TinyFish, a Palo Alto-based AI startup, has raised US$47 million in a series A round led by Iconiq Capital.

Other investors in the round include USVP, MongoDB Ventures, and Sandberg Bernthal Venture Partners.

Founded in 2024, TinyFish develops web-based AI agents to automate online tasks for enterprise clients in sectors such as retail and travel.

Its platform is designed to track prices, promotions, shipping times, and inventory levels on competitor websites, tasks that are often performed manually or with custom scripts.

The company plans to use the new capital to expand its product offerings and go-to-market operations.

TinyFish employs about 25 people and says the funding will support operations for the next three to four years.

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🔗 Source: Reuters

🧠 Food for thought

1️⃣ AI startups secure large funding despite broader market downturn

TinyFish’s $47 million Series A stands out significantly in today’s funding environment, where the median startup funding dropped to just $500,000 in 2023 2.

This massive difference, with TinyFish raising 94 times the median amount, illustrates how AI-focused companies can still attract substantial investor interest even as overall startup funding decreased significantly in 2023, continuing a trend from 2022 2.

The investment climate for generative AI specifically defied broader market trends, with investment projected to reach $42.6 billion by the end of 2023 and median pre-money valuations increasing 16% for early-stage generative AI companies 3.

This selective investor enthusiasm reflects what industry observers call a “fear of missing out” mentality around AI opportunities, leading to inflated valuations that contrast sharply with the 24% drop in valuations for non-AI startups 3.

2️⃣ Web agents address fundamental limitations of traditional data collection

TinyFish’s approach tackles a persistent problem that has plagued businesses for years: the unreliability and inefficiency of traditional competitive intelligence gathering.

The company specifically targets the replacement of “large, offshore teams performing manual data entry or custom software scripts that would often break when a website’s design changed,” highlighting how businesses have long struggled with fragile, labor-intensive data collection methods 1.

Traditional data collection methods are limited in scalability and often time-consuming, relying on manual processes that introduce human error and cannot handle the dynamic nature of modern websites 4.

This shift toward AI-powered web agents represents a significant change in how businesses can gather competitive intelligence, moving from reactive, brittle systems to proactive, adaptable automation that can handle the “dynamic and messy environment of the internet” at scale 1.

The validation from early customers like Google—who have substantial internal development resources to build similar tools themselves—suggests that even tech-savvy companies see value in specialized AI agent platforms over internal development 1.

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