Agentic AI / MCP

Agentic AI / MCP

Agentic AI / MCP

The future of business automation isn’t just AI—it’s autonomous AI agents that can reason, plan, and act independently. I help B2B SaaS companies and Financial Services firms harness agentic AI to drive competitive advantage and operational efficiency.

What is Agentic AI?

Unlike traditional AI that simply predicts or classifies, agentic AI systems:

  • Reason through complex problems autonomously
  • Plan multi-step workflows and adapt to changing conditions
  • Act by executing tasks and making decisions
  • Learn from outcomes to improve performance

This represents a fundamental shift from AI-as-a-tool to AI-as-a-workforce.

Services

AI Strategy & Roadmap

For Scale-ups & Growth Companies:

  • AI readiness assessment and maturity modeling
  • Use case identification and prioritization
  • ROI modeling and business case development
  • Technology stack selection and vendor evaluation
  • Risk assessment and governance frameworks
  • Integration with existing systems and workflows

For Financial Services:

  • Regulatory compliance and AI governance (MiFID II, GDPR, etc.)
  • Risk management and model validation
  • Client-facing AI applications (advisory, research, trading)
  • Back-office automation (KYC, compliance, operations)

AI Enablement & Training

Executive Workshops:

  • Agentic AI fundamentals for C-suite and boards
  • Strategic implications and competitive positioning
  • Investment decisions and build vs. buy analysis

Technical Team Training:

  • AI agent development and deployment
  • Prompt engineering and agent orchestration
  • Multi-agent system design patterns
  • Model Context Protocol (MCP) implementation
  • Best practices for production AI systems

Change Management:

  • Organizational readiness for AI transformation
  • Workforce planning and skills development
  • AI adoption frameworks and success metrics

Bespoke AI Agent Development

I design and build production-ready AI agent systems tailored to your business:

Single Agent Systems

  • Customer support automation
  • Document analysis and extraction
  • Research and intelligence gathering
  • Sales enablement and lead qualification
  • Financial analysis and reporting

Multi-Agent Systems

  • Coordinated workflows across business functions
  • Agent orchestration and task delegation
  • Complex decision-making processes
  • End-to-end process automation
  • Human-in-the-loop hybrid systems

MCP Server Development

  • Custom Model Context Protocol servers for enterprise integration
  • Secure data access and API integration
  • Tool creation for specialized business functions
  • Cross-platform agent capabilities

Full Lifecycle Support:

  • Requirements gathering and system design
  • Prototype development and validation
  • Production deployment and monitoring
  • Performance optimization and iteration
  • Maintenance and continuous improvement

Industry Expertise

B2B SaaS Companies

  • Product AI integration strategies
  • Customer success automation
  • Sales process optimization
  • Operational efficiency gains
  • Competitive differentiation through AI

Financial Services & Fintech

  • Trading and investment analysis
  • Risk assessment and compliance
  • Customer advisory and research
  • Portfolio management automation
  • Fraud detection and prevention

Agriculture & Specialized Industries

  • Domain-specific AI applications
  • Custom data integration and analysis
  • Operational optimization

Technology Stack

I work with leading AI platforms and frameworks:

  • LLM Providers: OpenAI, Anthropic (Claude), Google, Azure OpenAI
  • Agent Frameworks: LangChain, LangGraph, AutoGen, CrewAI
  • MCP: Model Context Protocol implementation
  • Infrastructure: AWS, Azure, GCP cloud platforms
  • Integration: RESTful APIs, GraphQL, webhooks, event-driven architectures

Why Agentic AI? Why Now?

Competitive Imperative:

  • Early movers gain 18-24 month advantage in AI capabilities
  • Agent systems reduce operational costs by 40-60% in targeted areas
  • Customer expectations increasingly require AI-powered experiences

Technology Maturity:

  • Foundation models (GPT-4, Claude, etc.) now capable of reliable reasoning
  • Agent orchestration frameworks production-ready
  • MCP enabling secure, scalable enterprise integration

Market Opportunity:

  • AI agent market projected to reach $47B by 2030
  • 73% of enterprises planning AI agent deployments by 2025
  • First-mover advantage in competitive differentiation

Engagement Models

Discovery & Strategy (2-4 weeks)

  • Current state assessment
  • Use case identification and prioritization
  • Roadmap and implementation plan
  • Fixed fee: Ideal for getting started

Proof of Concept (4-8 weeks)

  • Single agent prototype
  • Validation with real data and workflows
  • ROI modeling and scale planning
  • Fixed fee or hourly: De-risk before full commitment

Full Implementation (3-6 months)

  • Production-ready agent systems
  • Integration with existing infrastructure
  • Training and change management
  • Ongoing optimization
  • Project-based or retainer

Fractional AI Leadership

  • Part-time AI strategy and execution
  • 1-3 days/week commitment
  • Ideal for scaling AI initiatives without full-time hire
  • Monthly retainer

Case Study: Financial Services AI Transformation

Details available under NDA - Highlights:

  • Multi-agent system for investment research and analysis
  • 70% reduction in research time
  • Integration with existing trading platforms
  • Regulatory compliance maintained
  • 6-month implementation, 4x ROI in year one

Ready to explore agentic AI for your business? Connect on LinkedIn or explore my Interim CXO, Software Development, and Strategic Advisory services.