Every team evaluating Linkup asks the same first question: how do you perform against LLM native search and the competition? Fair question. On public benchmarks, we lead: SimpleQA and SealQA-0, state of the art. But raw accuracy only tells you so much. That's why we launched verticalized benchmarks that map to real use cases: GTM (People, Company), Legal (RedlineBench), Finance (FinSearchComp). Each links to an open repo with the dataset, queries, and methodology. Re-run it yourself. But what really matters is what works for you. Picking a provider on a public leaderboard alone is how you end up with failures in production: a benchmark measures general performance, not yours. So we go one step further and help you build a custom eval on your own queries and data, guide included. Public benchmarks show who leads in general. A custom eval shows who leads for you.

High-reliability inference needs high-performance retrieval.

@hcompany_ai is building one of the most advanced computer-use agent platforms in Europe.

The @Linkup_platform team is in London for one of the most exciting builder events of the summer: @unicorn_mafia’s Hardware Hackathon, alongside @AnthropicAI, @ElevenLabs, and @modal.