무슨 일이 일어났나요?
Enso, an Israeli startup founded in 2024, has secured $15 million in Series A funding led by MoreTech Ventures. The company develops AI agents designed to help businesses maintain visibility across evolving digital platforms, including AI-generated search results from tools like ChatGPT and , as well as traditional search engines and social media.
Israeli startup Enso has raised $15 million in a Series A funding round led by MoreTech Ventures, with participation from NFX, Phenomen VC, and Gil Hirsch. This brings the company's total funding to $23 million. Enso was founded in 2024 by Mickey Haslavsky, a co-founder of RapidAPI.
The company develops AI systems that continuously experiment with ways to get companies in front of potential customers. Its agents monitor platforms like Google, LinkedIn, ChatGPT, and , run experiments on content and distribution, and measure the impact on visibility. This is distinct from traditional marketing software as it involves forward-deployed engineers and marketers working with customers to integrate these agents into existing operations.
Enso's approach, termed 'Agentic Growth Hacking' by Haslavsky, extends beyond AI search to include traditional search, sales outreach, online communities, newsletters, and social media. The company states that marketers retain control over strategy and brand guidelines, while agents handle repetitive monitoring and testing tasks. Sensitive or irreversible decisions remain under human control.
Current clients include Papaya Global, MyHeritage, Natural Intelligence, Winn AI, and Israel Canada. The company publishes research from its experiments, including failures, and maintains open-source reference tools. MoreTech Ventures' Zack Keinan noted that the opportunity lies in the lack of established playbooks for new growth channels that change faster than teams can adapt.
왜 중요한가요?
This funding highlights a growing industry shift toward 'agentic growth hacking,' where AI systems are used to adapt marketing strategies in real-time to changing algorithmic landscapes. As consumer discovery moves from traditional link-based search to synthesized AI answers, companies face new challenges in ensuring they are mentioned by these systems. Enso's approach combines automated experimentation with human oversight, addressing the need for continuous adaptation in a rapidly changing digital ecosystem.
The shift in consumer behavior from typing queries into search engines to asking AI assistants for synthesized recommendations creates a new visibility challenge for businesses. If a customer asks ChatGPT for recommendations, only a handful of companies may be named, making it critical for businesses to understand how to be included in these AI-generated answers.
Enso's funding signals investor confidence in the need for adaptive marketing tools that can keep pace with rapidly changing algorithms across both traditional and AI-driven platforms. The concept of using AI agents to monitor and test marketing strategies in real-time represents a significant evolution from static, periodic marketing analyses.
This development is part of a broader trend where AI is not only a tool for content creation but also a mechanism for understanding and influencing how that content is discovered. The practical implication is that marketing teams may increasingly rely on agentic systems to identify emerging opportunities and execute campaigns more efficiently.
대화형 메커니즘: 실제로 작동하는 방식
이 개발의 이면에 있는 기본 기술을 대화식으로 살펴보세요.
crm_get_transaction(id='4092').An agent must create a draft calendar event for Tuesday at 2 p.m. Which evidence would establish the requested result?
다음에 무엇을 볼 것인가
Monitor how Enso's AI agents perform in real-world scenarios, particularly their ability to influence AI-generated recommendations. Watch for broader adoption of similar agentic marketing tools by other startups and established marketing firms, as well as potential regulatory or ethical discussions around manipulating AI search results.
Observe whether Enso's AI agents can demonstrably improve a company's visibility in AI-generated search results compared to traditional SEO methods. Independent verification of their effectiveness will be crucial for broader adoption.
Watch for the emergence of competing solutions in the 'agentic marketing' space, as the success of Enso's model may attract other startups and established marketing technology companies to develop similar AI-driven optimization tools.
Monitor potential ethical and regulatory discussions around the use of AI agents to manipulate or optimize visibility in AI-generated search results. As these systems become more prevalent, questions about fairness, transparency, and the integrity of AI recommendations may arise.