Developer Tools1 month ago
ContextIQ — AI Context Engineering Suite for AI Engineers
Inspect RAG chunks and visualize AI agent workflows, memory architecture, and execution traces.
@Higgs0110 · X
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Inspect RAG chunks and visualize AI agent workflows, memory architecture, and execution traces.
@Higgs0110 · X
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
Create a personal context file that AI tools read before responding, portable across platforms.
@connorhpbrn · X
the garden for your context
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
API providing token-level citations for LLM output grounded in attention analysis.
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
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]
View LLM model rankings across 10 benchmark questions.
fristovic · HN
She watched me look at model rankings and asked what do the numbers mean... I literally had no good way of explaining it to her so I just came up with something that is approximately in the same ballpark as some of the benchmarks out there lol
Detect if your LLM API has been model-swapped or degraded with 6 deterministic probes.
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测：填入任意 OpenAI 兼容端点的 base_url 和临时 API Key，跑 6 项探针（模型声明、动态题、能力完整性等）生成分项报告；Key 仅用于当次检测、不落库不留存，检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)
Store shared memories once and reuse them across AI systems and your team.
Repeater22746 · HN
ContextVault – Shared memory layer for your AI and your team
Tests LLM endpoints with adversarial cases and provides OWASP-mapped security audit reports.
@aryaan_sheth · X
- LLM security for small teams
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
Use one API to access and switch between LLM providers while optimizing inference costs.
justin2025 · Product Hunt
Auriko Trading desk for LLM calls