Product/Service Description
To de-risk initial AI adoption and swiftly validate its potential value, Aortac offers expert Proof of Concept (PoC) services. This structured engagement typically involves confirming core technology viability, developing rapid prototypes for user experience optimization, and then proceeding to full-scale implementation.
Aortac tailors PoC packages to different needs: * Rapid PoC: Designed for quick wins and initial validation, this focuses on demonstrating core AI value in a short timeframe. It might involve using LLMs to analyze internal company data, with AI Agents automatically generating analytical charts and summary reports, often leveraging cloud architecture for quick setup and minimal installation.
This is ideal for initial AI exploration and departmental-level data analysis applications. * Advanced PoC: This offers a more comprehensive, scalable enterprise-grade AI application platform. It deeply integrates LLMs and AI Agents into actual operational scenarios, supporting cross-departmental and multi-system intelligent applications.
This could include building a maintenance knowledge management (KM) system, connecting AI agents to repair logs and production line data for correlation analysis, supporting API integrations, and offering flexible deployment options (cloud, on-premise, or hybrid) with robust multi-user role and permission controls.
These services also encompass broader AI technology assessments, feasibility studies, ROI and risk evaluations, and associated employee training programs to ensure successful AI integration.
The PoC phase is critical for agile AI project initiation, allowing for iterative refinement based on early feedback before significant resource commitment.
Aortac tailors PoC packages to different needs: * Rapid PoC: Designed for quick wins and initial validation, this focuses on demonstrating core AI value in a short timeframe. It might involve using LLMs to analyze internal company data, with AI Agents automatically generating analytical charts and summary reports, often leveraging cloud architecture for quick setup and minimal installation.
This is ideal for initial AI exploration and departmental-level data analysis applications. * Advanced PoC: This offers a more comprehensive, scalable enterprise-grade AI application platform. It deeply integrates LLMs and AI Agents into actual operational scenarios, supporting cross-departmental and multi-system intelligent applications.
This could include building a maintenance knowledge management (KM) system, connecting AI agents to repair logs and production line data for correlation analysis, supporting API integrations, and offering flexible deployment options (cloud, on-premise, or hybrid) with robust multi-user role and permission controls.
These services also encompass broader AI technology assessments, feasibility studies, ROI and risk evaluations, and associated employee training programs to ensure successful AI integration.
The PoC phase is critical for agile AI project initiation, allowing for iterative refinement based on early feedback before significant resource commitment.
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