Developer Tools2 weeks ago
FlexInference: Drop your AI costs today
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
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Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
Automatically route each prompt to the cheapest capable model to cut API costs.
u/ASDKING100 · Reddit
Launched an AI API router tonight, and found a bug hours in that would've taken real payments without ever upgrading the account Built LLMLite over the past few weeks — it classifies each prompt and routes it to the cheapest model that can actually handle it, instead of hitting GPT-4o for everything. Free tier, no card needed to try it. Tonight, right as I was about to launch, ran a real transaction to test the payment flow end to end. Paddle processed it, webhook fired, signature verified
Compare and use multiple large 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
Generate llms.txt and MCP endpoints from any website URL for AI agent integration.
AshHackerNews · HN
AgentReady – MCP server that makes any docs site queryable by AI agents
Use one API to access and switch between LLM providers while optimizing inference costs.
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
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]
Tests LLM endpoints with adversarial cases and provides OWASP-mapped security audit reports.
@aryaan_sheth · X
- LLM security for small teams
Send your question to a panel of LLMs that peer-review each other and return one synthesized answer.
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree
Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X
API providing token-level citations for LLM output grounded in attention analysis.
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
Analytics dashboard for LLM API spending by model and environment with optimization suggestions.
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to
Compare latency and throughput across multiple LLM API providers.
@QAInsights · X