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Alternatives

Products that do what NexArt does

Make AI and software execution provable

  1. 1

    Fix bugs faster with open source, AI native observability

    2025

  2. 2
    Replicas239

    Run Claude Code and Codex in the cloud

    Jun 2026 · replicas.dev

  3. 3IB

    Hi HN, I built this because I got tired of the Claude Code CLI hiding details from me. Recent updates have replaced critical output with summaries like "Read 3 files" or "Edited 2 files". To see what actually happened, I was forced to use `--verbose`, which floods the terminal with unreadable JSON and system prompts. I wanted a middle ground: *Full observability without the noise.* `claude-devtools` is a local Electron app that tails the session logs in `~/.claude/` to reconstruct the execution trace in real-time. *Unlike wrappers, it solves the visibility gap in your native…

    Feb 2026 · github.com

  4. 4
    Retrace101

    Debug AI agents by replaying and forking runs

    Jul 2026 · retraceai.tech

  5. 5

    Production context for AI with logs, DBs, and error tracking

    May 2026 · comie.dev

  6. 6OS

    Hi HN, I forked chromium and built agent-browser-protocol (ABP) after noticing that most browser-agent failures aren’t really about the model misunderstanding the page. Instead, the problem is that the model is reasoning from a stale state. ABP is designed to keep the acting agent synchronized with the browser at every step. After each action (click, type, etc), it freezes JavaScript execution and rendering, then captures the resulting state. It also compiles the notable events that occurred during that action loop, such as navigation, file pickers, permission prompts, alerts, and downloads,…

    Mar 2026 · github.com

  7. 7KI

    Hi HN, We're building Kexa.io (https://github.com/kexa-io/Kexa), an open-source tool developed in France (incubated at Euratech Cyber Campus) to help teams automate the often tedious process of verifying IT security and compliance. Keeping track of configurations across diverse assets (servers, K8s, cloud resources) and ensuring they meet security baselines (like CIS benchmarks, etc.) manually is challenging and error-prone. Our goal with the open-source core is to provide a straightforward way to define checks, scan your assets, and get clear reports on your security…

    2025

  8. 8
    Tracea80

    Datadog for AI agents with traces, RCA, and team memory

    May 2026 · tracea.dev

  9. 9TT

    tracexec helps you to figure out what and how programs get executed when you execute a command. It's useful for debugging build systems, catching fd leaks, understanding what shell scripts actually do, figuring out what programs does a proprietary software run, etc.

    2024 · github.com

  10. 10LE

    I started using Claude Code (claude --dangerously-skip-permissions) and Codex (codex --yolo) and realized I had no reliable way to know what they actually did. The agent's own output tells you a story, but it's the agent's story. logira records exec, file, and network events at the OS level via eBPF, scoped per run. Events are saved locally in JSONL and SQLite. It ships with default detection rules for credential access, persistence changes, suspicious exec patterns, and more. Observe-only – it never blocks. https://github.com/melonattacker/logira

    Mar 2026 · github.com

  11. 11

    Visual debugging, tracing, and replay for agent workflows

    Apr 2026 · agenticlens.in

  12. 12OS

    EU legislation (which affects UK and US companies in many cases) requires being able to truly reconstruct agentic events. I've worked in a number of regulated industries off & on for years, and recently hit this gap. We already had strong observability, but if someone asked me to prove exactly what happened for a specific AI decision X months ago (and demonstrate that the log trail had not been altered), I could not. The EU AI Act has already entered force, and its Article 12 kicks-in in August this year, requiring automatic event recording and six-month retention for high-risk systems,…

    Mar 2026

  13. 13

    Auditable, provably-deletable memory for AI agents

    Jul 2026 · github.com

  14. 14ME

    We are building a VM that helps you simulate realistic production conditions, model latencies, different interleaving, user requests, and find bugs. Every non-deterministic property is turned into a knob you or a coding agent can control. We have helped teams perfectly reproduce support incidents and found bugs in some of the world's most well tested software (including a database).

    Jun 2026 · workers.io

  15. 15

    Secure hosting for whatever your AI builds

    Jul 2026 · nexalibre.com

  16. 16
    Recall16

    One developer solves it. Every developer knows it.

    Feb 2026 · recall.team

  17. 17CO

    Hi HN, I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…

    2025 · github.com

  18. 18

    Find Out Whats Exploitable. In Hours, Not Weeks.

    Jul 2026 · neurapent.com

  19. 19

    Proves vulnerabilities before reporting them.

    9d ago · dashboard-seven-self-13.vercel.app

  20. 20

    Instant bug reports your AI agent can actually debug

    Jul 2026 · tracebug.dev

  21. 21

    AI Firewall, Self-Healing Outputs, and Observability

    Jul 2026 · getneurix.netlify.app

  22. 22
    Etch5

    Trace, replay, and verify every AI agent decision.

    Jul 2026 · etch.systems

  23. 23
    CBX2

    The Future of Digital Evidence

    Feb 2026 · cbx.app

  24. 24

    The zero-knowledge engineer that fixes code without seeing

    Nov 2025

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