AI Agent MVP Implementation
Data & AI
Motivation
The AI Hybrid Workforce is a heterogeneous team composed of both humans and AI agents. It operates in a collaborative environment where AI agents augment human capabilities by autonomously handling simple, repetitive tasks. As a result, human team members can focus more on complex, high-value activities. This division of labour significantly enhances the hybrid team's performance in terms of scalability, efficiency, and effectiveness, when compared to a team composed solely of humans.
This offering builds on existing system requirements and agent onboarding definitions and develops the first productive iteration (the Minimal Viable Product) of the defined AI agent. The output is a production ready MVP AI agent that can be used in a limited scale rollout to validate the business case and generate input for iterative improvement and functional expansion of the agent.
What we bring
With more than 20 years of experience in software development and AI solutions for some of the world’s largest enterprises, PRODYNA is uniquely positioned to deliver a comprehensive perspective on every aspect of your future AI application. Our strengths in the AI domain include:
- Fail Fast Mindset: We anticipate your needs early and assess feasibility upfront. If the expected return on investment cannot be achieved, we help you redefine the approach.
- Simplicity First: We begin with the simplest viable setup and evolve it only as needed.
- System Architecture: We can provide you with a complete AI platform that fully integrates with your other cloud and on-prem services.
- Agentic Frameworks: We leverage the most suitable and up-to-date agentic frameworks to maximize productivity and solution effectiveness.
What you need
To efficiently develop the MVP, your organization should contribute the following:
- Clearly Defined system requirements: This a description of all functional and non-functional requirements that should be fulfilled by the MVP.
- Agent Onboarding Definitions. This is a list of AI governance, security and compliance requirements
- Business and Technical Stakeholder Support: We need to collaborate with business and technical stakeholders to ensure efficient development and smooth integration into your existing IT landscape.
What you get
The output is an MVP AI Agent fully deployed on the cloud platform. PRODYNA will guide you and your employees through the following phases:
Sprint 0 (2 days)
- Kick-off & Alignment: Scope, success criteria, and business goals of the MVP.
- Use Case Definition: Define user stories that will be implemented and evaluation methods.
- Developer Onboarding: Enable the developers to create the needed infrastructure and commit code according to your guidelines.
- Technical & Data Assessment: Understand your data sources, infrastructure, governance requirements, and integration points.
- Architecture: Develop a high-level architecture to visualize the target application.
- Roadmap: Develop a roadmap detailing the milestones for the MVP implementation.
Sprint 1 (10 days)
- Provisioning of Infrastructure: Provision and configure the application infrastructure and establish secure network configurations to the data pools.
- Tooling & Automation: Implement CI/CD pipelines and DevOps best practices for streamlined workflow and faster iteration.
- Core Application Implementation: Implementation of the MVP features with the most promising approach.
Sprint 2 (10 days)
- Evaluation: Testing the application performance in the real world and aggregating the results.
- Stabilization: Improve the application by implementing the findings of the evaluation.
- Demonstration & Knowledge Transfer: Present a working agent, summarize key lessons, and provide training or documentation to empower your teams for ongoing or future expansions.
Quick facts
- Effort: 22 days
- Production ready
- Delivers a functional MVP
Benefits
- Accelerated Time to Value: Deliver a functional AI agent within weeks, reducing risk and enabling faster ROI.
- Established Best Practices: Leverage 20+ years of software development experience to ensure a focused and effective MVP implementation.
- Holistic Insight: Gain a comprehensive understanding of AI capabilities, architectural design, key success factors, operational costs, and implementation efforts—empowering informed decisions for future development.
