
MoBagel
MoBagel | Device Management & Analytics.
USD | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
% growth | - | 59 % | 37 % | - | 38 % | 15 % |
EBITDA | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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MoBagel, founded in 2015 by AI scientists from Stanford and UC Berkeley, is an AI startup based in Silicon Valley. The company specializes in providing a generative AI platform and various enterprise-level AI Agents aimed at enhancing data-driven decision-making and automating business processes. Serving over 11,000 brands across industries such as sales and marketing, supply chain, finance, and manufacturing, MoBagel operates with the vision to 'Build AI Together and Beyond.'
MoBagel's offerings are divided into two main categories:
Generative AI Builder Platform: This No Code platform allows the development of various AI Agents using tools like AutoML, MLOps, DataOps, Auto Time Series Forecasting, generative BI, and mainstream LLMs such as Open AI GPT and Meta Llama. By integrating generative AI's LLM into a new multimodal system, the platform addresses hallucination issues in AI reasoning. This enables rapid creation of enterprise-level AI service applications for analysis, inference, and process automation, making it suitable for companies with basic AI or data science teams, allowing flexible and swift development of AI applications.
AI Agents: These agents are designed to enhance business process automation and intelligence in areas such as sales & marketing, supply chain, finance, and manufacturing. They automate processes and enable precise decision-making through KPI and performance-oriented strategies, making them ideal for businesses with specific commercial scenarios that want to see immediate results.
Keywords: Generative AI, AI Agents, No Code, AutoML, MLOps, DataOps, Time Series Forecasting, Business Automation, KPI Strategies, Enterprise AI.