Entefy Delivers Hyperconfigurable AI and Automation for Enterprises

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By Lian Jye Su | 2Q 2022 | IN-6535

Artificial Intelligence (AI) is the cornerstone for many emerging key technologies and strong business fundamentals. To accelerate AI adoption, companies can either build solutions using their own team of AI experts or buy from qualified AI providers. Entefy’s AI-optimized compute infrastructure, multimodal AI model library, and multifaceted expertise allow the company to deliver highly focused AI applications and hyperautomation for its end users in a seamless manner.

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End-to-End AI-as-a-Service

NEWS


Developing and deploying AI-based process automation and analytics that integrate tightly with existing business operations is still challenging, even in 2022. While enterprises nowadays are spoiled with choices, combining a patchwork of AI frameworks, platforms, and tools into a highly automated business function requires a lot more skills. This includes creating and refining algorithmic models, thoughtful process orchestration, user-friendly design, robust software, and a clear understanding of the business case.

Silicon Valley-based Entefy identifies a total of 18 skills to create a production-ready, enterprise-grade AI solution from ideation to full production. More skills will be required if the solution intends to leverage emerging technologies, such as on-device AI and edge computing. To resolve this complexity, the company provides comprehensive enterprise AI products and services, covering AI infrastructure, multimodal AI models, data management, backend workload orchestration, user interfaces, and visualization tools. In addition, through one convenient monthly subscription package, Entefy can deploy the full-stack AI solution on its private cloud, on a managed public cloud, or on the customer’s premises.

Entefy's Unique Differentiations

IMPACT


To provide its end-to-end AI technology, Entefy has made several unique decisions. First, the company builds and manages its own compute and storage infrastructure. In addition, the company partners with Equinix and designs its data centers to be a single-tenant private cloud. This enables the company to provide the best performance through highly optimized compute, storage, and networking. Second, the company’s platform enables the ingestion and processing of diverse data, from text and images to videos, audio files, and time-series tabular data. All these data are stored in Entefy’s databases and processed using a single, orchestrated data pipeline.

Third, Entefy builds its core platform functions with microservices. The functions are based on its proprietary Universal Message Object (UMO) and Micro AI Service (MAIS) architectures, ensuring high-level scalability and resiliency compared to traditional, monolithic design. Lastly, using Entefy’s proprietary app framework, Entefy provides end users the flexibility to present user interfaces, including outputs and insights, in formats best suited for their requirements.

Currently, Entefy’s customers vary in size, from Small and Medium Enterprises (SMEs) to global public companies across several industries, including financial services, healthcare, retail, and manufacturing. Key use cases include automatic underwriting and real-time pricing prediction. In addition, Entefy’s end-to-end platform minimizes the need to implement and manage dozens of different point solutions, and alleviates the need for heavy resourcing and costs with each implementation.

Capturing the Immense Commercial Opportunities in Cloud AI

RECOMMENDATIONS


COVID-19 presents an opportunity for enterprises to optimize their workflow through AI. A global survey by the IBM Institute for Business Value (IBV), conducted in collaboration with Oxford Economics during the first few months of the COVID-19 pandemic, found that 60% of the C-suite are accelerating digital transformation during the pandemic. This has led to the rapid emergence of companies that offer multi-disciplinary AI development tools and services. Some are focused on AI development platforms and Machine Learning Operations (MLOps), such as H2O.ai, Dataiku, and DataRobot. Others, such as SenseTime and Clarifai, are more vertical- or use case-focused. Finally, there are few companies similar to Entefy in offering end-to-end ML services, such as CognitiveScale and C3.

In comparison, beyond just AI tools and services, Entefy has its AI-optimized infrastructure, broad data expertise, privacy-focused AI models, and hyperautomation capabilities, allowing the company to go beyond a vertical-focused and public cloud-based business model. As a result, Entefy is well positioned to serve enterprises looking to accelerate their AI/ML development, including supply chain, healthcare, and conversational AI, the three post-COVID-19 growth areas for cloud AI highlighted by ABI Research.

 

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