Speed to market in AI search
Product manager at Cohere on enterprise AI search infrastructure and deep research agents
The real opportunity here is speed to market, not durable monopoly. These companies are selling a cleaner pipe between the web and an AI agent, where the API returns usable text, citations, and structure instead of blue links that a developer still has to scrape and clean up. That is valuable right now because agent builders want working research workflows immediately, and the market for those workflows is expanding faster than the infrastructure is consolidating.
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The product difference is concrete but narrow. Tavily won usage at Cohere because it returned page text ready for grounding, while Brave required extra hops and transformation. Ecosia also found providers close on core quality, with service and integration speed mattering more than a hard technical edge.
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Parallel is pushing up the stack from search into full deep research. In Manus, it helps an agent map the problem first, then work through subtopics and assemble tables and reports over 10 to 15 minutes. That makes it better for meaty analyst style tasks, but it also means its value is tied to orchestration, not just raw retrieval.
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The category is growing anyway. Exa reached $10M annualized revenue by September 2025 and raised an $85M Series B led by Benchmark. Parallel has raised $130M. Tavily was significant enough that Nebius agreed in February 2026 to acquire it and fold search into its AI cloud stack, which shows buyers want this layer even if it is not deeply defensible.
Going forward, this layer will get pulled in two directions. Big platforms can absorb generic web search infrastructure, while independents will move toward domain specific data streams, proprietary connectors, and higher level research workflows. The winners will be the ones that become the default engine inside valuable agent products before the giants decide the market is worth owning.