Developer Tools1 month ago
Auriko | One API for Every LLM, Zero Markup, Cache-Aware Cost Arbitrage
Use one API to access and switch between LLM providers while optimizing inference costs.
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
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Use one API to access and switch between LLM providers while optimizing inference costs.
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
Convert PDF, DOCX, XLSX, CSV, JSON, XML, HTML, Images to clean Markdown optimized for AI Agents, RAG, and Vector DBs. 100% Privacy-First, In-Browser Conversion.
@13SahajChawla · X
For professionals to redact their client's sensitive informations before giving AI to process it & while converting any kind of document to a structured MD file. Better quality outputs, 100% privacy with on-browser local processing, and fully free!
Tests LLM endpoints with adversarial cases and provides OWASP-mapped security audit reports.
@aryaan_sheth · X
- LLM security for small teams
Scale AI search visibility across client portfolios and internal teams with automated content generation, Brand DNA indexing, and LLM tracking across ChatGPT, Perplexity & Gemini.
u/Physical_Champion234 · Reddit
Built an AEO SaaS, would love brutally honest feedback please Hey everyone, I’ve been building Cyted , a SaaS that helps businesses track how often their brand appears in answers from AI tools like ChatGPT, Perplexity, Gemini, Google AI Overviews, Copilot. It’s more than just tracking mentions. Cyted can scan a company’s entire website, identify SEO and AI visibility issues, explain what may be wrong, and suggest ways to fix them. It also helps create blog posts based on those recommenda
Compare LLM API pricing across 450+ routes and calculate real monthly costs with caching and batch pricing factors.
u/Greywolff06 · Reddit
I built LLMPrice — a free calculator for comparing LLM API costs across 450+ pricing routes I kept running into the same problem when comparing LLM APIs: the headline token price doesn't always tell you what your actual workload will cost. Caching, batch pricing, reasoning tokens, retries, different endpoints, and OpenRouter routes can change the result quite a bit. So I built LLMPrice.com. You enter your workload once — requests, input/output tokens, caching, retries, etc. — and it com
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
Calculate GPU VRAM requirements for LLM fine-tuning and inference.
@FaiqAdzlan · X
Built a GPU VRAM calculator to try out Claude Code (#cursorfanboy). I wanted it as granular as possible so I based it off of LLMem) which really just covers fine-tuning tbh. Please tear it to shreds: GitHub:
Try semantic adapters that modify how frozen language models perceive marked text spans.
joshua_s_penman · HN
Semantic Overlays – an NX bit for LLM prompt injection (live demo)
API providing token-level citations for LLM output grounded in attention analysis.
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
Access multiple AI language models through a unified API interface.
u/DanTahirCode · Reddit
I built an open source coding agent with a personality - meet Klenny Code 🐾 Hey r/SideProject, my name is Dan Tahir, and I'm here to show off something I'm really proud of: Klenny Code, the open source coding agent with personality. A fully capable coding agent with memory and cross-project referencing, plus an assistant who can read your email, run scheduled tasks, pilot your browser, and be your corgi pal. Here's the pitch: bring your own OpenRouter API key, and Klenny wil
Compare LLM API pricing and calculate your monthly costs instantly.
u/ahmedk2002 · Reddit
I built a real-time LLM API pricing comparator — because I was tired of not knowing the actual cost difference between models I use LLMs daily at work and kept running into the same frustration: provider pricing pages give you raw numbers per million tokens, but no way to understand what that actually means for your specific use case. Is GPT-4o really that much more expensive than Claude Sonnet for 10k requests per day? What about DeepSeek vs Gemini Flash for high-volume summarization? I