Physical AI startup Mowito raises $3 million in seed funding round

Mowito, a company specializing in physical artificial intelligence (AI) and creating foundational models for industrial robots, announced on Tuesday that it has raised $3 million in a seed funding round.

Round Participants and Funding Goals

The round was led by Version One Ventures. Other participants included All In Capital, Unisol, iSeed, as well as angel investors such as Soumith Chintala (from Thinking Machines Lab), Adarsh Kulkarni (from Foundry Robotics), Ashish Kulkarni (from Coformer.ai), and Vaibhav Domkundwar (from Better Capital).

The company stated that the funds will be used to accelerate expansion in the United States, strengthen engineering and market teams, and scale deployments with manufacturers in the automotive and electronics industries.

Mowito's Technology and Application

Founded in 2024, Mowito develops physical AI models that allow industrial robots to learn directly from task demonstrations. This eliminates the need for traditional programming while maintaining the necessary precision for manufacturing processes.

The company serves global manufacturers in the automotive and electronics sectors, with headquarters in Bengaluru and Detroit. It was noted that Mowito robots are already being used on production lines of a major Fortune 500 automotive company and one of the world's largest electronics contract manufacturers, supporting high-precision assembly operations.

Vision and Leader Comments

Co-founder and CEO of Mowito, Puru Rastog, emphasized that manufacturing has reached a point where the bottleneck is no longer hardware but software. He noted that robots should not require reprogramming when production changes, but should learn like humans—through observation and repetition. He added that this funding will help accelerate this concept, expand globally, and implement Physical AI in more manufacturing environments.

All In Capital Partner Kushal Bhagia expressed the view that manufacturing is entering a new phase where AI will radically change industrial automation. He highly praised Mowito, stating that the company is creating fundamental technology that removes one of the main barriers to industrial automation—the complexity of robot programming—and that the technical depth of the team, early customer validation, and vision for Physical AI place it in an exceptional position to define this category.

ventureburn.comJuly 6, 17:42

Bespoke Labs raises $40 million to train reliable artificial intelligence agents

Artificial intelligence-based agents have significantly improved their capabilities in recent months, learning to write code, respond to customer queries, and perform basic digital tasks. However, they still struggle to provide consistently reliable results over several hours or even days.

Funding Round

The Mountain View-based startup Bespoke Labs aims to solve this problem. The company announced it has raised $40 million in Seed and Series A rounds. These funds will be used to create the complex environments necessary for training truly reliable AI agents.

Investors and Founders

Bespoke Labs' funding attracted attention from prominent figures in deep tech and AI. Wing VC led the Series A round, while 8VC led the Seed round. Other significant participants included Mayfield and The House Fund. Participants also included high-profile technology executives such as Jeff Dean from Google, Tristan Handy, CEO of dbt Labs, and angel investors from Meta, OpenAI, and Anthropic.

Scientific Approach to Training

Founded in 2024 by Mahesh Satyamurthy and Alex Dimakis, the company plans to direct the new capital toward expanding its elite engineering team and scaling its core infrastructure. Bespoke Labs addresses the agent reliability problem by creating an internal infrastructure that simulates a complete digital workspace. This includes large codebases, active Slack chats, current emails, and system logs.

Simulations and Training

Agents are trained in these realistic simulations, executing complex, long-term workflows that hold real economic value in modern companies. Unlike many startups that rely on manual contractors and simple application-level configurations, Bespoke Labs employs a strictly research-oriented approach. The company uses advanced reinforcement learning methods, allowing agents to learn from mistakes within their environments.

Automation and Open Source Contribution

Furthermore, the team utilizes a proprietary Genetic-Pareto Agent Optimizer (GEPA), which automates the search for policies and prompts. This automation allows organizations to measure and improve AI accuracy much faster than is possible with manual prompt engineering. The team is also actively involved in open-source development, contributing to widely recognized benchmarks such as Terminal-Bench and OpenThoughts.

Scaling AI Capabilities

According to independent benchmarks conducted by METR, the time it takes for AI agents to successfully complete tasks is decreasing by approximately seven months. Training platforms must keep pace with this impressive rate of development. Bespoke Labs instantly creates these synthetic environments using new data curation pipelines and is capable of mirroring existing corporate infrastructure digitally. This allows corporate agents to be tested before processing real production data.

Future of AI Growth

The $40 million raised will go directly toward scaling Bespoke Labs' environment-building infrastructure. By investing heavily in fundamental research and technical talent, the company positions itself as a critical component of the modern AI ecosystem. Leading AI labs and native tech enterprises have an urgent need for quality simulation spaces to develop their tools, and Bespoke Labs provides the necessary foundation for optimization and benchmarking, enabling enterprise-level autonomy.

ventureburn.comJuly 2, 21:12

LinqAlpha raises $22 million in Series A round to develop AI market analytics

LinqAlpha has successfully raised $22 million in a Series A funding round. These funds are earmarked to accelerate the growth of its artificial intelligence platform designed for institutional investors.

Investments and Partners

The round was supported by investors such as AVP, Atinum Investment, and GFT Ventures. Additionally, several strategic financial institutions and venture platforms from Europe, Asia, and the United States participated. The New York-based company develops what it calls the Alpha Intelligence Layer for global public markets.

Platform Functionality

The platform assists investment specialists in processing complex market information using specialized AI agents. With this new funding, LinqAlpha's total raised capital has increased to approximately $28.6 million.

History and Founders' Team

LinqAlpha was founded in 2022 by Jacob Choi, Subin Pang, Jin Kim, and Hodjun Choi. The founding team combines financial expertise with research in artificial intelligence. Among the founders are former Goldman Sachs analysts and MIT computer science graduates.

Application of AI Agents in Research

As public markets become increasingly interconnected, investors are forced to simultaneously track earnings reports, policy changes, supply chain events, credit markets, and social media signals. LinqAlpha believes that traditional analysis methods cannot keep up with such a growing volume of data. The platform allows investment teams to use AI agents trained on their own research history instead of relying on general language models. These agents then link new market events to previous investment ideas to generate relevant insights. One of the founders noted that the competitive advantage lies in identifying market-influencing signals even before they become widely known.

Client Base Expansion and Plans

Currently, the platform is used by over 70 financial institutions. Clients include research, trading, and sales teams at major investment banks. On the buying side, clients include Causeway Capital Management LLC and Schonfeld Strategic Advisors LLC. The company initially started in Cambridge, Massachusetts, and later operated between South Korea and the United States before establishing its headquarters in New York. During this period, the business also underwent two rebrandings before adopting the name LinqAlpha.

The new funding will allow the company to expand its international staff. Management also plans to strengthen integration with market and alternative datasets. Additional investments will be directed towards implementing equity, macroeconomics, credit, and multi-asset investment strategies.

AI Competitive Landscape

LinqAlpha is entering the competitive market of AI research platforms. Demand continues to grow as investment firms seek faster analysis without compromising their proprietary insights. According to Manish Agarwal, General Partner at AVP, many AI products focus on automating routine tasks or accelerating information retrieval. He believes that LinqAlpha helps investors find differentiated investment ideas through context-aware intelligence.

Competition remains significant, as large AI service providers have attracted significantly more funding in recent years. Nevertheless, LinqAlpha asserts that its specialized approach better meets the needs of institutional investors who seek bespoke analysis rather than standard AI outputs. Industry forecasts also point to continued expansion in financial AI, with growing adoption among banks, insurance companies, and asset managers expected to attract further investment in companies developing specialized corporate AI platforms. LinqAlpha's long-term success will likely depend on demonstrating measurable value to institutional clients operating in increasingly complex global markets.