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Alternatives

Products that do what OpenAnchor does

Observe and optimize every LLM request

  1. 1
    LangWatch669

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  2. 2

    Trace LLM requests + costs with OpenTelemetry monitoring

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  3. 3OO

    Hey HN, Nir, Gal and Tomer here. We’re open-sourcing a set of extensions we’ve built on top of OpenTelemetry that provide visibility into LLM applications - whether it be prompts, vector DBs and more. Here’s the repo: https://github.com/traceloop/openllmetry. There’s already a decent number of tools for LLM observability, some open-source and some not. But what we found was missing for all of them is that they were closed-protocol by design, vendor-locking you to use their observability platform or their proprietary framework for running your LLMs. It’s still early in the…

    2023 · github.com

  4. 4

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  5. 5

    Aggregate uptime monitoring across OpenAI, Claude, and more

    Apr 2026 · tools.lamatic.ai

  6. 6LO

    Hey HN, we’re Robert, Din and Temirlan from Laminar (https://www.lmnr.ai), an open-source observability and analytics platform for complex LLM apps. It’s designed to be fast, reliable, and scalable. The stack is RabbitMQ for message queues, Postgres for storage, Clickhouse for analytics, Qdrant for semantic search - all powered by Rust. How is Laminar different from the swarm of other “LLM observability” platforms? On the observability part, we’re focused on handling full execution traces, not just LLM calls. We built a Rust ingestor for OpenTelemetry (Otel) spans with GenAI…

    2024 · github.com

  7. 7

    Evaluate & optimize your LLM performance with DSPy

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  8. 8
    LLMWare358

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  9. 9AT

    I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…

    2025 · llmapitest.com

  10. 10
    Openlit152

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  11. 11
    AskCodi230

    Custom LLMs, without training. Use via openai compatible api

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  12. 12YD

    If you've built any web-based app in the last 15 years, you probably used something like Datadog, New Relic, Sentry, etc. to monitor and trace your app, right? Why should it be different when the app you're building happens to be using LLMs? So today we're open-sourcing OpenLLMetry-JS. It's an open protocol and SDK, based on OpenTelemetry, that provides traces and metrics for LLM JS/TS applications and can be connected to any of the 15+ tools that already support OpenTelemetry. Here's the repo: https://github.com/traceloop/openllmetry-js A few months ago we launched…

    2024 · github.com

  13. 13

    LLM Provider arbitrage to get the best performance for the $

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  14. 14

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  15. 15
    Openlayer197

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  16. 16

    Open source Google Reviews analyzer project using LLM

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    LLMonitor128

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  18. 18

    Avoid OpenAI downtimes - one API for 30+ LLMs

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  19. 19

    Calculate and compare the cost of the latest LLM APIs

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  20. 20
    Tokenwise143

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  21. 21

    An AI Cost Optimization Infrastructure for LLM Applications

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  22. 22
    LLMTest125

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  23. 23OO

    Hey HN, we're super excited to share something we've been working on: OpenLIT. After an engaging preview that some of you might recall, we are now proudly announcing our first stable release! *What's OpenLIT?* Simply put, OpenLIT is an open-source tool designed to make monitoring your Large Language Model (LLM) applications straightforward. It’s built on OpenTelemetry, aiming to reduce the complexities that come with observing the behavior and usage of your LLM stack. *Beyond Basic Text Generation:* OpenLIT isn’t restricted to just text and chatbot outputs. It now includes automatic…

    2024 · github.com

  24. 24AL

    We built any-llm because we needed a lightweight router for LLM providers with minimal overhead. Switching between models is just a string change : update "openai/gpt-4" to "anthropic/claude-3" and you're done. It uses official provider SDKs when available, which helps since providers handle their own compatibility updates. No proxy or gateway service needed either, so getting started is pretty straightforward - just pip install and import. Currently supports 20+ providers including OpenAI, Anthropic, Google, Mistral, and AWS Bedrock. Would love to hear what you think!

    2025 · github.com

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