Obviously AI Raises $4.7M Seed Round - No-Code AI for Analysts
Obviously AI Secures Seed Extension to Democratize Machine Learning
The entrepreneurial journey of Nirman Dave encompasses two distinct ventures, both characterized by a spirit of self-reliance. His initial undertaking, CircuiTricks, established during a gap year following high school, focused on creating educational kits for electronics and physics. Currently, Dave serves as the chief executive officer of Obviously AI, a no-code AI/ML platform designed to empower individuals lacking technical expertise to construct and train machine learning models.
Funding and Investment
The Berkeley-based company has recently expanded its seed funding round, bringing the total to $4.7 million, an increase from the previously announced $3.6 million. This extension was spearheaded by the University of Tokyo Edge Capital Partners (UTEC), a firm specializing in deep tech investments, with additional participation from Trail Mix Ventures and B-Capital.
Kiran Mysore, a principal at UTEC, shared that he discovered Obviously AI on Product Hunt while assisting a friend without a background in AI/ML or coding to develop machine learning models. After evaluating the platform and comparing it to other AutoML products, Mysore was sufficiently impressed to lead the investment round.
The Rise of No-Code/Low-Code Platforms
No-code/low-code startups have experienced significant growth in both attention and funding over the past year, with companies like Noogata and Abacus being prominent examples. Dave positions Obviously AI as catering to mid-market businesses that either lack a dedicated data science team or have personnel with data analytics skills but limited programming experience.
Proprietary Technology and Client Base
Obviously AI utilizes a proprietary technology known as “Edge-Sharp AutoML” to develop and train machine learning models tailored to the specific requirements of its clients. These models can be seamlessly integrated with existing cloud services and databases.
Industry Focus
The company primarily serves businesses in the marketing, software, direct-to-consumer, fintech, and insurance sectors. Currently, Obviously AI boasts a client base exceeding 3,000, who have collectively deployed over 82,000 predictive models on the platform.
The newly acquired seed funding will be allocated towards expansion into Asian markets, notably Japan, where the company will collaborate with Dai Nippon Printing (DNP), a leading Japanese printing company, to refine its go-to-market strategy.
Client Testimonial
Takeya Shimomura, research and development manager at Dai Nippon Printing, stated, “Predictive analytics for marketing and sales are crucial to us at DNP. However, current tools are often complex and require extensive time for implementation. Obviously AI enabled us to quickly onboard our analysts and achieve operational readiness in just a few hours.”
Founding Story and Team
Dave connected with Obviously AI’s co-founder and chief technology officer, Tapojit Debnath, while both were international students at Hampshire College. Following graduation, they completed internships at Bay Area startups.
Dave’s internship at Streamlabs, a live-streaming software platform, involved both video encoding algorithms and the development of machine learning models for marketing and sales. Debnath, during his machine learning internship at retail software startup B8ta, had a comparable experience.
Addressing the Talent Gap
The founders identified a shortage of machine learning engineers and observed that many companies rely on “citizen data analysts”—individuals with data science understanding but without formal coding skills.
Designed for the Citizen Data Scientist
“These individuals work extensively with data but aren’t programmers, and they are the primary focus of our tool design. The aim is to empower users to leverage their data understanding and rapidly build models without prolonged wait times,” explained Dave.
Dave and Debnath left their respective positions in 2018 to concentrate on their startup, initially exchanging chores for rent from their Airbnb host while honing their investor pitch before joining U.C. Berkeley’s SkyDeck accelerator program.
Edge-Sharp AutoML: A Differentiated Approach
Dave explained that many auto AI/ML platforms employ a “brute force” method, testing numerous algorithms on a dataset and selecting the best performer. This approach can be inefficient, as time is wasted on algorithms that ultimately prove unsuitable.
Obviously AI’s Edge-Sharp AutoML distinguishes itself by initially evaluating a focused set of machine learning models applicable to a given dataset. It then automatically shortlists the top five models, fine-tunes their hyperparameters, and delivers prediction results.
Pricing and Use Cases
Obviously AI’s pricing structure begins at $75 per month. Its typical clients are mid-sized businesses or smaller teams within larger organizations that lack dedicated data science resources, or whose data scientists are occupied with other projects.
A microlending company in India, with a team of 15, transitioned from manual loan applicant evaluation to AI-powered predictions using Obviously AI. The platform now predicts the likelihood of default and recommends loan amounts, providing applicants with immediate loan size estimates.
A German mobile gaming company utilized Obviously AI to implement a dynamic pricing model, predicting individual users’ willingness to pay for in-game items like tokens based on their gameplay interaction.
Future Development
A portion of the seed funding will be dedicated to machine learning research and development to broaden the platform’s applicability. Dave stated that Obviously AI currently concentrates on supervised learning use cases, where clients possess data and defined prediction goals. The company also acknowledges the potential of unsupervised learning, which involves identifying patterns in data without pre-defined objectives, for applications like automatic categorization and recommendation engines.
