The world is abuzz with the potential of Artificial Intelligence (AI) and the powerful Large Language Models (LLMs) that drive them. From revolutionizing customer service to streamlining complex business processes, the possibilities seem endless. However, the reality is that LLMs, for all their impressive capabilities, can be frustratingly unreliable. This inconsistency poses a significant challenge for enterprises eager to integrate AI into their operations. Enter Composo, a London-based startup aiming to bring much-needed order and reliability to the chaotic landscape of enterprise AI.
Composo is tackling the critical issue of LLM performance monitoring. While LLMs hold immense promise, their unpredictable nature can create significant headaches for businesses. How can companies ensure that the AI-powered applications they invest in are actually delivering the desired results? How can they measure accuracy, consistency, and overall quality? These are the questions Composo is designed to answer.
Composo distinguishes itself in a crowded market by offering a unique combination of a no-code platform and a robust API. This dual approach democratizes access to AI evaluation, allowing both technical and non-technical users to assess the performance of LLM-powered applications. Domain experts, business executives, and developers alike can leverage Composo's tools to gain valuable insights into the behavior and effectiveness of their AI investments.
The Composo Approach: Combining Reward Models and Custom Criteria
Composo's core technology revolves around a sophisticated system that blends a reward model with custom criteria tailored to specific applications. The reward model, trained on human preferences for AI outputs, provides a baseline for evaluating the quality of LLM-generated content. This baseline is then augmented with a set of criteria defined by the client, reflecting the unique requirements and objectives of their particular AI application.
Imagine a medical triage chatbot. A healthcare provider can use Composo to establish custom guidelines for identifying critical symptoms. Composo then evaluates the chatbot's performance against these guidelines, scoring its consistency in identifying potential red flags. This allows healthcare professionals to confidently assess the reliability of the AI tool and identify areas for improvement.
Composo recently launched a public API for Composo Align, a powerful model designed to evaluate LLM applications based on any user-defined criteria. This API opens up a world of possibilities for developers and businesses looking to integrate robust AI evaluation into their workflows.
Early Success and Strategic Growth
Composo's innovative approach has already garnered attention from industry giants like Accenture, Palantir, and McKinsey, all of whom have become clients. The company recently secured $2 million in pre-seed funding, a testament to the growing demand for reliable AI evaluation solutions. While the funding amount might seem modest compared to the massive investments flowing into the AI sector, Composo's co-founder and CEO, Sebastian Fox, explains that their strategy is not capital-intensive.
"For the next three years at least, we don’t foresee ourselves raising hundreds of millions because there’s a lot of people building foundation models and doing so very effectively, and that’s not our USP," Fox, a former McKinsey consultant, stated. "Instead, each morning, if I wake up and see a news piece that OpenAI has made a huge advance in their models, that is good for my business.”
Composo's focus is on leveraging the advancements in foundation models and building a robust evaluation platform. The newly acquired funding will be strategically deployed to expand the engineering team, led by co-founder and CTO Luke Markham, a former machine learning engineer at Graphcore, acquire new clients, and further bolster research and development efforts. "The focus from this year is much more about scaling the technology that we now have across those companies," Fox emphasized.
Addressing the Enterprise AI Bottleneck
Composo's mission is to address a critical bottleneck in the widespread adoption of enterprise AI. While the initial hype surrounding AI has been significant, businesses are now grappling with the practical challenges of implementation. Many organizations are hesitant to fully embrace AI due to concerns about reliability, consistency, and the ability to demonstrate tangible value.
"People are over the hype of excitement and are now thinking, ‘Well, actually, does this really change anything about my business in its current form? Because it’s not reliable enough, and it’s not consistent enough. And even if it is, you can’t prove to me how much it is,’” Fox explained.
Composo is bridging this gap by providing companies with the tools they need to confidently deploy and manage AI applications. By offering a reliable and transparent evaluation framework, Composo empowers businesses to overcome their hesitations and unlock the true potential of AI.
Industry Agnostic Approach and Competitive Advantages
Composo has adopted an industry-agnostic approach, recognizing that the need for reliable AI evaluation spans across various sectors. However, the company has seen particularly strong interest from organizations in compliance, legal, healthcare, and security, where the stakes of AI failures are particularly high.
Composo believes its competitive moat lies in its unique combination of technical expertise, data assets, and strategic focus. Fox highlights the significant research and development efforts that have gone into building Composo's platform. "There’s both the architecture of the model and the data that we’ve used to train it," he said, explaining that Composo Align was trained on a "large dataset of expert evaluations."
Furthermore, Composo benefits from a first-mover advantage and the accumulation of valuable data over time. As the platform continues to evolve, it gathers increasing amounts of information about evaluation preferences, further strengthening its ability to provide accurate and relevant assessments.
Navigating the Evolving AI Landscape
Composo is well-positioned to navigate the rapidly evolving AI landscape, including the rise of agentic AI. The company's flexible approach to evaluation, based on user-defined criteria, makes it adaptable to the increasing complexity of AI applications. While Fox acknowledges that agentic AI is still in its early stages, he believes that Composo's technology is ideally suited to address the challenges of ensuring reliability and consistency in this emerging field. "In my opinion, we are definitely not at the stage where agents work well, and that’s actually what we’re trying to help solve," Fox said.
The Future of AI Evaluation
Composo's vision extends beyond simply evaluating existing AI applications. The company aims to play a key role in shaping the future of AI development by providing developers with the tools they need to build more reliable and trustworthy AI systems from the ground up. By fostering a culture of continuous evaluation and improvement, Composo is contributing to the creation of a more robust and dependable AI ecosystem.
In conclusion, Composo is tackling a crucial challenge in the world of enterprise AI. By providing a powerful and accessible platform for evaluating LLM performance, Composo is empowering businesses to confidently embrace the transformative potential of AI. As the AI landscape continues to evolve, Composo's focus on reliability, transparency, and adaptability positions it as a key player in shaping the future of AI adoption.
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