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Langfuse vs Scoopika

Observability for LLM apps, not a toolkit for building agents.

Side by side

What it is
Langfuse:Langfuse is an open-source platform for tracing, evaluating and monitoring LLM applications and AI agents.
Scoopika:Open-source toolkit to build multimodal AI agents with streaming, validation, memory and knowledge stores.
Best for
Langfuse:LLM observability & analytics
Scoopika:Multimodal AI agents with real-time streaming
Who it’s for
Langfuse:Developers building, debugging and scaling LLM-based apps and agents.
Scoopika:Developers building LLM-powered web apps, bots, and data extraction tools.
Pricing
Langfuse:Freemium
Scoopika:Freemium
Plans
Langfuse:Hobby Free · Core $29 per month · Pro $199 per month · Enterprise $2499 per month
Scoopika:HOBBY Free
Open source
Langfuse:Yes, 35,097 GitHub stars
Scoopika:—
Works with
Langfuse:Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift
Scoopika:—
DevHunt upvotes
Langfuse:89
Scoopika:4
Launched on DevHunt
Langfuse:Jan 2023
Scoopika:Oct 2024

Langfuse features

  • 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.

Scoopika features

  • Real-time streaming. Stream text and voice responses as they are generated, with hooks for token and tool callbacks.
  • LLM output validation. Built-in JSON schema validation with retries and error recovery.
  • Serverless long-term memory. Managed encrypted memory store for conversation history without developer overhead.
  • Knowledge stores. Upload files, PDFs or websites to edge-close stores that agents can query.
  • Multimodal inputs. Accept text, images, audio and URLs, and generate validated outputs from any source.
  • Custom functions & APIs. Connect any API or custom code as tools agents can call during execution.
  • Voice interaction. Process multiple audio inputs in parallel and stream voice replies in under 300 ms.
  • Open-source SDKs. Type-safe TypeScript SDKs for server, client and React integration.

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