Agentic AI / MCP

The future of business automation isn't just AI—it's autonomous AI agents that can reason, plan, and act independently. This is the hands-on, delivery side of my work: agent strategy, team enablement, and bespoke multi-agent and MCP systems. For a full enterprise platform, see MeetLoyd.

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

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
  • • Strategic implications
  • • Investment decisions

Technical Team Training

  • • AI agent development
  • • Multi-agent system design
  • • MCP implementation

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
  • • Research gathering
  • • Financial analysis

Multi-Agent Systems

  • • Coordinated workflows
  • • Agent orchestration
  • • Complex decision-making
  • • End-to-end automation

MCP Server Development

  • • Enterprise integration
  • • Secure data access
  • • Tool creation
  • • Cross-platform capabilities

Technology Stack

  • 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

Engagement Models

Discovery & Strategy (2-4 weeks)

Current state assessment, use case identification, roadmap development

Fixed fee

Proof of Concept (4-8 weeks)

Single agent prototype, validation with real data

Fixed fee or hourly

Full Implementation (3-6 months)

Production-ready systems, integration, training

Project-based or retainer

Fractional AI Leadership

Part-time AI strategy and execution (1-3 days/week)

Monthly retainer

Ready to explore agentic AI for your business?

Let's discuss how autonomous AI agents can transform your operations and create competitive advantage.

Connect on LinkedIn