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Intelligent App & AI Rapid prototyping & AI innovation

Intelligent App & AI

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Overview

Differentiators

Features

Use Cases

Overview

Differentiators

Features

Use Cases

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:

Breakdown data silos and centralize relevant data in a scalable, centralized data lake.
Ground AI, semantic search, bots, &/or custom copilots in your data.
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.

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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