AI agents development
We build AI agents that don't just answer: they execute real tasks in your systems with RAG, tools (function calling) and cost and security limits.
Want an AI agent that works for you?
At RoviDev we build it custom · With cost and security control · Usually reply in under 30 minutes
They take actions via APIs and function calling.
They answer from your docs, not made up.
CRM, ERP, web, WhatsApp and databases.
Cost caps, traceability and human handoff.
AI that executes, not just chats
Ideal for companies that want to automate processes with generative AI reliably: agents that query data, take actions in your systems and know when to hand off to a person.
Is this service a good fit?
Good fit if
You have repetitive processes or support that can be automated with AI connected to your data and systems, with cost control.
When we are not a fit
You want a generic chatbot demo with no connection to your data; a standard assistant is faster and cheaper there.
Typical deliverables
Agent with RAG, a set of tools/actions, prompts with escalation policy, a usage dashboard and cost limits.
Use case
A support team automates 40% of L1 tickets with an agent that queries the docs and opens a ticket when confidence is low.
Quick questions
Which models? OpenAI, Anthropic or open-source depending on cost, privacy and latency.
What about privacy? We can limit data, anonymise and deploy with access control.
First reply usually within 30 minutes with feasibility and what is missing.
How we work with you
Goals, context, priorities and time or budget constraints.
Feasibility, phases, schedule and how we collaborate, by email.
Implementation, testing and deployment with reviewable milestones.
Post-launch tweaks and improvements as agreed.
Outcomes we prioritise
Reliably automated processes, less manual work and AI cost under control. We measure by tasks resolved without intervention and time saved.
Frequently asked questions about AI agents
How is an agent different from a normal chatbot? An agent doesn't just answer: it uses tools to take actions (query data, create records, call APIs) and decides steps following goals and policies.
How do you avoid hallucinations? With RAG on your documentation, answer policies, validations and human handoff when confidence is low.
Can AI cost be controlled? Yes: token caps, caching, per-task model choice and usage monitoring to avoid surprises.
You may also like
AI chatbots · AI integration in your product · Automate customer support
Recommended reading
To decide what to automate first, this guide on automating business processes helps. Read the guide →
Related case study
NexusDesk AI — an AI assistant with RAG that resolves L1 support and escalates to humans with context. Read case study →