Jerry Chen and Instabase CEO Anant Bhardwaj | Building a System of Intelligence
Sep 12, 2023
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Jerry Chen and Instabase CEO Anant Bhardwaj discuss building a defensible system of intelligence in the AI landscape. They explore the inception and problem-solving approach of Instabase, the dominance of foundation models, reducing friction to sell AI platforms, and lessons learned as a founder and CEO.
Instabase has successfully built a defensible system of intelligence, incorporating customer feedback and the latest technology advances.
Instabase began as a distributed operating system called Data Hub and evolved into an applied AI platform for automating complex business workflows.
Instabase leverages large language models like GPT-3 and GPT-4 to handle a wide range of tasks, while focusing on representing problems correctly and improving the platform's limitations.
Deep dives
The evolution of Instabees and the power of system intelligence
Instabees is a case study in building a deep mode of IP around AI for the enterprise. The company allows enterprises to build apps using applied AI to solve complex business processes. The market is excited about Instabees because AI is evolving quickly and it is seen as a valuable tool for creating value. Instabees has raised significant funding and is valued at $2 billion. The market demand for AI platforms is driven by the need for GPUs to run AI, the cloud providers that require AI infrastructure, the availability of large language models, and the need for platforms that enable organizations to build AI applications. Instabees is well-positioned in the market as a system of intelligence for enterprise AI.
The origins of Instabees and its transformation from data hub to AI platform
Instabees originated from the idea of building a distributed operating system called Data Hub that could scale applications beyond a single machine. By creating an operating system that could handle large-scale applications and manage data files, Instabees aimed to solve the problem of running complex business processes that cannot be handled by one machine alone. The idea evolved into creating an applied AI platform that automates complex workflows for large enterprises. The platform uses AI to read and extract data, apply business logic, and build applications that automate processes like loan processing or document analysis. Instabees has become a powerful tool for large enterprises to digitize and automate their complex business workflows.
The role of large language models in Instabees' AI platform
Instabees has embraced the power of large language models (LLMs) in its AI platform. LLMs like OpenAI's GPT-3 and GPT-4 have become a valuable tool for reasoning and language understanding. By leveraging LLMs, Instabees can handle a wide range of tasks and applications, including document analysis, classification, extraction, and more. These models have become essential in solving complex business problems. However, Instabees emphasizes the importance of correctly representing the problem to the model and separating the factual information from the model's reasoning. Instabees also recognizes the limitations of LLMs and is constantly working on improving the platform to address these constraints and provide the best solutions for its customers.
The launch of AI Hub and its impact on simplifying complex workflows
Instabees recently launched AI Hub, an updated version of its platform that incorporates large language models and focuses on simplicity and usability. AI Hub is built upon the existing data hub and Instabees platform, offering a drag-and-drop interface, conversational capabilities, and simplified UX. The goal is to empower users to build applications, ask questions, and solve complex business problems without the need for complex engineering or fine-tuning of models. AI Hub includes features like a chat interface, a modular app builder, a human review process, and an app store for sharing and reusing applications. The focus is on reducing friction, enhancing reusability, and providing a user-friendly experience.
The future of Instabees: building a global ecosystem and developer community
Moving forward, Instabees aims to build a thriving ecosystem and developer community around its platform. This includes expanding beyond enterprise customers to cater to SMBs, startups, and individual users. The goal is to create a global application ecosystem that solves complex business workflows at scale. Instabees emphasizes the importance of community and aims to provide a platform where developers can collaborate, share, and reuse applications and modules. By fostering this community and ecosystem, Instabees aims to continue simplifying the process of building AI applications and becoming a go-to solution for complex business problems worldwide.
Building a defensible system of intelligence at a time when LLMs are becoming commoditized (and when all the classic moats like economies of scale are more important than ever) isn’t easy. But Instabase, which provides an applied AI platform for enterprise organizations to run various operational processes, has managed to accrue a large customer base and recently hit $2 billion valuation. The company has gained traction largely because they've taken cues directly from customers since day one while incorporating the latest technology advances to continually expand their product, making it useful across hundreds of different use cases for a range of industries.
Greylock general partner and Instabase board member Jerry Chen spoke with Instabase CEO and founder Anant Bhardwaj about the company’s journey amid the fast-changing AI landscape.
