The Gold Standard for AI in Finance
Charli started as a simple, yet powerful idea in 2018 to develop a ‘chief of staff’ that gives people more time by automating complex, repetitive tasks. From the outset Charli needed to be capable of handling complex, data-driven challenges and intelligently designed to not just be a tool, but an extension of human capability.
Coordinated Models: The Backbone of Charli’s AI Ecosystem
The team at Charli came out of the world of Digital Twins and were very familiar with the challenges of building, configuring, and maintaining complex AI systems that needed to be continuously monitored and controlled. “At Charli AI, it’s not about simply having a lot of data but curating the right data to solve specific challenges—just as Digital Twins rely on highly specialized models working in harmony,” says Joel Emery, CPO and Co-Founder at Charli AI. This background generated a wealth of knowledge and set the groundwork for Charli’s intelligent and unique workflow (now commonly referred to as Agentic Workflow).
AI is dependent upon data, and to scale AI there needed to be a method that could capture and make sense of a massive amount of diverse data. This required advanced methods and intelligence to auto curate the data and continuously train and test AI models for production readiness. Not just a single AI model, but any number of AI models that were involved in a complex process. As Joel explains, “We’ve always believed it’s not about the quantity of data—it’s how the data is processed, curated, and applied that makes the difference.”
Taming AI Complexity with Intelligent Workflows
Digital Twins are a complex ecosystem with many different models required to analyze and process inputs from across a broad spectrum of data that is both structured and unstructured. The Charli AI team’s experience in managing Digital Twins gave them the expertise to streamline these processes.
Much like digital twins, AI consists of hundreds if not thousands of models that must be Coordinated and managed efficiently, a task that can be both time consuming and expensive. Charli set out to ‘tame’ this complexity.
The Charli platform operates more than 100 AI models that work simultaneously to handle tasks such as data processing, extraction, classification, categorization, normalization, interpretation, analysis, and many more intelligent processes. The result? Professionals no longer need to sift through endless market reports and filings.
“AI isn’t just about the amount of data—it’s about how you use it,” says Joel Emery. “We curate and apply data intelligently, enabling professionals to make better decisions faster.” Charli’s architecture ensures that AI isn’t just generating insights but cross-referencing and fact-checking them in real time to maintain accuracy.
Charli leverages the latest in AI techniques, including transformer architectures, alongside highly optimized open-source large language models (LLMs). Our AI models are a combination of proprietary designs, as well as designs in collaboration with academia and the open-source community. We design, build, and maintain over 70% of the models within the Charli ecosystem; and we highly optimize open source LLMs to work in concert with the network of models to provide accurate well written results.
Contrary to the hype surrounding AI and GPT, the true intelligence of an AI system does not lie in the LLM. The intelligence of Charli is a result of the coordinated network of models that can effectively break-down complex problems, much like humans do, into manageable steps. Charli applies advanced multi-modal analysis, rich contextual cross-retrieval augmentation, and a diverse network of data extractors to arrive at accurate outcomes.
Our models are designed, tuned, and continuously trained and tested to operate in the complex world of financial services. They are domain specific and understand the nuances of the ‘finance’ vernacular.
Data Security: The Foundation of Trust
In financial services, security is paramount. As Kevin, CEO and Co-Founder of Charli AI, notes, “Our goal is to set the gold standard for secure and reliable AI. Every decision the system makes is traceable, auditable, and explainable—even years later.”
In a world where AI systems often operate as “black boxes,” Charli’s auditable and explainable AI ensures clients and regulators can trust the system’s outcomes. Furthermore, Charli goes to great lengths to fully containerize the AI ecosystem so that data remains private and protected. Even questions and interrogation of the AI system are secured from prying eyes so that our customers do not leak their intellectual capital. Our goal for Charli is not just Responsible AI — it is setting the Gold Standard for Secure, Reliable and Trusted AI.