCP. It does not document runtime blocking. Best for: teams that mainly used Galileo for tracing and custom evaluations.

Staying on Galileo

If you use Galileo for its built-in metrics, its agentic evaluations and CLHF, no single option above replaces all of that, and the acquisition alone is not a reason to move. Enterprise customers already have Luna-2 and hosted guardrails. Free and Pro users who need blocking can add the open-source Agent Control and keep everything else where it is.

How to Choose

1. If you need to find behavioral failures and carry them through remediation, choose Failproof AI. Its evaluations and automatic failure analysis identify recurring problems, findings recommend fixes, and tested policies can steer or block supported high-risk behavior at the agent hook.
2. If your priority is a large catalog of ready-made evaluations, Future AGI and Galileo provide the broadest sets. Judgment Labs specializes in judges, while Langfuse and Latitude support custom evaluation on open platforms.
3. If procurement is the constraint, favour published prices and self-serve starts: Failproof AI, Raindrop, Latitude and Future AGI publish theirs; Judgment Labs does not.
4. If data must stay on your own infrastructure without an enterprise contract, look at Latitude, Langfuse, Future AGI and self-run Agent Control.

The important distinction is whether discovery and enforcement share one workflow. Failproof AI connects production findings to tested behavioral policies. With other evaluation platforms, teams may need to build or operate the enforcement layer separately. Turn judge findings into runtime policies shows how the workflow works.