AI consulting and implementation for enterprise Gen AI, ML, and data infrastructure
ITRex builds production AI systems across the Gen AI, ML, and data stack for mid-market and enterprise clients. The tech footprint reflects a dual-track operation: classical ML and data engineering (Python, TensorFlow, PyTorch, Snowflake, Fivetran) paired with modern cloud infrastructure (AWS, GCP, Docker, Lambda). Senior engineering-heavy hiring (9 of 10 open roles) concentrated in Poland, Romania, Serbia, and Portugal signals aggressive scaling of delivery capacity; no adopting or replacing signals visible in the stack, indicating stability in their chosen toolchain.
Notable leadership hires: Head of People
ITRex is an AI consulting and implementation firm founded in 2009, based in Aliso Viejo, California, with 201–500 employees. The company delivers production-grade Gen AI solutions—including LLM integration, RAG, AI copilots, autonomous agents, and LLMOps infrastructure—alongside classical ML, computer vision, and data engineering work. Core verticals include healthcare, biotech, pharma, retail, logistics, and manufacturing. The consulting practice spans strategic readiness assessments, proof-of-concept-to-production pathways, compliance enablement (HIPAA, SOC2, EU AI Act), and governance layers. Delivery is backed by vector databases (Pinecone, FAISS, Weaviate), unstructured data pipelines, and ML infrastructure on AWS and GCP.
Backend: .NET, C#, Python, PostgreSQL, SQL Server. ML/Data: TensorFlow, PyTorch, scikit-learn, Pandas, NumPy. Cloud: AWS (ECS, Lambda, Snowflake, ElastiCache), GCP. Frontend: Angular, TypeScript, JavaScript. DevOps: Docker, CloudWatch, Route 53.
Generative AI, RAG, LLM integration (GPT, Claude, Gemini, LLaMA, Mistral), autonomous agents, LLMOps, classical ML, computer vision, and production data infrastructure. Services span use-case roadmaps, PoCs, compliance, and at-scale deployment.
ITRex Group's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.