Who We Are
AI Engineering Company
Kagen AI is an AI engineering company backed by over a decade of experience in building digital products and enterprise applications. We specialize in accelerating AI adoption across industries, leveraging industry-specific expertise and AWS services. Our mission is to help businesses maximize their AI investments by turning ideas into proof of concept and migrating them to production.
Use Cases
Key enterprise Generative AI use cases we are building
Our Solutions
Solving business problems with our robust Generative AI solutions
Conversational AI Chatbot
Empower user interactions with AI chatbots that deliver seamless, real-time assistance.
Contact Center AI Agent
Enhance customer support with AI service agents supporting voice and email for efficient query resolution.
Document Intelligence
Automate document processing with AI to extract, classify, and manage critical data effortlessly.
Workforce Optimization
Optimize staff scheduling and resource allocation through AI-based workforce management solutions.
Enterprise Search
Enable intelligent, AI-driven enterprise search for quick and accurate access to information.
Financial Intelligence
Leverage AI to analyze financial data, uncover insights, and drive informed decision-making.
Payment Reconciliation
Streamline payment reconciliation processes with AI-powered automation for improved accuracy and efficiency.
AI Service Desk Agent
Leverage Generative AI to provide fast, accurate, contextual query resolutions and deliver personalized solutions.
Industries We Serve
Advancing Business Across Key Industries
.png)
Banking, Financial Services, & Insurance
Utilizing AI in the financial services industry requires a mature approach and robust framework to mitigate risks and exposures. Our cloud, AI, and ML capabilities help banks transition to new operating models, embrace digitalization, and implement intelligent automation.
Read More
Our Approach
Prototype to Production
Ideation
- Review availability and quality of data for AI use cases
- Organizational preparedness for AI adoption
- Identification of gaps in readiness to implement AI use cases
- Prioritize Generative AI use cases
Strategy
- Data pre-processing and embeddings
- LLM selection (quality, performance, and cost), fine-tuning, prompt engineering, RAG, Evaluation, AI Guardrails
- Integration with existing/new business applications
- LLMOps - AI infrastructure readiness, model training, and deployment pipeline automation
- Build and scale Proof of Concept
Industrialize
- Move LLM App from PoC to Production
- Implement data and AI policies and guardrails
- Implement LLM Observability and LLMOps
- Optimize models for performance and implement evaluation for both response and retrieval.
- Integrate with internal and external applications
Success Stories
Transformative AI Impact Across Industries
Media and Advertising
EdTech
Retail & Commerce
Our Partners
.png)
.png)
Our LLM Toolkit
Our Ecosystem of Tools and Platforms for LLM Development
Resources
Your Hub for AI Insights and Industry Trends
Impact of Generative AI-Based Shopping Assistant Chatbots in eCommerce
October 1, 2024
Read More.png)
.png)
.png)
