The rapid development and deployment of artificial intelligence (AI) models have created a competitive landscape where businesses must continually adapt to stay ahead. According to a recent report, nearly 10% of companies plan to spend a staggering $25 million on AI initiatives this year alone. However, with great investment comes great uncertainty: half of all AI leaders struggle to calculate or demonstrate the value of their projects.
The Challenge of Measuring ROI
Gartner’s findings highlight the complexity of measuring return on investment (ROI) in AI. With so many new models emerging weekly and significant resources being poured into them, it’s challenging for businesses to evaluate their effectiveness. This is where experimentation platforms like Eppo come into play.
Eppo: A Game-Changer in AI Experimentation
Co-founded by ex-Airbnb data scientist Chetan Sharma, Eppo offers a comprehensive platform for evaluating and customizing AI models for specific use cases. Beyond its model evaluation suite, Eppo provides a general A/B testing platform and service for apps and websites.
A Cost-Effective Approach to Evaluating AI Models
Sharma emphasizes the importance of A/B testing in evaluating AI effectiveness without overspending: "With new AI models launching weekly and companies pouring millions into them, A/B testing offers a cost-effective way to evaluate their effectiveness without breaking the bank."
Eppo’s contextual bandit system is a key differentiator in the market. This feature automatically spots new variants of customers’ websites, apps, or AI models and actively explores their performance by serving increasing load or traffic.
Accelerating Growth through Experimentation
Sharma explains that experimentation drives velocity and accelerates growth by stripping away bureaucratic decisions while tightly tethering initiatives to growth metrics: "Experimentation answers whether premium models improve metrics. It’s a game-changer for companies looking to optimize their AI investments."
Enterprise Adoption and Funding
Eppo has gained significant traction in the market, with several hundred enterprise customers on board. Perplexity, a leading language model, credits Eppo with allowing them to significantly scale the number of experiments they run concurrently.
The company’s recent $28 million Series B round, led by Innovation Endeavors, values Eppo at $138 million post-money and brings its total raised to $47.5 million. Sharma plans to use this funding to bolster marketing efforts, enhance analytics offerings, and scale go-to-market initiatives.
A Rising Need for AI Experimentation
The demands of efficient growth combined with the rise of AI have created an "adapt-or-die" mentality in the market. Legacy vendors are often unable to meet the evolving needs of companies, leading them to staff large in-house teams or build their own solutions. However, these in-house efforts are becoming unsustainable due to employee movement and layoffs.
Conclusion
The AI industry’s rapid evolution creates a complex landscape where businesses must navigate ROI uncertainty. Experimentation platforms like Eppo offer a cost-effective solution for evaluating AI effectiveness. With its contextual bandit system and focus on A/B testing, Eppo stands out as a game-changer in the market. As companies continue to invest heavily in AI, the need for robust experimentation tools will only grow.
