Artificial Intelligence
Current Challenges
Artificial intelligence adoption faces challenges around data quality, model interpretability, ethical governance, and talent scarcity. Organizations must navigate the gap between AI hype and practical deployment while managing bias and regulatory uncertainty.
Project History
Production systems delivered across healthcare, climate, government, streaming, finance, and enterprise.
ForkTex Intelligence — Centralized AI Inference
Production AI service layer for the ForkTex ecosystem. Multi-provider LLM orchestration (Anthropic + OpenAI), SSE streaming, structured JSON output, content extraction (PDF/Word/Excel/HTML), and Qdrant-backed vector search with optional CLIP multimodal embeddings.
Automated Compliance Document Generation
End-to-end AI pipeline auto-generating EU regulatory compliance documents for a safety consultancy. Multi-modal AI integration improved client efficiency by 80% through automated compliance workflows. RAG, vector-space search, multi-modal LLM and data embedding.