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TinyFish Analysis: $47M Raised

What is TinyFish?

Most deployed enterprise web agent platform
Employees
11-50
Founded
2024
Valuation
$47.0M
Latest Funding Round Size
$47.0M

Product Features & Capabilities

  • Enterprise web agents for real-time data extraction
  • JobRight Autofill Agents for job applications
  • Local intelligence for ride-hailing demand prediction
  • Competitive analysis for e-commerce product matching
  • Continuous monitoring for hotel pricing and availability.

Use Cases

Automate job application processes to increase interview rates; Monitor real-time hotel pricing for better customer insights; Predict ride-hailing demand to optimize pricing strategies; Track competitor pricing and inventory for e-commerce; Extract structured data from conference websites for lead generation.

How much TinyFish raised

Funding Round - $47.0M

Recent

Other Considerations

Raised $47 million in funding; Trusted by major companies like DoorDash and ClassPass; Focused on delivering measurable outcomes at enterprise scale.

Trade Show Presence

TinyFish participated as a Level 2 sponsor at the Shoptalk Fall 2025 event, which will take place from September 29 to October 1, 2026, in Nashville. Their product, Mino, is described as an "agentic platform" that provides competitive and pricing intelligence using AI agents to capture real-time data on checkout prices and pricing variations.

Reported Clients

TinyFish has reported several notable clients on their website, including:
  1. DoorDash - They utilize TinyFish's platform to manage complex web interactions at scale, as noted by Abhi Shah, Director of Data Science.
  2. ClassPass - Jonathan Lam, Senior Program Manager, highlighted the measurable impact of TinyFish's AI agent solutions on their operations.
  3. Jobright.ai - TinyFish powers JobRight Autofill Agents, which significantly improve interview rates and reduce job search time.
  4. Amplemarket - TinyFish agents assist in automating lead intelligence extraction from conference websites.
These relationships involve leveraging TinyFish's advanced AI technology to enhance operational efficiency, streamline job application processes, and automate data extraction for lead generation.

Gtm Strategy

TinyFish employs a hybrid go-to-market (GTM) strategy that combines elements of both product-led growth (PLG) and sales-led approaches.

Upon analyzing TinyFish's website, it is evident that they prioritize user engagement through a demo request option prominently featured on the homepage, which suggests a sales-led approach to initiate contact with potential customers. However, there is no explicit mention of pricing, indicating that they may prefer to engage in discussions with interested parties rather than providing transparent pricing upfront. This aligns with a sales-led strategy, where personal interaction is key.

The absence of a "Start Free Trial" or "Sign Up" button suggests that immediate self-service access to the product is limited, which is a characteristic of PLG companies. However, the presence of a demo request indicates that they are also focused on guiding potential customers through a more structured sales process.

Customer testimonials on the site highlight the effectiveness of their solutions, which can foster trust and encourage adoption, a hallmark of PLG. However, the testimonials do not indicate viral adoption from individual users but rather suggest a more traditional sales cycle, which is indicative of a sales-led approach.

Additionally, while there are no extensive educational resources directly available on the site, the presence of a blog may provide insights and support for users, which is a common practice in PLG strategies to enhance user experience and self-service learning.

Overall, TinyFish's strategy reflects a blend of both PLG and sales-led growth, focusing on structured engagement through demos while also providing avenues for user education and feedback.

Find more companies like TinyFish

US Series A startups

Financial Overview

$47MTotal Raised
Funding Round$47.0M
Recent
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