AI agents, LLM-powered workflows, and intelligent automation systems — built for reliability, not just demos. We ship AI that handles real-world complexity at scale.
Arthiq builds production-grade AI systems — not ChatGPT wrappers with a logo on top. We develop AI agents, LLM-powered workflows, and intelligent automation that solve real business problems with robust error handling, monitoring, and fallback strategies built in from day one.
Our AI engineering team works across the full stack: from RAG pipelines and knowledge retrieval systems to multi-agent orchestration, fine-tuned language models, computer vision, and document extraction. We integrate with OpenAI, Anthropic, open-source models, and build custom solutions when off-the-shelf doesn't cut it.
We've built our own AI products — InvoiceRunner for automated invoice processing and AgentCal for autonomous meeting scheduling. We understand the difference between AI that impresses in a demo and AI that works reliably at 3 AM with no one watching. We build the second kind.
From standalone AI features to complete intelligent systems — we build AI that creates measurable business value.
Autonomous agents that use tools, make decisions, and execute multi-step workflows. Customer support, research, data processing, and operational automation.
Enterprise-grade LLM integration with prompt engineering, caching, rate limiting, cost management, and quality monitoring. Not a wrapper — a system.
Retrieval-augmented generation pipelines that give your AI accurate, up-to-date knowledge from your own data. Documents, databases, APIs — any source.
AI-powered automation that replaces manual processes — document processing, data extraction, classification, routing, and end-to-end business workflows.
Natural language interfaces for your products — chatbots, voice assistants, and conversational UIs that understand context, maintain state, and resolve issues.
Fine-tuning and custom model development for domain-specific tasks. Data preparation, training pipelines, evaluation frameworks, and deployment infrastructure.
We work with the best tools for the job, not the trendiest ones. Our AI engineering team has deep expertise across the major LLM providers, agent frameworks, and ML infrastructure — and we'll guide you to the right combination for your use case.
For most projects, we start with API-based LLM integration (OpenAI, Anthropic) because it ships fastest and costs least. When the use case demands it — domain-specific understanding, strict latency requirements, or data privacy constraints — we move to fine-tuned or self-hosted models.
Our production AI systems include comprehensive observability: token usage tracking, latency monitoring, output quality evaluation, cost dashboards, and automated alerting. You always know how your AI is performing and what it's costing.
A structured approach to shipping AI systems that work reliably at scale.
We assess your use case, evaluate available data, and determine the right AI approach. Build vs. buy, API vs. fine-tune, agent vs. pipeline.
We build a working proof of concept within 2-3 weeks. Real data, real outputs — so you can evaluate quality before committing to full development.
We harden the prototype into a production system with error handling, monitoring, guardrails, caching, and scalable infrastructure.
We deploy, monitor, and continuously improve. AI systems get better with real usage data — we build the feedback loops that make that happen.
Common questions about our AI development and automation services
Tell us about your AI project and we'll share our assessment — feasibility, approach, timeline, and tech stack. No obligation, no sales pitch.