Unlocking the transformational Generative AI Potential by Mastering the Data Paradox
CEO’s Keynote
Unlocking the transformational Generative AI Potential by Mastering the Data Paradox
Nitin Seth,
Co-Founder and CEO, Incedo Inc
Key Takeaways
- Overcoming key data hurdles around fragmented and multi-sourced data, sub-optimal data quality, and data infrastructure issues - to help enterprises fulfill the promise of Generative AI.
- Creating a ‘Trusted Data Layer’ across the enterprise with Incedo's ‘Data - Unified Solution Framework’, that links business goals, Data & AI technology, and core processes to create data readiness for AI implementation.
- Transitioning from strategy to execution with Incedo’s diagnostic approach that ensures near-term results while building a strong foundation for long-term data capabilities.
Product Launch: Incedo brAInspark
We successfully launched our Generative AI platform – Incedo brAInspark, at the AI Summit NY! With brAInspark, Incedo is putting the power of Generative AI directly into the hands of our clients and enterprises, to unlock tangible business value by fine-tuning contextual enterprise data.
“For Generative AI to be truly transformational, Data Contextualization is needed at three layers – Data of internet (Macro Data), Enterprise Data and Individual Data (Micro Data). With brAInspark, we aim to empower enterprises by solving specific business problems around productivity improvement and SDLC,” stated Nitin at the launch.
Platform Demos
Gen AI for SDLC Transformation: Unveiling 'BrainSpark', Incedo's Gen AI platform for Disruptive Innovation
- Realize true opportunities to help with Productivity and Accuracy gains using Generative AI
- Identify the ‘secret sauce’ to convert broad-based LLMs into function and task-specific knowledge models
- Deep-dive on Generative AI across Software Development Life Cycle (SDLC) – Co-Development, QA Testing, Deployment, etc.
Boost Business IQ with Incedo Lighthouse - your AI-powered Personal Business Analyst
- Problem Discovery: Surface the most pertinent business problems from data sets automatically every day with KPI tree-based issue decomposition
- Root Cause Analysis: Identify the segments of customers and the key drivers that are impacting the business KPIs in most significant manner
- Actions and Experiments: Plan remedial actions for problematic customer segments and evaluate their efficacy through experimentation before full-scale implementation.
Success Stories
A Fortune 500 bank in US transforms Collections Ops with AI-based Automated Decisioning
Decrease in dollar write-offs for cards and personal loan portfolios
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Generative AI-enabled Customer Service Solution for a Top US Healthcare firm
Reduction in Avg. Search Time of Knowledge Articles
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Mid-tier Bank revamps Model Risk Management with AI-driven System of Insights
Gains in efficiency with automated model monitoring
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Generative AI-enabled QA Testing Solution for a Leading US Wealth Management firm
Productivity gains for the end-to-end execution of QA test cycle
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