The Last Mile Challenge in Gen AI Adoption
Gen AI Faces a “Last Mile” Adoption Barrier in Enterprises. Despite enhancement in the capabilities of LLMs, enterprises struggle with adopting Gen AI effectively. There is a significant gap between generalized, horizontal LLMs developed by Big AI companies and their application to the specific, nuanced needs of industries.
Key Adoption Challenges
- Inaccurate: Off-the-shelf LLMs don’t accurately perform align with industry-specific use cases.
- Data Limitations: Lack of training on proprietary, trusted data.
- Lack of Explainability: Enterprises need transparency in AI decisions.
- Data Privacy: Reluctance to expose proprietary data externally.
- Guardrails: The need for guardrails to ensure AI aligns with compliance needs.
Enterprises Need Vertical AI Applications
Addressing Real-World Industry-Specific Challenges
Enterprises need Vertical AI Solutions that solve specific, messy use cases.
These solutions must leverage the strengths of Big AI advancements while addressing specific industry needs.
AI agents targeted for domain-specific use cases, with superior reasoning and answering capability.
Cost-effective, customized Gen AI solutions that deliver measurable ROI
Our Focus Areas
Automotive AI and Connected Car Data Analytics
- We have a pedigree in Automotive AI and Data Analytics, delivering AI-powered applications in the Automotive and Mobility sectors.
- Our Connected Vehicle Data Analytics and Sensor AI products and solutions serve clients across geographies at scale.
- Gen-AI based applications for knowledge management and analytics in the automotive industry.
- Expertise in customized AI applications leveraging LLM models with proprietary cognitive architecture and methodology
- Check out AutoWiz , our Connected Vehicle Data Analytics Platform Site
Gen AI for Financial Services
- Vertical Gen AI applications for Research and Analytics applications.
- We aim to empower analysts and investment professionals across asset classes with AI-enhanced research, monitoring, and decision-making tools.
- Our first use case is an intelligent assistant that enhances productivity and decision-making in the research workflow.
- We are combining our core Gen AI expertise and cognitive architecture with domain knowledge of experts from Financial Services.
- We provide a unique, productized service model that blends customized, consultative solutions with the cost benefits of reusable core technology engines.