AI · alternatives · 2026
24 alternatives to Progress AI Observability
Hi HN! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.
Progress AI Observability is a debugging and monitoring platform for AI agents running in production. It traces agent executions to identify failures, hallucinations, and ungrounded responses that standard monitoring… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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OpenTelemetry-native observability for agents and LLMs
Aug 2026 · openobserve.ai · its alternatives →
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Automated Penetration Testing for AI-Built Apps
2021 · replay.io · its alternatives →
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TraceRoot.AI▲342Fix bugs faster with open source, AI native observability
2025 · traceroot.ai · its alternatives →
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…
Dec 2025 · truefoundry.com · its alternatives →
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AgenticLens▲64Visual debugging, tracing, and replay for agent workflows
Apr 2026 · agenticlens.in · its alternatives →
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Tracium.ai▲70Hi everyone, thanks for checking out tracium. At work I needed some clarity on how much each agent costs us and how they perform on production so I started looking at existing solutions for this such as LangSmith and LangFuse. Honestly, they felt like they are overcomplicated to integrate and that there should be a simpler solution so I decided to build Tracium. Tracium keeps track of every single AI API call that you make to an LLM provider, with this you can see traces, spans, I/O, tokens in/out, latency. You can compare during A/B testing, see usage from each customer and…
Mar 2026 · tracium.ai · its alternatives →
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Agent Monitor▲128An AI agent rewriting your codebase looks like scrolling text in a terminal. Agent Monitor shows you what it
Feb 2026 · agentmonitor.io · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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Tracea▲80Datadog for AI agents with traces, RCA, and team memory
May 2026 · tracea.dev · its alternatives →
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APIEval-20▲121An open benchmark for AI agents that test APIs
May 2026 · resources.kusho.ai · its alternatives →
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This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…
Apr 2026 · github.com · its alternatives →
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Retracefree tier, from $29/mo▲101Retrace records your AI agents runs so you can replay them step by step, fork from any point to a fix, and share the result as a link
Jul 2026 · retraceai.tech · its alternatives →
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Your AI agent is burning 6x more tokens than it needs to just to browse the web. We built OpenBrowser MCP to fix that. Most browser MCPs give the LLM dozens of tools: click, scroll, type, extract, navigate. Each call dumps the entire page accessibility tree into the context window. One Wikipedia page? 124K+ tokens. Every. Single. Call. OpenBrowser works differently. It exposes one tool. Your agent writes Python code, and OpenBrowser executes it in a persistent runtime with full browser access. The agent controls what comes back. No bloated page dumps. No wasted tokens. Just the data your…
Apr 2026 · openbrowser.me · its alternatives →
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Hi HN! My name is Olaf, I work at CircleCI as a technology advisor in the CTO office, came in through the acquisition of my company Vamp.io (progressive delivery for microservices on k8s) in 2021. Wanted to hear the HN community feedback and thoughts on a project we think could be very interesting when adding AI coding agents to the SDLC and your CI pipelines. Our team at CircleCI built Chunk sidecars after repeatedly running into the same issue internally: by the time our CI catches a failure, the agent has already moved on and most of the useful context is gone. The basic idea of Chunk…
May 2026 · circleci.com · its alternatives →
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We built meta-agent: an open-source library that automatically and continuously improves agent harnesses from production traces. Point it at an existing agent, a stream of unlabeled production traces, and a small labeled holdout set. An LLM judge scores unlabeled production traces as they stream. A proposer reads failed traces and writes one targeted harness update at a time, such as changes to prompts, hooks, tools, or subagents. The update is kept only if it improves holdout accuracy. On tau-bench v3 airline, meta-agent improved holdout accuracy from 67% to 87%. We open-sourced meta-agent.…
Apr 2026 · github.com · its alternatives →
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We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev · its alternatives →
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Tool-agnostic TypeScript library for observing coding agent sessions. Built-in Cursor provider, extensible to Claude Code, Codex, and OpenCode. - vtemian/agentprobe
Mar 2026 · github.com · its alternatives →
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Hi HN, I'm Kaushik, and I built Rocketgraph. I believe that while other spaces have caught up to the AI wave, the observability space is still lagging behind, using the same tools and dashboards that we use to analyse logs from human-written code. But now the code is written and debugged by AI, so we need to rethink how we do observability where the observer itself is an AI. The problem that I run into is when an alert fires, I have to manually check the Grafana dashboards and write LogQL queries, which is pretty much like greping. But production usually breaks due to a schema mismatch, or a…
Jun 2026 · github.com · its alternatives →
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Full observability for AI agents. Zero code changes.
Apr 2026 · agentlens.techmatbd.com · its alternatives →
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At Laminar (https://github.com/lmnr-ai/lmnr) we're building open source AI observability platform in Rust. We obsess over instrumentation DX for our Python and TS SDKs and in this new blog we outline how we made the most seamless way of instrumenting recently released claude agent sdk
Dec 2025 · laminar.sh · its alternatives →
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Aug 2026 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →