How Lightsage uses TinyFish to make customer onboarding 30% faster. DLDivya Lath, GTM + Product · Oct 22, 2026 At a glance. * Company: Lightsage is the Agent-Led Growth platform that shows developer tools how coding agents like Claude Code and Codex discover, evaluate and use them, and what to fix * Use case: Auto-generating each new customer's competitor list during onboarding, then tracking those competitors over time * Why TinyFish: Speed, accuracy, and hundreds of parallel runs at a cost that works for every signup * TinyFish products: Search, Fetch * Headline number: 30% faster customer onboarding Company overview. AI agents are becoming software buyers. Coding agents now pick libraries, install SDKs, and call APIs for their users, often without a human ever landing on a homepage. Lightsage helps software companies see how those agents find their product, where integrations break, and why an agent chose someone else. The platform covers Agent Discovery across coding agents and answer engines, Agent Usability evaluations across APIs, SDKs, CLIs, MCP servers, and skills, and Agent Analytics on where agents go and where they fail. Customers include Reducto, Daytona, Rime, Firecrawl and TinyFish. Lightsage raised a $4M seed round led by Nexus Venture Partners in September 2026. Every one of those analyses starts with one question: who are you being compared against? That's where TinyFish comes in. The problem. Lightsage needs a competitor list before it can show a new customer anything useful. Agent visibility is relative. "Claude Code recommends you 40% of the time" only means something next to who it recommends the other 60%. Asking customers to type in competitors slows onboarding and misses the ones they don't know about. Building lists by hand doesn't scale. So Lightsage generates the list automatically at signup, which means running live web searches for every new account. That puts three demands on the search layer: fast enough to feel instant, accurate enough to be right the first time, and cheap enough to run for every signup, free ones included. Lightsage needed competitor lists accurate enough to skip a manual check. Why Lightsage built on TinyFish. "TinyFish is cost-effective and scales easily to hundreds of parallel runs. The results are noticeably more accurate than what we used before, and we had it running in production in an afternoon." Jun Liang Lee, CEO, Lightsage Accuracy. For a feature whose whole output is "here's who you compete with," accuracy is everything. Jun rated the results noticeably more accurate than previous providers. Speed and scale. TinyFish Search is low latency and runs hundreds of searches in parallel, so competitor discovery finishes in seconds even when many customers sign up at once. That keeps the onboarding flow moving instead of waiting on search. Cost. The price works at signup volume, even for free accounts. Setup time. Under a day, comfortably inside one afternoon. TinyFish's docs are built for agents: the team copied prompts straight into Claude Code and used the code examples to wire everything up. Where TinyFish fits. A new customer enters their product. Lightsage calls TinyFish Search to find who else solves the same problem, uses Fetch to read those pages, and generates the competitor set before onboarding is done. The same layer then powers ongoing competitor tracking, so the list stays current as the market moves. | Need | Lightsage | TinyFish | | Who competes with this product? Turns results into the competitor set | Search finds current, accurate sources; Fetch reads them | | Do it at signup speed | Runs inside the onboarding flow | Low latency, fast enough to feel instant | | Do it for every signup | Handles signup spikes | Hundreds of parallel runs | | Keep it current | Tracks competitors over time | Fresh results from the live web | Key outcomes. * 30% faster customer onboarding. Onboarding went from about 22 seconds to about 15. Low-latency, parallel search means competitor discovery no longer slows down signup. * Live in one afternoon, using agent-ready docs and code examples. * Noticeably more accurate results than previous providers. * Hundreds of parallel runs at a cost that works for every signup. * 4 out of 5 on how much difference TinyFish has made. What's next. Lightsage plans to push more of onboarding through TinyFish and bring TinyFish Search into its AI chat features. See where your API ranks on DevTool Arena, Lightsage's free, public coding-agent benchmark. Read Lightsage's side of the story: "Who Are You Being Compared To?" (coming soon) Building a product that needs to know the market in real time? AI disclosure

Lightsage has raised $4 million in seed funding to help software companies sell their products to autonomous AI agents. The round was led by Nexus Venture Partners, with participation from angel investors including Postman CEO Abhinav Asthana and former Salesforce CTO Steven Tamm. The startup has introduced "agent-led growth", running simulations across multiple coding agents to help software firms understand how AI tools discover and choose products. Lightsage assigns agents real-world integration tasks, measures software visibility against competitors, and identifies issues like confusing documentation or broken API endpoints that prevent successful outcomes. The platform provides analytics on agentic traffic and insights into which agents use software, for which tasks, and how often. Currently focused on developer software, Lightsage plans to expand into business software, cloud infrastructure, and automated payments.