This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Liner helps developers build AI apps with search agents and lower-cost search tools. Add web search, academic search, cited answers, deep research, and visual answers to your product. Web Search starts at $1 / 1K requests — 1/10 of OpenAI’s public web search tool-call price.
I’m Stellar from Liner. Today we’re launching Liner Developer Platform, search agents for AI products, plus lower-level tools for teams that want to build their own workflows.
Most AI apps need more than model memory. They need to search fresh sources, cite evidence, research complex questions, and sometimes explain the answer visually.
Liner gives developers two ways to build that:
Agents 🔎 Search Agent — searched answers with citations and source evidence ⚡ Quick Answer Agent — fast, lightweight cited answers 📄 Deep Research Agent — multi-step research reports 📊 Visual Answer Agent — answers with interactive visuals
Tools 🌐 Web Search — structured web results 📚 Academic Search — scholar results and paper metadata 🧩 Visualization — turn queries into embeddable HTML visuals
We’d love feedback from people building AI search apps, copilots, agents, RAG workflows, and research tools.
Question for builders: would you rather start with a ready-made search agent, or use lower-level search tools and build the answer flow yourself?
Search costs are a real line item when you're running agents at scale - the OpenAI web search pricing adds up fast once you get past toy usage. $1/1K requests with cited answers is the kind of pricing that actually makes grounded AI features worth shipping. Curious how latency compares on the academic search vs the web search endpoints.
This api is amazing. I’m using this for my personal project, and I really appreciate for this great product! Thank you liner team!
About Liner Developer Platform on Product Hunt
“Build search agents with 10x cheaper web search”
Liner Developer Platform was submitted on Product Hunt and earned 41 upvotes and 5 comments, placing #20 on the daily leaderboard. Liner helps developers build AI apps with search agents and lower-cost search tools. Add web search, academic search, cited answers, deep research, and visual answers to your product. Web Search starts at $1 / 1K requests — 1/10 of OpenAI’s public web search tool-call price.
Liner Developer Platform was featured in Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and Search (18.1k followers) on Product Hunt. Together, these topics include over 183.6k products, making this a competitive space to launch in.
Who hunted Liner Developer Platform?
Liner Developer Platform was hunted by Stellar Kang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Liner Developer Platform stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Stellar Kang
Hey Product Hunt 👋
I’m Stellar from Liner. Today we’re launching Liner Developer Platform, search agents for AI products, plus lower-level tools for teams that want to build their own workflows.
Most AI apps need more than model memory. They need to search fresh sources, cite evidence, research complex questions, and sometimes explain the answer visually.
Liner gives developers two ways to build that:
Agents
🔎 Search Agent — searched answers with citations and source evidence
⚡ Quick Answer Agent — fast, lightweight cited answers
📄 Deep Research Agent — multi-step research reports
📊 Visual Answer Agent — answers with interactive visuals
Tools
🌐 Web Search — structured web results
📚 Academic Search — scholar results and paper metadata
🧩 Visualization — turn queries into embeddable HTML visuals
We’d love feedback from people building AI search apps, copilots, agents, RAG workflows, and research tools.
Question for builders: would you rather start with a ready-made search agent, or use lower-level search tools and build the answer flow yourself?