Homan Ansari

Your Industry Doesn't Need Generic AI. It Needs Domain-Specific Agents.

The Challenge

Energy and industrial companies waste 30–50% of operational capacity on repetitive tasks:

Data analysis and reporting
Maintenance scheduling
Compliance documentation
Customer support queries
Financial processing

Generic AI can't handle regulated environments or domain complexity. Pilots die in PowerPoint. Consultants deliver decks, not code.

The Solution

Pre-trained AI agents built specifically for energy and industrial workflows.

Production-ready, not pilots
Live in days, learning from every operation
Built for SOC2, HIPAA, GDPR compliance
Domain expertise baked in (patent holder)
Measured impact: 40% efficiency gains

From predictive maintenance to compliance automation. From concept to production in days, not quarters.

Not Just Another AI Expert — A Specialist in Production AI for Regulated Industries

I'm the equivalent of 913.ai for the energy and industrial sector.

While others talk about AI transformation, I've shipped 7 autonomous agents across all business functions, managing 100+ wind turbines with real-time predictive maintenance.

Patent holder in wind energy technology (DE 10 2023 134 843.4).
Director of Software Engineering & IT at MOVEAIR GmbH.
20+ years building systems that work in regulated environments.

My approach: Domain expertise first, AI second.

When you deeply understand wind energy (or manufacturing, or industrial IoT), you can build agents that ship in days, not quarters. That's the difference between consultants who deliver PowerPoints and engineers who deliver production code.

I don't do generic AI labs or research projects. I build vertical agents that handle real work, generate measurable ROI, and comply with SOC2/GDPR/HIPAA from day one.

Production AI Agents — Delivered, Deployed, Delivering Value

💬 Company Chatbot

Challenge: Customer support team buried in repetitive questions consuming 30+ hours weekly. Knowledge scattered across 10,000+ documents. Response time: 24–48 hours.

Solution: RAG-powered conversational AI with semantic search across entire company knowledge base. Pinecone vector database + LangChain orchestration + GPT-4 reasoning.

Impact: → 60% reduction in support queries
→ 95%+ accuracy rate on answers
→ Response time: instant (24/7 availability)
→ Live in production, handling real customers
→ Deployment: 3 days from concept to production

RAG Pinecone LangChain GPT-4

🎙️ Voice AI Assistant

Challenge: Executive productivity bottleneck: calendar management, email triage, meeting prep consuming 10+ hours weekly.

Solution: Personal AI assistant with voice-first interface. Multi-modal capabilities (voice, text, calendar integration). Autonomous calendar/email automation.

Impact: → 10+ hours saved weekly
→ Zero-latency voice interaction
→ Meeting prep automated
→ Context-aware task prioritization

ElevenLabs Vapi Multi-modal

👥 HR Agent

Challenge: Recruitment and onboarding workflows manual and time-consuming. Candidate screening: 40+ hours per hire.

Solution: Autonomous agent for full employee lifecycle: recruitment, screening, onboarding, support. LLM-powered candidate evaluation + workflow automation.

Impact: → Automated candidate screening
→ 50% reduction in time-to-hire
→ Consistent onboarding experience
→ 24/7 employee support availability

LLM Automation Workflows

💻 IT & Dev Agent

Challenge: Help desk overwhelmed with tier-1 tickets. Code generation requests slow. Average ticket resolution: 4+ hours.

Solution: Help desk automation + code generation + development assistance. Claude Code integration + GitHub workflows + ticket automation.

Impact: → 50% reduction in ticket resolution time
→ Tier-1 tickets handled autonomously
→ Code generation on-demand
→ DevOps workflow acceleration

Claude Code GitHub Automation

📊 Sales Agent

Challenge: Lead qualification manual and slow. Proposal generation: 8–12 hours per deal. Response time kills pipeline velocity.

Solution: AI-driven lead qualification, customer engagement, and proposal generation. GPT-4 reasoning + CRM integration + N8N workflow automation.

Impact: → 3x faster response times
→ Automated lead qualification
→ Consistent customer engagement
→ Proposal generation in minutes

GPT-4 CRM N8N

💰 Accounting Agent

Challenge: Invoice processing manual and error-prone. Expense categorization inconsistent. Compliance risk.

Solution: Invoice processing automation + expense categorization + financial reporting. LangFlow orchestration + OCR + finance system integration.

Impact: → Invoice processing automated
→ Expense categorization: 100% consistent
→ Financial reporting on-demand
→ Compliance audit trails built-in

LangFlow OCR Finance

📰 PR Agent

Challenge: Content generation time-consuming. Press release drafting: 4–6 hours each. Brand tracking inconsistent.

Solution: AI-powered content generation, press release drafting, and media monitoring. Claude for content + automated brand tracking + sentiment analysis.

Impact: → Press releases drafted in minutes
→ 24/7 media monitoring
→ Brand sentiment tracked automatically
→ Content generation on-demand

Claude Content Sentiment

🌬️ Wind Energy IoT Platform

Challenge: 100+ wind turbines requiring real-time monitoring. Predictive maintenance critical for uptime. Data volume: TB-scale.

Solution: IoT platform with AI-powered predictive maintenance and real-time analytics. AWS IoT + InfluxDB time-series + ML models for anomaly detection.

Impact: → 100+ turbines monitored in real-time
→ Predictive maintenance prevents downtime
→ Anomaly detection catches issues early
→ Data-driven optimization
→ Patent: DE 10 2023 134 843.4 (Wind Energy Conversion Technology)

AWS IoT InfluxDB ML Analytics