Custom AI agent development for complex enterprise workflows

We engineer distributed AI agent architectures capable of autonomous coordination, context sharing, and parallel task execution across complex workflows.

Our team fine-tunes and grounds large language models on your proprietary data and internal systems, ensuring task relevance, accuracy, and compliance.

We deliver production-ready agent systems in weeks through mature CI/CD pipelines, automated testing frameworks, and standardized delivery playbooks.

Our agents are designed to handle multi-step reasoning, conditional logic, and integrated task execution across CRMs, ERPs, and internal services.

We support cloud, on-premise, and hybrid deployments with native integration into enterprise tools and systems via secure APIs and middleware.

Leverage OpenAI, Claude, Gemini, or proprietary models without vendor lock-in — Xenoss provides the orchestration layer and interface abstraction.

Our systems include RBAC, encrypted data handling, activity logging, and audit readiness aligned with ISO 27001, SOC 2, and internal IT policies.

Our solutions are designed to reduce total cost of ownership through lean orchestration, efficient inference strategies, selective LLM routing, and infrastructure-aware deployment models.