AI Operations Systems
The companies winning in 2026 are running on AI. We build the systems.
We build autonomous AI agents, LLM-powered applications, and enterprise RAG systems that execute real business workflows — not prototypes. Our AI engineering team ships production systems on GPT-4o, Claude, Llama, and open-source models with the orchestration, monitoring, and operational infrastructure to run them reliably.
What We Deploy
Production AI systems that execute workflows, not just answer questions.
AI Agent Architecture
Multi-step autonomous agents built on LangChain, LangGraph, and CrewAI that execute business workflows without human intervention — from document processing to customer operations.
LLM Application Development
Production-grade applications built on GPT-4o, Claude, and Llama. Model selection, prompt engineering, fine-tuning, evaluation frameworks — the full engineering stack.
Enterprise RAG Systems
Retrieval-augmented generation over your proprietary data: vector databases (Pinecone, Weaviate, pgvector), embedding pipelines, retrieval optimization, and grounding infrastructure.
AI Workflow Automation
Replace manual operational processes with AI-driven decision and execution systems. Document processing, classification, routing, and approval workflows — automated and auditable.
Operational Intelligence
Real-time dashboards and AI-powered analytics that surface decisions rather than displaying numbers. Anomaly detection, forecasting, and automated insight generation.
AI Integration Engineering
Connect AI capabilities to your existing CRM, ERP, and business systems. We build the integration layer that makes AI useful inside your actual workflows, not alongside them.
Want to understand how we approach AI engagements?
Our 5-phase AI Transformation Framework documents the methodology behind every AI project we run — from readiness assessment to enterprise operations.
How We Ship AI Systems
From AI readiness assessment through production deployment and LLMOps.
AI Readiness & Problem Definition
We assess your data infrastructure, define the specific business workflow to automate, and design the AI system architecture before any development begins.
Prototype & Validate
A working prototype with real data in 2–3 weeks. We validate model selection, retrieval quality, and output reliability before committing to a production architecture.
Production Engineering
Build the full system: APIs, orchestration layer, evaluation framework, human-in-the-loop controls, audit trails, and error handling for production-grade reliability.
Integration & Testing
Integration with your existing systems, end-to-end testing with real operational scenarios, performance benchmarking, and adversarial testing for edge cases.
Deployment & LLMOps
Production deployment with monitoring, drift detection, evaluation pipelines, and the operational infrastructure to maintain AI system quality over time.
Book a Free Scoping Call.
Get on a call and walk away with a 1-page build plan within 48 hours — what we'd build, how long it'd take, and what it costs.