━━ Failproof AI · answers
answers
one question per page, answered in the first paragraph: pricing, self-hosting, open source, runtime blocking, and which tool fits a mid-market team - checked against each vendor's own site and docs.
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Agent evaluation tools with runtime guardrails
Failproof AI, Galileo and Future AGI can intervene while an agent is running. They enforce checks at different points, so the right choice depends on whether you need to inspect model traffic, gateway calls or the tool action itself.
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Agent observability pricing compared: eight platforms, one table
Free tiers, entry prices and billing meters for eight agent observability platforms. Compare what you pay to trace sessions, evaluate behavior, find recurring failures, alert your team and act on what the system finds.
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An agent eval platform for mid-market teams: six requirements, six vendors
Mid-market teams need production evaluations and failure analysis without an enterprise buying cycle or a dedicated evaluation team. Compare six platforms on self-service access, pricing, remediation, security and deployment.
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Best agent behavior monitoring tools for finding and fixing failures
Eight tools for understanding how agents behave in production. Compare how they detect failures, group recurring problems, evaluate sessions, alert your team and help prevent the same failure from happening again.
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Best Judgment Labs alternatives for agent evaluation and monitoring
Compare seven alternatives for agent evaluation, production monitoring, failure discovery, self-hosting and runtime policies. The right choice depends on what is missing from Judgment Labs for your team.
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Best LLM-as-a-judge tools for evaluating AI agents
Compare eight tools for running LLM judges in CI and on production agent sessions. See which ones add tracing, failure analysis, alerts, self-hosting and a path from a bad score to a fix.
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Build vs buy for agent evals: build the judgment, buy the plumbing
The rubrics, the labels and the calibration are yours whichever way you go. The question is who runs the storage, the scoring schedule, the dashboards and the alerts - and a decision rule for answering it.
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Can you self-host Judgment Labs? The SDK yes, the platform not yet
judgeval runs in your code, but the Judgment platform it reports to is hosted only, with self-hosting listed as coming soon. What runs where today, what to ask, and the options that put agent traces on your own infrastructure now.
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Can you self-host Raindrop? VPC deployment is a limited beta
Raindrop added deployment in your own VPC with Raindrop 2.0 in June 2026, and is rolling it out to a small group of partners first. What that means for a team whose data cannot leave its cloud, and what to run in the meantime.
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Cisco acquired Galileo: what it means for customers
Cisco announced the Galileo acquisition in April 2026, completed it in May and renamed the product Splunk Agent Observability in August. Here is what changed and what customers should confirm before renewal.
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Do you need an agent evaluation platform?
A script and a spreadsheet are enough while one team can still review its agent by hand. A platform becomes useful when production volume hides failures, several agents need consistent evaluation, or problems must reach an owner quickly.
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Does Future AGI block tool calls?
Yes, when the tool call passes through Future AGI's Agent Command Center. Here is what its Tool Permissions and MCP Security checks cover, and where you may need protection closer to the agent.
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Does Judgment Labs block agent actions? No - here is what does
Judgment Labs scores agent traces and alerts on them after they run. That is a deliberate design, not a gap to wait out. What the docs say, why monitors stay off the hot path, and how to add blocking beside judgeval.
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Does Raindrop block agent actions?
Raindrop is built to find silent agent failures, rank them and help you fix them. It does not sit in front of a tool call. What it does, why a monitor is built that way, and how to add blocking beside it.
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Future AGI alternatives: six options and who each one fits
Future AGI combines evaluations, judge models, simulation, prompt optimization and gateway guardrails in one Apache-2.0 platform. Compare alternatives for automated failure discovery, simpler self-hosting, deeper judge tooling and production issue resolution.
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Future AGI pricing: free tier, usage rates and the three add-ons
Future AGI combines a free allowance with usage charges and optional monthly add-ons for retention, SSO, compliance and support. See the published rates, a worked monthly bill and the contract details that need confirmation.
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Future AGI self-hosting requirements: hardware, stack and caveats
Future AGI supports self-hosting through Docker Compose. See the hardware tiers, services, licence boundaries, telemetry settings and production checks your team should plan for.
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Galileo alternatives: seven options and who each one fits
Galileo is now Splunk Agent Observability, its hosted guardrails and Luna-2 sit on Enterprise, and Protect is deprecated. Seven options, including staying put, with what each does instead and where each is weaker.
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Galileo pricing: Free, Pro at $100 a month, and what Enterprise adds
Galileo publishes two of its three plans. Free and Pro are metered in traces; everything that blocks at runtime, Luna-2 included, sits on Enterprise behind a sales call. What each tier gets, what grows with volume, and what to ask.
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Galileo Protect is deprecated: what to use instead
Galileo deprecated Protect in June 2026 and points new users to Agent Control, an Apache-2.0 control plane you run yourself. What changed, the four realistic replacements, and how to move one guardrail across.
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How much do agent evals cost? Judge tokens plus the platform fee
Two bills: the tokens your judge model reads, and whatever the platform meters. A formula for the first, worked examples with every assumption stated, the vendor meters for the second, and the levers that move both.
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Is Galileo Luna-2 Enterprise-only? Yes, and other ways to judge cheaply
Yes. Luna-2 is limited to Galileo Enterprise. See what the 3B and 8B evaluation models do, how the published token rate fits into an Enterprise contract and how to reduce judge costs without them.
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Is judgeval open source? Yes - the SDK, not the platform
judgeval is Apache-2.0 and public on GitHub. The Judgment platform it sends traces to is closed and hosted. Here is what the license covers, what still depends on the service, and how other deployment models compare.
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Judgment Labs pricing: not published, and what to ask instead
Judgment Labs sells by demo and publishes no plans. What is free, what is not public, the questions that turn a demo into a comparable quote, and what the rest of the agent evaluation category charges on the page.
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Latitude alternatives: what to use instead, and when to stay
Latitude V2 provides open-source tracing and evaluation. Teams look elsewhere when they need deeper production querying, automatic failure analysis, alerts, or a workflow that carries a finding through to a tested fix.
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Latitude pricing: tiers, credits, and the cost of self-hosting
Latitude offers a free cloud tier, Pro at $99 a month and custom Enterprise pricing, with unlimited seats throughout. Usage is billed in credits, but the public pricing page does not define how product activity converts into credits.
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Latitude self-hosting: what you deploy and what you operate
Latitude is MIT-licensed and can run on your infrastructure through Docker Compose, Swarm, Helm or Railway. See the services you operate, the production work involved and when self-hosting makes sense.
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Latitude V1 gateway removed: what changed and what to do now
Latitude V2 removed the prompt gateway, PromptL, hosted tools and triggers. Here is what still works, how to migrate, and when to replace the gateway with direct provider calls or a separate service.
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Migrating agent evals between platforms: what moves and what does not
Traces, datasets and judge code move. Score history, tuned alerts and calibration mostly do not. How to use OpenTelemetry as the portable layer, run two platforms side by side, and cut over without losing the thread.
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Open-source agent eval tools: what is actually open in each
"Open source" covers a pytest plugin, an SDK for a closed platform, and a whole platform you run yourself. The license of each, what it gets you, and what stays behind a contract.
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Questions to ask an agent eval vendor, and what a good answer sounds like
Use this checklist to test failure discovery, evaluation quality, trace access, alerting, fixing workflows, deployment, security and pricing during a demo or trial.
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Raindrop AI pricing: the plans, the meter and the arithmetic
Raindrop publishes its prices in its docs rather than on a pricing page. The shape is simple - a free cap, a flat Pro fee, and a per-event meter with no allowance - so the monthly bill is one line of arithmetic once you know your traffic.
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Raindrop alternatives: seven options and who each fits
Raindrop classifies production agent events and groups recurring problems into Issues. Teams look elsewhere for a lower starting price, a workflow that carries findings through to fixes, broader deployment options or alert channels beyond Slack.
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Security review checklist for agent observability vendors
Agent traces can contain shell commands, file contents, query results, secrets and customer data. Use this checklist to review collection, redaction, model access, retention, identity, deployment and compliance.
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Self-hosted agent evaluation platforms: what you can run yourself today
Compare agent evaluation platforms you can deploy on your own infrastructure, from free open-source projects to Enterprise VPC and on-prem installations. See what each licence includes and what your team must operate.
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Self-service agent evaluation platforms: pricing, trials and sales calls
Most agent evaluation platforms offer a free tier and a first paid plan you can buy online. Here is which you can try without a sales call, which become sales-led when you upgrade, and which require a demo from the start.
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Sentry for AI agents: error tracking for failures that throw nothing
Error trackers work because code that fails usually throws. Agents fail by answering wrongly, skipping a step or stopping early, with every call returning 200. What carries over from the Sentry model, what breaks, and which tools fill the gap.
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What is agent behavior monitoring, and what can it not do?
Agent behavior monitoring uses production traces to measure known behaviors, uncover recurring failure modes and help teams fix what agents do. Here is how the workflow differs from tracing, offline evals and runtime controls.
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