Captide is reshaping how financial institutions build with AI, offering a full-stack platform that makes it easy to deploy multi-agent systems, embed intelligence across financial workflows, and extract insights from millions of corporate filings—without the overhead of building and managing complex RAG infrastructure.
At the foundation is Captide’s curated library of global financial disclosures from over 14,000 public companies, preprocessed and structured for optimal use with large language models. On top of this, Captide has built domain-specific AI agents that read, interpret, and reason over this data—augmenting a wide range of high-value tasks, from investment research to equity modeling.
These agents don’t just extract information, they make use of all authoritative sources to automate workflows that once took hours or days. With exceptional precision, speed, and contextual understanding, Captide’s systems are trusted by leading asset managers, investment banks, and global institutions to enhance decision-making at scale.
Powered by the LangChain ecosystem, Captide enables real-time exploration of investment theses, corporate events, peer comparisons, M&A signals, and more.
Scaling with LangGraph Platform
Captide agents are used in a range of use cases—from answering sequential questions on company filings to powering spreadsheet-like setups that require large-scale parallel invocations to populate cells with metrics and insights. To ensure reliability and scalability across use cases, Captide agents are deployed on LangGraph Platform. LangGraph Platform ensures the service scales effectively with request volume and provides built-in tools for saving and recalling the state of an agent's execution within each session. This ensures agents remain consistent, responsive, and context-aware at scale.
In spreadsheet-style applications, Captide agents may be triggered simultaneously across thousands of cells, each with different parameters. This results in a high volume of concurrent tasks in a point of time. LangGraph automatically scales infrastructure up or down to meet these demands, ensuring stable, efficient performance regardless of load.
Deploying on LangGraph Platform has also enabled Captide’s product team—finance domain experts—to actively shape agent behavior. With access to LangGraph Studio’s low-code interface, they can iterate quickly on prompts and agent design, bringing client feedback and industry knowledge directly into the loop. This frees the engineering team to focus on the agent set up and architecture and provides a level of agility to the product team that wouldn’t be possible with more traditional setups.
Observability and Reliability with LangSmith
Captide’s AI agents operate within a sophisticated orchestration framework, breaking down complex tasks, coordinating multiple tool calls, and ensuring transparency at every step. To maintain high performance and control, Captide relies on LangSmith to make every agent decision fully observable, testable, and verifiable. With LangSmith, the team can trace responses end-to-end, while closely monitoring cost, accuracy, and latency.
LangSmith also plays a critical role in maintaining quality over time. Captide sets up evaluations that test both common and edge-case user requests recurrently, scoring the agent’s responses to catch issues before they surface. It’s a continuous feedback loop that ensures every deployment is smarter, faster, and more resilient than the last.
Bringing in Generative UI into Captide
To serve investment teams seeking powerful tools with minimal technical overhead, Captide has recently launched an interface that provides immediate access to its core technology. Through natural language alone, analysts can perform complex equity research, benchmark companies, and validate investment theses, powered by Captide’s AI agents.
To bring this experience to life, Captide built the platform using LangGraph’s generative UI technology. This allows AI agents to push interactive React components from the server directly into the user interface. Each component is uniquely identified and bundled by LangGraph Platform, then loaded dynamically as the conversation unfolds. The result is a responsive, modular experience where the interface adapts in real time to the user’s requests and the agent’s research path.
One of the most powerful aspects of this design is the visibility it offers. In Captide’s implementation, users don’t just see the final answer–they see the entire thought process. As the agent works through a request, the interface streams updates on the steps it’s taking, which sources it’s checking, and what it’s finding along the way. This matters because no two queries follow the same path—researching an M&A deal is very different from benchmarking companies, and Captide’s clients expect transparency into every step. For example, if someone asks about a past acquisition, the system recognizes the task, pulls relevant documents from a massive library of filings and disclosures, and surfaces key excerpts. All of this is shown to the user in real time, making the research traceable and auditable from start to finish.
Conclusion
Captide brings the full potential of agentic AI directly into the hands of financial analysts and decision-makers. With LangGraph and LangSmith powering everything under the hood, the platform scales effortlessly, stays reliable under pressure, and offers complete visibility into every step of the process. The result is a smarter, more intuitive way to research, reason, and act—setting a new standard for how AI supports financial workflows.