Telem – Route agent web search across providers and inspect the traces
TL;DR: Web search open router that routes agent web search across providers (Exa, Parallel, Tavily, Brave, SerpAPI etc.), and traces web search results with quality metrics, so you can visualize whether a bad agent run is a web search problem or a reasoning problem. I work in venture capital, and before that I worked in information retrieval. When agents went viral, I built a due diligence agent for my day job. I vibe-coded the first version. It was pretty bad. My first reaction is to blame the model. I tried to change backend models, maybe because Fable doesn't want to help me do people…
What it does
Telem AI builds infrastructure for AI agents: web search routing, web fetch routing, and agent observability.
One API across search providers. Route each agent query to the best engine by cost, latency, and answer quality — with automatic failover when a provider degrades. Resilient page retrieval for agents. Rendering, retries, and clean extraction handled for you — hand your model readable content, not raw HTML. See what your agents actually do. Traces, traffic, and judged quality metrics across every project — live in the Telem console today. Drop-in APIs with sane defaults. Point your agent at one endpoint, get routing, retries, and telemetry without changing your stack. Simple pricing 03 / Pricing ZERO additional charge. Unlike the OpenRouter business model, you pay the…from telem.ai
In the maker’s words, at launch
TL;DR: Web search open router that routes agent web search across providers (Exa, Parallel, Tavily, Brave, SerpAPI etc.), and traces web search results with quality metrics, so you can visualize whether a bad agent run is a web search problem or a reasoning problem. I work in venture capital, and before that I worked in information retrieval. When agents went viral, I built a due diligence agent for my day job. I vibe-coded the first version. It was pretty bad. My first reaction is to blame the model. I tried to change backend models, maybe because Fable doesn't want to help me do people search? Maybe because GPT 5.5 overthinks things? I tried DeepSeek, Kimi, Qwen; I changed prompts again and again, no good. Then I stopped just simply checking the final answer and started reading the actual trajectories: what did the agent search for? What came back? What pages did it read? At what point agents were off the rail? Pretty interesting: Sometimes the agent is stuck and confused because the information provided is irrelevant or even wrong; Sometimes the agent keeps iterate the same query, like "XXX lab UCB CS PhD founder 2026" "2026 XXX lab machine learning systems students startup" because the web search provider is not up-to-date; Sometimes sub-agents give up too early because the agent's intelligence is not enough or too "guardrailed"; Sometimes everything is just slow. A run jeopardized at minute 1 but still ran for another 10 before returning nonsense. That's because of bad searches, but nothing reveals it. So I built two things: 1. Web Search/Fetch router: One gateway for Exa, Parallel, Tavily, Brave, Ceramic, Linkup, Seltz, You, SerpAPI, etc. You or your agent can pick one or query several concurrently, and the responses come back in a homogeneous format. 2. Web Search Observability: Trace every search your agent (and its sub-agents) makes with an evaluator scoring relevance, diversity, and a few other things. Point is to answer one question: is your pipeline broken because the web search is bad? If so, where? Everything is agent-operated. All u need to do is to run this shell script: <curl -fsSL https://docs.telem.ai/alpha_install.sh | sh> Please give it a try, any feedback/suggestion would be great! Especially I’d like to ask: how are you debugging search/retrieval failures nowadays?
Does the same job
all alternatives →
The new Firecrawl /searchJul 2026 · docs.firecrawl.dev · ▲257Our most accurate Search API for AI agents.
- ALAirweave – Let agents search any app2025 · github.com · ▲176
Hey HN, we're Lennert and Rauf. We’re building Airweave (https://github.com/airweave-ai/airweave), an open-source tool that lets agents search and retrieve data from any app or database. Here’s a general intro: https://www.youtube.com/watch?v=EFI-7SYGQ48, and here’s a longer one that shows more real-world use cases, examples of how Airweave is used by Cursor (0:33) and Claude desktop (2:04), etc.: https://youtu.be/p2dl-39HwQo A couple of months ago we were building agents that interacted with different apps and were frustrated when they…
- INIndex – New Open Source browser agent2025 · github.com · ▲98
Hey HN, Robert from Laminar (lmnr.ai) here. We built Index - new SOTA Open Source browser agent. It reached 92% on WebVoyager with Claude 3.7 (extended thinking). o1 was used as a judge, also we manually double checked the judge. At the core is same old idea - run simple JS script in the browser to identify interactable elements -> draw bounding boxes around them on a screenshot of a browser window -> feed it to the LLM. What made Index so good: 1. We essentially created browser agent observability. We patched Playwright to record the entire browser session while the agent operates,…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com