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Future AGI vs Langfuse

Open-source LLM observability without built-in guardrails or simulation.

Side by side

What it is: Future AGI:Future AGI is a platform for evaluating, guarding, and optimizing AI agents to prevent hallucinations and improve accuracy.; Langfuse:Langfuse is an open-source platform for tracing, evaluating and monitoring LLM applications and AI agents.
Best for: Future AGI:AI hallucination detection & optimization; Langfuse:LLM observability & analytics
Who it’s for: Future AGI:Enterprises and teams building AI agents that need safety, observability, and continuous improvement.; Langfuse:Developers building, debugging and scaling LLM-based apps and agents.
Pricing: Future AGI:Freemium; Langfuse:Freemium
Plans: Future AGI:Free $0/mo · Pay-as-you-go $0/mo; Langfuse:Hobby Free · Core $29 per month · Pro $199 per month · Enterprise $2499 per month
Open source: Future AGI:Yes, 2,080 GitHub stars; Langfuse:Yes, 35,097 GitHub stars
Works with: Future AGI:Docker Compose, OpenAI, Anthropic, Gemini, ClickHouse, Temporal; Langfuse:Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift
DevHunt upvotes: Future AGI:19; Langfuse:89
Launched on DevHunt: Future AGI:Sep 2025; Langfuse:Jan 2023

Guardrails. Block AI hallucinations in real-time with built-in and ML-powered guardrails.
Evaluations. Run comprehensive evaluations using 20+ metrics and AI-as-judge.
Simulations. Simulate thousands of multi-turn conversations for text and voice agents.
Tracing. End-to-end request tracing with custom dashboards and alerts.
Datasets & Experiments. Manage versioned evaluation datasets and run structured experiments.
Agent IDE. Visually build, test, and iterate AI agents with a low-code interface.
Dashboards. Drag-and-drop widgets for unlimited custom dashboards.
Alerting. AI-powered alerts for anomalies and hallucination spikes.

Hierarchical Traces. Capture every LLM call, tool invocation and retrieval step with filters for user, session, cost and latency.
Prompt Management. Version, fetch, release and cache prompts separately from code with one-click deployments.
Evaluation Engine. Run LLM-as-judge, heuristic or human-review evaluations on production data or experiments.
Experiments & Datasets. Define test cases, run experiments and create golden datasets for continuous improvement.
Dashboards & Alerts. Monitor cost, latency and quality via custom dashboards and automated alerts.
Human Annotation. Collaborative human-in-the-loop workflows with annotation queues.
Extensive Integrations. Supports Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift and 100+ agent frameworks and model providers.
Self-hosted & Cloud Options. Available as hosted SaaS or self-hosted under MIT license.

Based on each tool's website and DevHunt data. Details may change; check the official sites.