RapidCanvas Raises $16M to Revolutionize Data Science with AI Agents

RapidCanvas raises $16M to streamline data science projects with AI agents - SiliconANGLE

Data science startup RapidCanvas Inc. today announced that it closed a $16 million funding round led by Peak XV,. Titanium Ventures, Accel and Valley Capital Partners also contributed to the investment, which brings the company's total raised since launch to over $23.5 million. RapidCanvas was founded in 2021 by Chief Executive Officer Rahul Pangam and Chief Technology Officer Uttam Phalnikar. The duo previously launched Simility Inc., a fraud detection startup that was acquired by PayPal Holdings Inc. in 2018. RapidCanvas' namesake software platform promises to automate repetitive data science tasks using artificial intelligence agents. Those are large language models customized to a specific use case. According to the company, its agents can automate up to 75% of the tasks involved in data science projects. The first phase of an analytics initiative focuses on collecting the data that users wish to process. RapidCanvas provides more than 500 integrations for pulling records from cloud storage services, databases and other information sources. If a connector isn't avaialble for a system, customers can generate a new one with the-built AI. A drag-and-drop interface allows users to prepare data for analysis without writing code. RapidCanvas can organize records from different sources into a common file format, remove duplicate items and filter errors. It's possible to modify data in other ways as well. A worker could, for example, replace a list of product prices with one average price to streamline processing. RapidCanvas also lends itself to feature engineering. This is the process of organizing data into a form that is easier for AI models to understand. After completing the initial preparatory work, customers can create multiple versions of the finalized dataset. One version can be used to train AI models while another could be turned into a benchmark for comparing the AI models' accuracy. A built-in chatbot automates the coding usually involved in such tasks. Besides AI models, RapidCanvas can also create data visualizations. A what-if analysis tool allows users to search the data visualized in a graph for new patterns. RapidCanvas' core feature set is complemented by administrative tools that make it to easier manage deployments of the software. Access controls regulate who can access what feature based on employees' roles. Under the hood, an autoscaling feature adjusts infrastructure usage based on workload requirements.

AI Agents Startup RapidCanvas Secures $16M to Address Technical Talent Shortage

RapidCanvas estimates that 70% of the nearly $1 trillion in global salaries paid to software engineers and data scientists could be optimised with AI. Austin-based RapidCanvas has announced a $16 million Series A funding round to advance its AI agents, which can automate up to 75% of complex tasks traditionally handled by data scientists and engineers. The round, led by Peak XV Partners with participation from Titanium Ventures, Accel, and Valley Capital Partners, brings the company's total funding to $23.5 million since its inception in 2021. RapidCanvas aims to address the global shortage of technical talent by offering a "Service-as-Software" model that integrates AI agents with human expertise. These AI agents, powered by LLMs, perform tasks such as data processing, pattern recognition, and decision-making at high speed and scale. The hybrid approach allows businesses to reduce reliance on technical talent, requiring only one or two expert engineers for tasks that typically need larger teams. The platform is particularly effective in coding-related tasks, where AI agents automate up to 70% of routine operations, freeing experts to focus on high-value work. RapidCanvas estimates that 70% of the nearly $1 trillion in global salaries paid to software engineers and data scientists could be optimised with AI, enabling enterprises to unlock faster ROI and business growth. The company's co-founders, Rahul Pangam and Uttam Phalnikar, come from an experience of working in AI-powered business transformation space, and have previously built Simility, a risk management platform acquired by PayPal. The company's Reliable AI framework ensures validated, secure, and explainable outputs, enabling businesses to implement AI solutions faster and at a fraction of the cost of traditional methods. Unlike traditional Software-as-a-Service (SaaS) tools that improve employee productivity, RapidCanvas links software costs directly to business outcomes, marking a shift in automation's potential. The startup claims that early customers have reported consistent value across diverse use cases, showcasing the platform's scalability and efficiency. With this funding, RapidCanvas is set to accelerate AI adoption across industries, helping enterprises overcome the technical talent gap and achieve tailored AI solutions that drive growth and profitability. Observing the current trend, AI agents seem to be a hot trend with a number of big tech companies and startups building them. Aampe, an AI startup, headquartered in North Carolina, is building agentic infrastructure to provide personalised experiences for product and marketing teams. The startup raised $18 million in Series A financing, and will reveal that 100 million AI agents are being used in their consumer apps.

How RapidCanvas automates 70% of data tasks for gen AI projects

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Ever since ChatGPT emerged, enterprises have been all about AI and how it can help them address critical business challenges. It all started with large language model (LLM)-powered chatbots and search tools, which allow users to find answers and insights quickly. But the trend has now shifted to compound AI agents -- systems capable of performing multi-step reasoning and handling tasks like support ticket management, responding to emails and making reservations. Salesforce triggered the wave of AI agents with the announcement of AgentForce a few months back. Now, these systems are moving deeper into the enterprise stack. Case in point: RapidCanvas, a Texas-based startup, claims its context-aware AI agents can automate 70% of data tasks during custom AI deployment. The company has raised $16 million in series A capital to further accelerate the expansion of its agent-based platform. In fact, enterprises such as PayPal, Suzlon and MTE Thomson are already using it across their workflows, accelerating the time to value by ten-fold and reducing the implementation costs by as much as 80%. RapidCanvas AI agents address AI deployment bottlenecks When executing an AI project, organizations are often bogged down by tech the talent shortage (due to high demand). Even if they manage to hire skilled engineers or external consultants, those teams have to spend a lot of time on coding and data science tasks -- from integrating data assets, to preparing, transforming and modeling them, to productionize downstream use cases. This stretches out implementation by several months, affecting ROI and business growth. To fix this, former PayPal executives Rahul Pangam and Uttam Phalnikar -- who handled risk strategy and architecture -- teamed up to launch RapidCanvas. "Our goal with RapidCanvas is to revolutionize how businesses build reliable, customizable AI solutions without requiring teams of technical experts; our platform empowers business and operations teams by using a hybrid approach combining AI Agents and an expert in the loop," Pangam told VentureBeat. At the core, RapidCanvas' platform provides enterprises with content-aware AI agents that can be prompted in natural language to handle several data engineering and science tasks, from data ingestion, orchestration and preparation to enabling analytics, applications, pipelines, automation and modeling. According to Pangam, agents execute these tasks on behalf of users by enriching their prompts with contextual information gathered directly (business terminologies fed by users) as well as from connected systems (CRMs, data platforms, support ticket systems). It also takes into account the problem the user is trying to solve, as well as context gathered from previous projects to ensure the task is optimally run. This, Pangam says, enables enterprises to handle up to 70% of data tasks faster and more cost-effectively than humans. And, they can use the prepped data in combination with a visual canvas to deploy the application in question. But here's the catch. While the offering reduces the dependency on technical talent, such as data engineers, it does not eliminate their need. The remaining 30% of the job in the workflow -- covering aspects like system design, hypothesis testing and problem-solving -- goes to human experts. Pangam says a company that may have previously employed 10 expert engineers would just need one or two when using RapidCanvas agents to build AI projects. Taking on DataRobot, Dataiku RapidCanvas is taking on the likes of leading players like DataRobot, Dataiku, Palantir and Alteryx. However, the company says its human-agent hybrid approach is a key differentiating element. "In any of the legacy data science machine learning vendors, the primary way for non-coders to build end-end AI solutions is using no-code templates," Pangam explained. "For example, if I want to merge two datasets, I have to pick the 'join' template from the UI, add datasets, join conditions to instruct which columns to match for index, set the join type and then define output columns. On the other hand, with RapidCanvas, the user instructs the agent to merge two specific datasets and it auto-generates the code to merge them. This is because the agent already has the prior context of the type of tables, index and schema, size, join types, data types, etc." Further, the CEO noted that the company offers a human expert as part of its subscription. This individual works as an advisor, helping teams at key decision points with ideas, as well as support for performing complex operations, verifying outcomes and understanding industry best practices. Users can go either for this human expert-backed plan or a self-service platform-only offering at a fixed monthly fee per user. Several enterprises, including Fortune 200 companies, across manufacturing, retail, infrastructure and financial services domains have already begun adopting RapidCanvas for their AI development pipelines. The company counts among its early customers PayPal, SFR, Suzlon, AutoFi and MTE Thomson. Looking ahead, the company plans to grow its customer base and further enhance its AI agents to ensure they can work together to automate and simplify complex workflows in a multi-agent, human-in-the-loop-backed setup.