AI · alternatives · 2026

24 alternatives to How to analyze your LLM output – A behavioural health monitor for LLMs

Hey HN! We're Dr. Kashyap Thimmaraju and Giuseppe Canale from Silicon Psyche. We've built Posture Sequence Analysis (PSA), a behavioural health monitor for LLMs and AI Agents. Why we built PSA We built PSA because we wanted to operationalize the Cybersecurity Psychology Framework (CPF3)[1] via Silicon Psyche[2]: our theory that because LLMs have been trained by humans on human-generated data, they inherit human-like vulnerabilities (what hackers use to psychologically trick people into doing things). Our initial attempt resulted in a methodology to jailbreak Opus 4.6 and other frontier…

Posture Sequence Analysis (PSA) is a behavioral health monitoring tool for large language models and AI agents. It analyzes how LLMs respond to psychological manipulation techniques, based on the theory that language… 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.

1
Athina AI▲509
Monitor LLMs and automatically detect hallucinations in prod
2024 · athina.ai · its alternatives →
2
Llama 3.2 Interpretability with Sparse Autoencoders▲579
I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com · its alternatives →
3
Human Behavior▲273
Product analytics told you what happened. We handle it.
Aug 2026 · humanbehavior.co · its alternatives →
4
Muscle-Mem, a behavior cache for AI agents▲226
Hi HN! Erik here from Pig.dev, and today I'd like to share a new project we've just open sourced: Muscle Mem is an SDK that records your agent's tool-calling patterns as it solves tasks, and will deterministically replay those learned trajectories whenever the task is encountered again, falling back to agent mode if edge cases are detected. Like a JIT compiler, for behaviors. At Pig, we built computer-use agents for automating legacy Windows applications (healthcare, lending, manufacturing, etc). A recurring theme we ran into was that businesses already had RPA (pure-software scripts), and…
2025 · github.com · its alternatives →
5
Digital Behavioral Design▲417
Human behavior is programmable. A book on product design.
2018 · thriveglobal.com · its alternatives →
6
Open-source model and scorecard for measuring hallucinations in LLMs▲65
Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com · its alternatives →
7
Mental State of HN Users Before/After Lockdown▲65
Explore and run AI code with Kaggle Notebooks | Using data from Hacker News: All Posts, Stories, Ask/Show HN, etc
2020 · kaggle.com · its alternatives →
8
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 →
9
Kelet – Root Cause Analysis agent for your LLM apps▲47
I've spent the past few years building 50+ AI agents in prod (some reached 1M+ sessions/day), and the hardest part was never building them — it was figuring out why they fail. AI agents don't crash. They just quietly give wrong answers. You end up scrolling through traces one by one, trying to find a pattern across hundreds of sessions. Kelet automates that investigation. Here's how it works: 1. You connect your traces and signals (user feedback, edits, clicks, sentiment, LLM-as-a-judge, etc.) 2. Kelet processes those signals and extracts facts about each session 3. It forms hypotheses…
Apr 2026 · kelet.ai · its alternatives →
10
20+ Claude Code agents coordinating on real work (open source)▲53
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 →
11
LLM Alignment Template – Aligning Language Models with Human Feedback▲9
Hey Hacker News! I've been working on an open-source project called LLM Alignment Template, a comprehensive toolkit designed to help researchers, developers, and data scientists align large language models (LLMs) with human values using Reinforcement Learning from Human Feedback (RLHF). What the project does: Interactive Web Interface: Easily train models, visualize alignment metrics, and manage alignment with an accessible UI. Training with RLHF: Align models effectively to human preferences using feedback loops. Explainability: Built-in dashboards to help understand model behavior using…
2024 · github.com · its alternatives →
12
Digital Behavioral Intelligence▲15
Analyze user's "Digital Body Language" to predict intent.
2020 · formotiv.com · its alternatives →
13SB
Stop building "Agents" and ship LLM-powered chatbots that work▲10
2024 · rasa.com · its alternatives →
14
I implemented evals metrics for LLMs that runs locally on your machine▲22
The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
2023 · github.com · its alternatives →
15
Aiaiai.guide: Plain-English mental model for LLM apps, tools and agents▲7
I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide · its alternatives →
16
Spoon-Bending – a framework for analyzing GPT-5 alignment behavior▲22
I put together a repo called Spoon-Bending, it is not a jailbreak or hack, it is a structured logical framework for studying how GPT-5 responds under different framings compared to earlier versions. The framework maps responses into zones of refusal, partial analysis, or free exploration, making alignment behavior more reproducible and easier to study systematically. The idea is simple: by treating prompts and outputs as part of a logical schema, you can start to see objective patterns in how alignment shifts across versions. The README explains the schema and provides concrete tactics for…
2025 · github.com · its alternatives →
17
Opt-in Self-Check▲3
A runtime behavioral probing framework for LLM agents
Jul 2026 · github.com · its alternatives →
18
SYNTHETIC CORTEX Beta Test▲6
artificial emotions into LLMs
2025 · scortexlabs.com · its alternatives →
19
LLMs can be susceptible to a new kind of malware▲17
New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
20
RagMetrics▲13
We built live AI evaluation to detect hallucinations, grounding issues, and drift as outputs are generated. This helps teams move GenAI from pilots into production.
2025 · ragmetrics.ai · its alternatives →
21
Conduct, open-source guardrails for LLM and MCP tool calls▲22
Runtime governance for AI agents. Allow, warn, or block every model and tool call before it commits. Hash-chained audit for every decision. Compliance packs for SOC 2, HIPAA, PCI DSS, EU AI Act, SR 11-7, and FDA CSA. Apache 2.0. - sseshachala/conductai
Aug 2026 · github.com · its alternatives →
22
Humsana▲11
Real-time Behavioral Intelligence
Nov 2025 · humsana.com · its alternatives →
23
I built an open-source AI data layer that connects any LLM to any datafree▲18
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
2025 · github.com · its alternatives →
24
Auto-generate hard evaluation data for LLMs▲14
Expert quality medical abstraction, powered by LLMs.
2024 · talc.ai · 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 →