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DeepCast

DeepCast provides an AI platform that enables engineers and scientists to create digital twins with minimal data and no coding, streamlining the modeling process for product development. This technology reduces the time and resources required for experimentation, resulting in significant cost savings and improved operational efficiency.

Traction 4/10
Houston, United States · HQ
Founded 201541K+ followers
  • Artificial Intelligence
  • Data & Analytics
  • Enterprise Software
  • Software Only
Updated 23 months ago

Funding

Raised to date

$255.6KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

2 founders

Hector Klie

CEO

Arturo Klie

Entrepreneur

Product

Problem

Developing digital twins for product development traditionally requires extensive data, specialized coding skills, and significant time investment, creating a barrier for many engineers and scientists. The complexity and resource demands of conventional modeling processes can slow down experimentation and hinder operational efficiency.

Solution

DeepCast offers an AI-powered platform that simplifies the creation of digital twins, enabling engineers and scientists to build practical models with minimal data and no coding. The platform integrates with diverse data sources and tools, allowing users to gain real-time insights and accelerate product development. DeepCast's AI engine automatically builds a digital twin that explains the underlying process, providing a recommendation companion for lab and field applications. The resulting models can be accessed through a cloud-based or on-premise dashboard for data analysis, prediction assessment, and team collaboration.

Target Audience

The primary target audience includes engineers, scientists, and product development teams across various industries seeking to streamline modeling processes, reduce experimentation time, and improve operational efficiency.

Features

  • AI-driven engine for automated digital twin creation with minimal data requirements
  • No-code interface for model building, accessible to users without programming expertise
  • Real-time integration with various databases, files, and third-party APIs via SaaS data connectors
  • Cloud-based and on-premise dashboard for data analysis, model prediction, and team collaboration
  • Interpretable equation generation for understanding the drivers behind model predictions
  • Closed-loop steam flooding optimization for enhanced oil recovery
  • Corrosion modeling for rapid categorization of anti-corrosive materials
This profile is AI-generated and may contain inaccuracies.