Igor Iric

CTO · Founder of Flockion · Agentic AI & Enterprise Cloud Architect

Building production-grade AI agent platforms, multi-agent systems, enterprise RAG and intelligent business applications.

📍 Switzerland  ·  🧠 Agentic AI  ·  ☁️ Cloud Architecture  ·  🏗️ Enterprise Platforms

I am a CTO, software architect and founder of Flockion, focused on building the next generation of enterprise Agentic AI systems.

My work sits at the intersection of:

AI agents + enterprise software + cloud architecture + data + product engineering.

I design systems where AI moves beyond a chatbot and becomes an operational layer of the enterprise — with specialized agents, teams, tools, knowledge, memory, workflows, human approvals, governance and observability working together.

My background spans enterprise software engineering, cloud-native architecture, distributed systems, cybersecurity, DevOps and technical leadership.

Today, much of my work is focused on turning LLMs and AI agents into reliable production systems that can operate inside complex enterprise environments.

Flockion is the platform I founded to make AI agents usable as real enterprise software.

Instead of building isolated copilots, Flockion enables organizations to create an entire ecosystem of agents, teams, tools, skills and knowledge that can collaborate and operate under enterprise governance.

                    ┌─────────────────────────┐
                    │        FLOCKION         │
                    │  Agentic AI Platform    │
                    └────────────┬────────────┘
                                 │
        ┌────────────────────────┼────────────────────────┐
        │                        │                        │
    AI Agents               Agent Teams              Knowledge
        │                        │                        │
    Tools / MCP              Orchestration              RAG
    Skills                   Routing / Handoffs        Memory
    Providers                Collaboration             Context
        │                        │                        │
        └────────────────────────┼────────────────────────┘
                                 │
                    Governance · HITL · Security
                    Observability · Evaluation
                    Marketplace · Discovery

Flockion includes:

• 🧠 AI agents with tools, skills, memory and knowledge
• 👥 Multi-agent teams and orchestration
• 🔌 MCP servers and enterprise tool integrations
• 📚 Enterprise RAG and knowledge management
• 🧬 Agent and team versioning
• 🔀 Forking and reuse of agents and teams
• 🛡️ Governance, policy controls and risk configuration
• 🙋 Human-in-the-loop approval workflows
• 🔭 Runtime observability and execution traces
• 💬 Agent, team and human conversations
• 📰 Agent-generated feeds and discovery
• 🏪 Publishing, subscriptions and marketplace capabilities
• 🔑 BYOK and provider configuration
• 🏢 Private enterprise deployment
• ☁️ Azure-native infrastructure
• 🤝 Microsoft Agent Framework-oriented runtime
• 🔗 External agent and provider integration

Microsoft Agent Framework · Azure AI · Python · FastAPI · React · TypeScript · PostgreSQL · MCP · Azure Service Bus · Key Vault · Application Insights · Azure AI Search

Azure and AI frameworks run the agents. Flockion runs the agentic organization.

Explore Flockion →

My current engineering work is centered around several areas of applied enterprise AI.

Founder & Lead Architect

A full-stack platform for creating, publishing, running, governing and discovering AI agents and multi-agent teams.

Architecture

React TypeScript FastAPI Python PostgreSQL Microsoft Agent Framework Azure MCP

Key capabilities

Agents · Teams · Skills · Tools · MCP · Memory · RAG · Governance · HITL · Observability · Marketplace · BYOK

View Flockion Engineering →

AI Architecture · Multi-Agent Systems · Enterprise Data

An Agentic AI platform designed to transform financial information into continuously generated business intelligence.

The platform combines:

Enterprise Data → AI Agents → Investigation → Simulation → Recommendation → Human Decision

Typical integrations include:

SAP · Snowflake · Azure · Enterprise RAG · Power BI · Microsoft Agent Framework

Knowledge Architecture · Retrieval · AI Search

A production-focused RAG architecture for large enterprise knowledge environments.

Designed around:

• document ingestion pipelines
• metadata enrichment
• stable document/chunk identities
• hybrid and semantic retrieval
• vector search
• multimodal content
• access control
• citation grounding
• incremental indexing
• retrieval evaluation
• agent-accessible enterprise knowledge

Technology

Azure AI Search · Azure OpenAI · Python · Microsoft Agent Framework · RAG

Agentic Operations · Commodity Intelligence · Decision Support

A specialized team of AI agents for continuously investigating supply-chain signals.

Detected Signal
      ↓
Agent Investigation
      ↓
Cross-Agent Analysis
      ↓
Scenario / Simulation
      ↓
Recommended Action
      ↓
Human Decision

Agents can specialize in:

Commodity Intelligence · Supplier Risk · Procurement · Logistics · Market Research · Financial Impact

Agent Observability · Human-in-the-Loop · Decision Intelligence

An operational interface for understanding what AI agents are detecting, investigating and recommending.

The architecture follows a simple operational model:

SIGNALS                    INVESTIGATION                 DECISION

External Data  ─┐
Enterprise Data ├──► Specialized Agents ──► Options ──► Simulation
Documents       │        + Tools              │              │
Events          ┘        + Knowledge          │              ▼
                                           Evidence     Recommendation
                                                              │
                                                              ▼
                                                       Human Approval

My role goes beyond architecture diagrams and prototypes.

I work across the complete technology lifecycle:

Business Problem
      ↓
Product Strategy
      ↓
Solution Architecture
      ↓
Technical Validation
      ↓
Platform Engineering
      ↓
Security & Governance
      ↓
Production Deployment
      ↓
Observability & Improvement

Areas I regularly work on:

• Technology and AI strategy
• Product architecture
• Enterprise solution design
• Engineering organization and standards
• Cloud architecture
• AI platform architecture
• Security and governance
• Build-vs-buy decisions
• Architecture reviews
• Technical due diligence
• Product development
• Developer enablement
• Customer and stakeholder workshops

The systems I build are designed around a few principles:

AI must be observable.

Agents need explicit permissions and boundaries.

Enterprise AI needs evidence, not just answers.

Human approval belongs inside the architecture, not outside it.

The best AI architecture is the one that can actually run in production.

Microsoft & GitHub certifications

Microsoft

GitHub

• Accredited GitHub Partner Trainer
• GitHub Administration
• GitHub Actions
• GitHub Developer
• Using Git with GitHub

Agentic AI · AI Agents · Enterprise AI · Microsoft Agent Framework · Azure · RAG · Cloud Architecture · Multi-Agent Systems · AI Governance · Software Architecture · Engineering Leadership

I enjoy exchanging ideas with engineers, architects, founders and technology leaders working on the transition from traditional enterprise software to AI-native systems.

If you're building something around:

Agentic AI · Enterprise AI · Azure · Multi-Agent Systems · AI Platforms · RAG · Cloud Architecture

feel free to reach out.