ALL SERVICESAI agents that work in production.
RXY Studio builds production AI systems: agents that use your tools and data, retrieval over company knowledge, automated workflows and the model integration behind them—evaluated before every release, bounded by permissions and hosted by the same team.
AI agents can do real work: research, support, operations, analysis.
Most never leave the demo, because nobody built the system around them.
Agents with clear tools, clear limits and tests that prove they work.
Measured on cost, quality and speed—and improved every week.
What is an AI agent?
An AI agent is a model that can take actions: it reads information, decides on next steps and uses tools—APIs, databases, documents—to complete a task. In a business, an agent replaces a sequence of manual steps with a supervised, automated one.
What do you build?
- AI agents for research, support, sales operations and internal workflows.
- Retrieval over company knowledge, so answers come from your own sources.
- Automated workflows that connect agents to the systems they act in.
- Model selection and routing across providers such as OpenAI, Anthropic, Google and open-weight models.
- Evaluation suites that test quality before every release.
How do you keep agents safe and reliable?
Every agent gets only the tools and permissions it needs, actions that matter require human approval, and every step is logged. Prompt injection and excessive agency are among the top risks in the OWASP Top 10 for LLM applications, so we design against them from the first version.
AI engineering & agents,
end to end.
AI agents
Agents with defined tools, limits and approval steps.
Knowledge retrieval
Answers grounded in your documents, systems and data.
Automation
Workflows that run reliably without supervision.
Evaluations
Quality, cost and speed measured before and after every release.
Questions,
answered first.
01Which AI models do you use?
We are model-agnostic and choose per task—frontier models from OpenAI, Anthropic and Google or open-weight models such as Llama and Mistral—based on quality, cost and data requirements.
02Can AI agents access our internal systems safely?
Yes, with least-privilege access: each agent gets only the tools it needs, sensitive actions require approval and every action is logged.
03How do you measure whether an agent works?
With evaluation suites built from real cases. Every release is tested for quality, and production usage is monitored for cost, speed and errors.
Ready to build
what comes next?
One team for strategy, design, software, AI, security, hosting and visibility. Tell us where you want to go.
Start a project