Applied AI Engineering
We build deterministic AI agents and automation systems for engineering teams that can't afford unpredictable behavior.
What We Do
aixagent.io is a specialized AI engineering practice. We don't sell AI strategy decks or generic consulting—we build production-grade AI systems with engineering teams.
Our work is focused on a specific problem: most AI agent demos look impressive, but production deployment in regulated industries requires a fundamentally different approach. We specialize in the engineering patterns that make AI reliable, auditable, and maintainable at scale.
Deterministic Agents
Graph-based agent architectures with explicit state machines and auditable execution paths.
RAG Pipelines
Retrieval-augmented generation systems that ground LLM outputs in verifiable source documents.
Enterprise Governance
Audit trails, access controls, and compliance documentation for regulated industry deployments.
Our Approach
We operate on a sprint model. Rather than long engagements with uncertain outcomes, we run focused 2-week engineering sprints with defined deliverables. Each sprint ships something that works in your environment—not a proof of concept on synthetic data.
We map your workflows, identify the highest-value AI automation opportunities, and assess your data and infrastructure readiness.
We architect and implement the agent system, including guardrails, observability, and integration with your existing tools.
We run evaluation suites, tune performance, document the architecture, and transfer ownership to your engineering team.
Based in Sophia Antipolis
We're headquartered in Sophia Antipolis, France—Europe's largest technology park, home to R&D centers for dozens of global technology companies. This puts us within the European regulatory environment and close to the enterprise clients who need AI systems built to GDPR and EU AI Act standards.
We work with clients across Europe and globally, primarily in fintech, legal tech, healthcare IT, and engineering services. Our engagements are conducted primarily in English and French.
Engineering Values
- → Determinism over magic. We design AI systems with explicit state machines and predictable execution paths. If you can't explain how a decision was made, it shouldn't be in production.
- → Measurement before optimization. We instrument everything before we improve anything. Intuition about AI system performance is usually wrong; data is usually right.
- → Humans stay in the loop. For decisions with real consequences, we design mandatory human checkpoints. Automation should augment human judgment, not replace it for high-stakes decisions.
- → Simple before complex. We resist the temptation to build multi-agent systems when a well-designed single agent would work. Complexity compounds failures.
Work with us
Describe your workflow automation challenge and we'll assess whether it's a good fit for an AI agent sprint.
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