Yes, we can! That's the answer to every question you'll see selected here in our new regular series "What's In Our Inbox" Here we will share insightful, trend-spotting questions from clients and partners along with our expert, trendsetting responses.
This week, could AI Agents, or "LLMs That Do Things," transform how a company trains its nationwide sales team at a fraction of the time and cost?
Partner: We need to develop an AI model that acts as an interactive trainer for our sales team. The AI would simulate real customer interactions, allowing new salespeople to practice handling objections, answering questions, and improving their communication skills in a controlled environment. The goal is to ensure the sales staff are well-prepared and confident before engaging with actual customers.
What kind of team members and positions are necessary to develop and maintain this kind of AI product?
Rootstrap: For an AI agent like this, we recommend a dedicated pod comprising:
- AI Engineer: Technical lead. Owns prompt engineering, fine-tuning, training actions, leveraging RAG, and implementing RLHF. This person will also establish testing protocols using tools like Giskard, Ragas, and Promptfoo to validate model behavior.
- Data Engineer: Owns data infrastructure, integrating with your existing data systems, ensuring data is centralized and accessible. Handles data transformations and establish real-time pipelines as needed.
- Full-Stack Engineer: Owns the UX/UI for both users and admins, connecting frontend components with backend systems, including the AI model.
Additionally, we can provide:
- Technical Product Manager: Translate business strategy into detailed product and data requirements, and also drive project timelines, coordinate between teams, and ensure alignment with your business objectives.
- UX/UI Designer: Crafts intuitive interfaces and user experiences.
- QA Engineer: Ensures high quality through rigorous manual and automated testing.
- DevOps Engineer: Deploys, maintains, secures, scales, and cost-engineers the infrastructure and deployment processes.
Partner: What kind of technology is necessary to develop and maintain this type of AI product?
Rootstrap: Developing an AI Agent to train your salespeople would likely require:
- Data Integration Tools: To connect with your existing data systems and manage data flow.
- Vector Databases: For efficient storage and retrieval of embeddings used in NLP tasks.
- Backend Infrastructure: Hosted on platforms like AWS EC2 or containerized services to handle requests and implement RAG for querying data.
- Frontend Platform: For building user interfaces accessible to your staff and administrators.
- Admin Dashboard: For configuration, reporting, and monitoring system performance.
- User Access & Controls: For setting user roles and permissions while also ensuring data privacy and compliance with relevant regulations.
Partner: What type of AI models do you work with?
Rootstrap: We're experienced with all leading Large Language Models (LLMs), including OpenAI’s GPT, Anthropic's Claude, and Meta's Llama. We also work with external services like AWS Textract for Optical Character Recognition (OCR) and utilize models available in Google Cloud's Vertex AI for text and audio processing.
Our expertise extends to:
- Custom Model Development: Creating bespoke models for Natural Language Processing (NLP), Computer Vision, predictive analytics, and recommendation engines.
- Model Fine-Tuning: Adapting pre-trained models to fit specific use cases.
- End-to-End Machine Learning Pipelines: Developing pipelines for applications like image recognition, text classification, sentiment analysis, and real-time data processing.
- Optimization and Integration: Ensuring models are optimized for performance, scalability, and seamless integration into existing systems.
Partner: Can you explain your development capabilities?
Rootstrap: We have the full spectrum of development capabilities to bring your AI solution to life. With a team of around 200 software builders, our expertise spans:
- AI/ML Engineers: Skilled in building and refining AI models tailored to unique business needs and data.
- Data Engineers: Experts in data integration, pipeline creation, and infrastructure setup.
- Backend and Frontend Developers (ReactJS, Node, Ruby): Proficient in creating robust applications with intuitive user experiences.
- Mobile App Developers (React Native, iOS and Android Native): Capable of extending functionalities to iOS and Android platforms.
- Product Management and UX/UI Design: Own mapping the user journeys and data flows, product planning and requirements gathering, UX/UI design and user testing.
- Quality Assurance (QA) Engineers: Implement end-to-end manual and automated unit and regression tests of the code well as User Acceptance Testing (UAT) to ensure a smooth deployment and run in production.
- DevOps Engineers: Ensuring scalable, secure, and efficient deployment in cloud environments.
Our collaborative approach ensures that we deliver a comprehensive, high-quality solution from concept to production.
Conclusion
We hope this Q&A provides clarity on how we approach complex projects and the resources involved. At Rootstrap, we're passionate about leveraging cutting-edge technology to solve real-world problems. If you're considering modern software solutions to supercharge your business, we're here to help you navigate the journey from idea to success.
Ready to Rootstrap? Let's accelerate your roadmap and turn your vision into reality. Learn more and get in touch here: rootstrap.com/intro
