Alternatives
Products that do what Phoring — Scenario Intelligence Engine does
From documents to simulations to cited foresight
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io
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2025 · github.com
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2023 · stackoverflow.gg
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Hey hn, this has been something I've been working on for the last few months and is finally robust enough to really show off. I've been pretty tired with the design outputs of LLMs for a while, and I've always thought diffusion offered much more creative / on brand design outputs, even before they were able to render text. I had enough conviction for this to leave my role over at Figma to build Diffui. The goal is to allow for you to design your full web app as quickly as possible, in a figma-like interface, and then hand that off to an agent to build. The page shows some interactive…
Jul 2026 · diffui.ai
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Run a research agent with cited answers in a single API call
Jun 2026 · tabstack.ai
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I started building this 10 months ago, largely using agentic coding tools. I've stayed very involved in the code base and architecture, and have never moved faster in my life as a dev. The word processor engine and rendering layer are all built from scratch - the only 3rd party library I used was the excellent Y.js for the CRDT stack. Would love some feedback!
Mar 2026 · revise.io
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Hey HN! Over the weekend (leaning heavily on Opus 4.5) I wrote Jargon - an AI-managed zettelkasten that reads articles, papers, and YouTube videos, extracts the key ideas, and automatically links related concepts together. Demo video: https://youtu.be/W7ejMqZ6EUQ Repo: https://github.com/schoblaska/jargon You can paste an article, PDF link, or YouTube video to parse, or ask questions directly and it'll find its own content. Sources get summarized, broken into insight cards, and embedded for semantic search. Similar ideas automatically cluster together. Each…
Dec 2025 · github.com
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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
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We built HALO (Hierarchal Agent Loop Optimizer), an open-source tool for debugging and optimizing AI agents using their execution traces. It’s a loop. Run your agent, feed the traces to HALO, get the report, apply the fixes, then re-run your agent. HALO takes in OTEL compliant traces from AI agents using tracing frameworks such as Langfuse, Arize/OpenInference, or even just plain JSONL. It uses an RLM (Recursive Language Model) to more efficiently break trace analysis into smaller subproblems in order to find recurring patterns across large amounts of data and fix systemic issues that…
Jun 2026 · github.com
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2025 · github.com
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Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!
Nov 2025 · github.com
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I feel like LLMs can help me understand anything. However, after I get a summary, I can't dive in to parts that I find interesting; can't refer to original source easily and can't control context with chatbots. This is an attempt to solve for a complete knowledge consumption experience with AI . Please give me feedback!
Oct 2025 · kerns.ai
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Hi HN. I've been running AI coding agents (Claude Code, Codex, etc.) on real repos for a while now. The dirty secret of "autonomous coding" is that agents stop all the time — quota limits, test failures, policy violations, bad judgement calls. You end up babysitting them. So I asked a different question: what if the system was designed around the assumption that agents WILL fail, and the job of the infrastructure is to never let that failure become a dead end? openTiger is a "non-human-first" orchestration system that runs multiple AI agents in parallel — planner, workers, testers, judge —…
Feb 2026 · github.com
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In the age of information, documentation is your team's strategic asset. AkiraDocs turns that asset into a powerful, intelligent platform that grows with your organization. Transformative Capabilities: Automated content generation Instant multi-language support Data-driven SEO optimization Flexible integration Invest in documentation that delivers real value.
2024 · github.com
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