Intelligent App & AI
Solution Overview
EPAM’s Intelligent App and AI solution accelerates business process improvements through the integration of a shared data lake, grounded AI, and integration of AI back into your business processes and applications. Our approach starts with an understanding of your business objectives. We apply EPAM’s AI prioritization framework to help select use cases with the highest probability of driving the desired change through the integration of AI. To power your business transformation, we follow a prescriptive three step process to AI integration:
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Breakdown data silos and centralize relevant data in a scalable, centralized data lake.
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Ground AI, semantic search, bots, &/or custom copilots in your data.
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Integrate those AI solutions back into your application &/or business processes.
For enterprise customers, this solution also matures supporting technology processes like security, operations, and governance to ensure safe, scalable adoption of AI across the business.
Customer Problem
Customer business is dependent on a manually intense repetitive process that could be streamlined. The pain isn’t big enough to justify a complete rewrite of the application(s) or system(s) but there is a clear, justify financial impact on the business (targeting $5M+ downstream impact).
The customer believe AI can provide the streamlined business process capabilities, but doesn’t have experience with AI, central data lakes for AI, integration of AI back into applications, or supporting AI functions at scale.
EPAM Solution
EPAM Intelligent App and AI solution focuses first on the business outcome with a structured framework for evaluation and prioritization of relevant use cases. We work with business and technical stakeholders to select the right AI use cases for pilot/POC development. When potential business impact is demonstrated, we deliver on a clear roadmap from pilot to full production implementation & beyond. To ensure the highest quality technical solutions throughout, we leverage EPAM’s existing reference architectures and solution designs as a starting point for all technical conversations.
This integrated business & technical approach reduces your risk & accelerates your journey to tangible business impacts.
Key Differentiators
Reduced business risk
Impact-focused workshop & prioritized backlog, allow for agile validation of potential business impact
Rapid prototyping
Our Pilot approach quickly validates business impact. Aligned POCs validate technical architecture & solutions
Multi-cloud AI solutions
No need to change cloud provider. The solution works well with AI from each CSP and even with data from different cloud
Benefits
AI strategy
Advance your AI strategy with a backlog of use cases & COE model to safely scale
Proven process
Pilot, Prod, Adoption model reduces risk and regularly demonstrates feasibility
Shortened TTM
Rapid prototyping brings your ideas to life, engaging customers & stakeholders
Reduced TTV
Implement faster with proven architectures for data lake, AI, and apps
Enterprise integration
Customizable to ease enterprise integration & better fit your tech ecosystem
Business & Technical consulting
Expertise to optimize business processes, accelerate development, scale adoption
Features
- AI Strategy. Explore the art of the possible based on relevant AI use cases in your industry or tech ecosystem.
- Prioritization framework. Establish clear priorities based on probabilistic downstream impacts.
- Data lake centralization. Break down data silos to create enterprise-wide AI solutions.
- AI acceleration. Rapid prototyping with a variety of available models validates technical feasibility.
- Intelligent Applications. Modernize your current application experiences with AI, grounded in your data, and integrated into the workflow for your users.
- Multi-cloud capabilities. A standardized approach can produce Intelligent App & AI solutions in each of the major cloud providers, even if you app &/or data resides in a different cloud.
Use Cases
Retail/CPG
Problem Statement:
Customer needs are changing as retail experience shift increasingly to online or social media shopping experiences
Solution Proposed:
Connecting with customers through personalized experiences.
Achieved results:
Personalized experiences directly correlate with increased customer engagement and satisfaction. Enhanced personalization leads to higher conversion rates, repeat business, and customer loyalty, thereby driving revenue growth and competitive advantage in the retail market.
Financial Services
Problem Statement:
Automated fraud detection
Solution Proposed:
Transactional processing at scale with AI-assisted processes for classification and fraud detection
Achieved results:
The financial and reputational risks associated with fraud are immense. Automating fraud detection can dramatically reduce these risks by identifying and mitigating fraud more quickly and accurately than manual processes
Energy
Problem Statement:
Maintaining energy assets for production or distribution of energy is costly, especially when maintenance is a reaction to a problem.
Solution Proposed:
Predictive maintenance for energy assets
Achieved results:
Predictive maintenance significantly reduces unplanned downtime and extends the lifespan of critical assets, leading directly to cost savings and increased energy production reliability.
Healthcare
Problem Statement:
Patient and at times physicians can have a myopic view limited to a patient & their needs.
Solution Proposed:
Personalized patient care journeys with AI
Achieved results:
Personalized care plans based on pop-health stratification can improve quality of care for the patient and the cost of care for providers and payors. By leveraging AI, the healthcare industry is moving towards more customized healthcare, directly impacting patient outcomes and operational efficiency.
Lifesciences/Medtech
Problem Statement:
Life Science and Medical technology companies invest heavily in the personal required to process and understand large volumes of complex data
Solution Proposed:
AI-empowered business process w/ optional smart product integration/predictions
Achieved results:
Optimizing business processes like supply chain directly impacts the ability to meet patient needs while maintaining cost efficiency. AI-driven predictions allow for better resource allocation, potential waste reduction, and avoidance of shortages, which can be life-saving. Integrating smart products provides faster feedback cycles on new or existing products, further improving a number of supporting business processes.
Additional Information
Questions & Answers
Integrates with
AWS
Azure
GCP
OCI
EPAM DIAL
EPAM ALITA
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