AI · alternatives · 2026

24 alternatives to Graphsignal – Production Model Monitoring: Anomalies, Drift, Exceptions

GPU Profiler for AI agents. Contribute to graphsignal/graphsignal development by creating an account on GitHub.

Graphsignal is a production model monitoring tool that tracks anomalies, drift, and exceptions in deployed machine learning models. It helps data scientists and ML engineers identify when models behave unexpectedly or… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Graphsignal – Production Model Monitoring: Anomalies, Drift, Exceptions launched in 2021; newer entries below may have overtaken it.

1
Graphsignal – Machine learning profiler for training and inference▲35
Hi HN, I'm the founder of Graphsignal (https://graphsignal.com). Graphsignal is a machine learning profiler. We've created it to make ML profiling simple and usable. It provides performance summaries, ML operation and kernel level statistics as well as detailed resource usage information necessary for making training and inference faster and more efficient. Profilers help fix performance issues, improve user experience and reduce computation costs. Such improvements benefit machine learning profoundly; model training jobs that run for hours or days could be made much shorter and…
2022 · graphsignal.com · its alternatives →
2
Graphsignal – ML profiler to speed up training and inference▲16
Hi, Graphsignal founder here. We've launched Graphsignal earlier this year to make machine learning profiling practical and easy to use. Basically, it enables the profile-optimize-benchmark loop. For example, making inference faster by optimizing an ML model, while still maintaining accuracy. We've make a lot of progress that I wanted to share. The profiler now natively supports TensorFlow, Keras, PyTorch, PyTorch Lightning, Hugging Face, XGBoost and JAX frameworks along with built-in support for distributed workloads. Profiles now include tracing information in chrome trace format. Process…
2022 · github.com · its alternatives →
3
GraphBit▲437
We built GraphBit to solve the reliability gap in AI frameworks. It’s built on a Rust execution core with a Python layer for accessibility — deterministic orchestration, lock-free concurrency, and built-in observability. We’d love feedback from the HN community, especially from those running multi-LLM or agentic workflows at scale.
2025 · graphbit.ai · its alternatives →
4
Forge – Guardrails take an 8B model from 53% to 99% on agentic tasks▲687
Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments. I built Forge, an open-source reliability layer for self-hosted LLM tool-calling. What it does: - Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) to local models running on consumer hardware - Takes an 8B model from ~53% to ~99% on multi-step agentic workflows without changing the model - just the system around it - Ships with an eval harness and interactive dashboard so you can reproduce every number I wanted to run a handful of always-on agentic systems…
May 2026 · github.com · its alternatives →
5
Circuit Tracer▲457
Anthropic's open tools to see how AI thinks
2025 · anthropic.com · its alternatives →
6
Graphite Reviewer▲575
Your high-signal AI code review companion
2024 · graphite.com · its alternatives →
7
Fast Real-Time Anomaly Detection in Dynamic Graphs▲118
Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies. - Stream-AD/MIDAS
2020 · github.com · its alternatives →
8
Higher Order Sketch-Based Graph Anomaly Detection▲55
Sketch-Based Anomaly Detection in Streaming Graphs - Stream-AD/AnoGraph
2021 · github.com · its alternatives →
9
Human Behavior▲273
Product analytics told you what happened. We handle it.
Aug 2026 · humanbehavior.co · its alternatives →
10
Claude Artifacts but creating real web apps▲189
Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://news.ycombinator.com/item?id=36422730 Would love feedback if you give…
2024 · gptengineer.app · its alternatives →
11
Fast Anomaly Detection in Graphs [pdf]▲215
The NUS School of Computing is recognised among the top global universities for computer science; and exemplifies academic excellence and innovative research.
2020 · comp.nus.edu.sg · its alternatives →
12
Monitor ML▲171
Real-time production monitoring of ML models, made simple.
2019 · arize.com · its alternatives →
13
Real-time dashboard for Claude Code agent teams▲77
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 →
14
Progress AI Observability▲168
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.
Aug 2026 · telerik.com · its alternatives →
15
Interactive, animated architecture of any HuggingFace models▲113
Interactive, animated architecture maps for any Hugging Face model — and whether it fits on your GPU.
Aug 2026 · modelmap.cc · its alternatives →
16UD
Unify – Dynamic LLM Benchmarks and SSO for Multi-Vendor Deployment▲91
Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
17
We post-trained a model that pen tests instead of refusing▲93
Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…
Jun 2026 · argusred.com · its alternatives →
18IG
Interactive Graph by LLM (GPT-4o)▲45
Data automation and visualization platform for spreadsheet users.
2024 · columns.ai · its alternatives →
19
ML condenses billions of logs into a tiny snapshot your LLM can debug▲13
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 →
20
Whisker▲94
Create and edit CAD models into production-ready prototypes
Mar 2026 · whisker.spatialkittens.com · its alternatives →
21WH
We have built a benchmark platform for graph databases▲83
2022 · memgraph.com · its alternatives →
22
CueObserve▲73
Open-source Anomaly detection on SQL data
2021 · github.com · its alternatives →
23
Spec27▲34
Hi HN! We’re a team of ML validation specialists and we’ve been building /Spec27, a tool for testing whether AI agents still do their job safely and reliably as models, prompts, tools, and surrounding systems change. We started working on this because a lot of current LLM evaluation work seems aimed at scoring general model behavior, while many teams are deploying systems that have a specific mission to fulfill. Many of the tools also assume you have full access to the agent stack and traces so you can place SDKs and Gateways, but a lot of agents are being created on vendor platforms…
Apr 2026 · spec27.ai · its alternatives →
24
CUDA Profiler for Production Inference▲6
Graphsignal Profiler. Contribute to graphsignal/graphsignal-profiler development by creating an account on GitHub.
Jun 2026 · github.com · its alternatives →

Also compare

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 →