Case Study: Knowledge Management AI Chatbot
Our Client experienced explosive growth over the past few years as one of the fastest growing startups. With a growing number of employees and an increasing amount of information to manage, it became crucial for our client to streamline communication and ensure all team members had quick and easy access to essential company knowledge across their cloud drives, email and internal chat platform.
Key challenges Client faced included:
Keeping teams aligned: As new employees joined the company, it was essential to ensure they were up-to-date on policies, product features, and sales strategies.
Managing a complex product roadmap: With new features and updates constantly in development, employees needed a centralized source of information to stay informed about product changes.
Maintaining compliance with industry regulations: As a company operating in the highly regulated financial sector, it was critical for them to keep all employees up-to-date on regulatory requirements and ensure compliance across the organization.
Ensuring consistency in sales and marketing messages: As the sales and marketing teams grow, it becomes increasingly important to maintain consistency in messaging to potential and existing customers. A centralized knowledge management solution can help ensure everyone is on the same page and presenting a unified message.
Onboarding new team members efficiently: Rapid growth often means onboarding many new employees at once. A streamlined onboarding process, supported by a comprehensive knowledge management system, can help new team members get up to speed quickly and become productive more rapidly.
Managing and sharing customer feedback effectively: With a growing customer base, they likely received an increasing amount of feedback from users. A centralized system for collecting, managing, and sharing this feedback can help the company better understand its customers' needs and priorities.
These challenges are not unique to our client; many businesses face similar issues as they grow and expand. Effective internal knowledge management is crucial for maintaining efficiency, aligning teams, and fostering a culture of collaboration and innovation.
Why an AI Chatbot?
In order to tackle their knowledge management challenges, it was crucial to find a solution that was accessible, scalable, and could easily integrate with existing systems. We identified that an AI chatbot was the ideal choice for several reasons:
Integration with existing systems: The AI chatbot could seamlessly integrate with existing systems including their cloud drives, chat platform and emails, ensuring a smooth transition and minimal disruption to our client's current processes.
Accessibility and ease of use: The chatbot could be accessed through multiple channels, including messaging platforms, mobile apps, and the company's intranet, making it convenient for employees to get the information they needed regardless of their location or device.
Scalability: As they expanded, the chatbot would be able to grow alongside the company, accommodating more users, handling more information, and responding to more complex queries.
Handling rapid user growth: With our client experiencing explosive user growth, it's essential for the company to scale its customer support efforts efficiently. A chatbot can handle routine customer inquiries, freeing up human support staff to focus on more complex issues.
Integrating diverse products and services: They offer a wide range of products and services. An AI chatbot can provide a unified source of information about these various offerings, making it easier for customers and employees to stay informed.
End-to-End Services Offered
As part of this project, our team provided end-to-end services including product management, management consulting, software development and RAG services.
Product Management
Project planning and coordination: We collaborated with our client's stakeholders to define project goals, timelines, and deliverables.
Product roadmap development: Our team created a detailed roadmap for the chatbot project, aligning it with their overall business strategy.
Prioritization and resource allocation: We helped them optimize resource allocation, ensuring the chatbot's development and deployment remained on track.
Management Consulting
Strategic advisory: We offered strategic advice on the implementation and adoption of AI technology within our client's organization.
Change management: Our team guided them through the necessary organizational changes to ensure a smooth transition to the new chatbot system.
Training and support: We provided training and ongoing support to their employees, fostering successful adoption of the chatbot solution.
Software Development
Solution architecture: Our team designed an optimal architecture for the chatbot, leveraging AWS services and Claude 3 Opus to ensure scalability and performance.
Implementation: We developed and deployed the chatbot application, integrating it seamlessly with our client's existing infrastructure.
Customization: Our team tailored the chatbot's functionality and user interface to meet their unique requirements.
Retrieval Augmented Generation (RAG) Services
Integration: We integrated RAG capabilities into the chatbot, combining retrieval-based and generative models for improved accuracy and context awareness.
Performance improvement: Our team fine-tuned the RAG components, optimizing response generation speed and relevance.
Testing and audit: We conducted rigorous testing and auditing of the RAG system, ensuring its reliability and adherence to AI ethics and governance standards.
In-Depth Look at Chatbot Architecture
To address our client's knowledge management challenges, we built an AI chatbot solution using AWS, leveraging Claude 3 Opus from Anthropic.
The chatbot utilized Retrieval Augmented Generation (RAG), a technique that combines retrieval-based and generative models for improved accuracy and context awareness. The key components of the solution included:
Claude 3 Opus
Anthropic's Claude 3 Opus is an AI model with excellent language processing capabilities. For chatbots, Claude excels in:
Contextual understanding: Claude accurately interprets user queries within the context of Client's products, services, and policies.
Domain-specific language: Claude quickly adapts to Client's unique terminology and language, making it well-suited to handle queries related to cryptocurrencies and financial regulations.
AWS-Based Solution
AWS CDK: Deploys all the required resources for the chatbot application in an AWS account.
AWS Lambda (Orchestration): Connects the various components of the architecture and handles communication between them.
Amazon ECS Cluster: Hosts the Streamlit application, which serves as the user interface for interacting with the chatbot.
Application Load Balancer: Distributes incoming user traffic to the chatbot application, ensuring high availability and scalability.
Amazon VPC: Provides a secure and isolated environment for the chatbot application.
Retrieval Augmented Generation (RAG)
AWS Kendra: Acts as the vector database, storing and retrieving vector representations of text data for efficient retrieval of relevant information based on similarity in vector space.
AWS Glue: Extracts, transforms, and loads data from various sources into the vector database for indexing.
Amazon Bedrock: Serves as the inference engine for answering user queries using Claude 3 Opus and the data indexed by AWS Kendra.
Deployment and Infrastructure
AWS CDK: Deploys the necessary infrastructure as code, ensuring efficient and repeatable deployment of the chatbot application.
Amazon S3: Stores data required for the chatbot application, such as historical queries, response templates, and user session data.
Streamlit Application
User-friendly interface: Streamlit provides an intuitive, easy-to-navigate interface for users to interact with the chatbot.
Customizable UI elements: Widgets and interactive components can be tailored to Client's branding, ensuring a consistent user experience across platforms.
Chatbot Responses
Instant answers: The chatbot provides real-time responses to user queries, ensuring quick access to information.
Proactive suggestions: The chatbot can offer related resources and links based on user queries, encouraging deeper knowledge exploration.
Continuous Improvement
User feedback mechanism: The chatbot includes a feedback feature, allowing Client employees to rate responses and suggest improvements.
Outcomes and Takeaways
By taking a comprehensive view of the technical solution combined with the organizational challenges of adoption across departments, our team ensured that our client's chatbot project was robust, effective and easily adopted by relevant stakeholders. Tasks that often began with hours or days lost to information gaps and research are now completed in minutes. Beyond improving efficiency, the new chatbot also drove employee satisfaction as they were now able to avoid yield loss and maximize their efforts on value-added work.
