AI agents by WhiteGuava that reason, use tools, and finish the job, connected to your business systems, not stuck in a chat window.
What an AI agent actually is
What is an AI agent, in practice? It is not a FAQ script. It can read a request, decide which tools or data it needs, take steps, and hand off to a person when it should. We build that behaviour around your workflows, permissions, and source systems.
WhiteGuava agents show up as customer support assistants, WhatsApp AI agents, internal knowledge assistants, and operations helpers. They use RAG (retrieval-augmented generation) so answers come from your documents and databases, not from generic internet text, the same LLM application development approach frameworks like LangChain are built around, applied to your specific systems.
The best conversational AI is not the one with the cleverest replies, it is the one that actually knows your business and knows when to stop and ask a human. That is the standard we build agents to.
How we build agents
Tool-using agents
Agents can call APIs, look up records, create tickets, and follow your business rules. MCP and custom tools are used when the work needs more than a prompt.
Private knowledge
RAG systems connect the agent to policies, product data, and internal wikis so it stays grounded in your information.
Support and operations
Typical builds include customer support agents, internal assistants, and workflow agents that move work across CRM, email, and chat.
Production, not a prototype
Logging, evaluation, human escalation, and deployment are part of the build. An agent that only works in a demo is not finished.
Conversational AI that stays on-topic
We scope what the agent should and should not answer, so a conversational AI system stays useful instead of drifting into generic small talk.
LLM and RAG architecture
Model choice, retrieval design, and evaluation are treated as engineering decisions, the same discipline behind serious LLM application development.
Where agents get used
Customer support
First-line support that resolves common requests and escalates the rest with full context, instead of a bot that dead-ends every unusual question.
Sales and lead qualification
An AI sales agent that responds to inbound interest immediately, asks qualifying questions, and books time with a human rep when it counts.
Internal HR and operations
From candidate screening support to internal policy lookup, agents built for AI in HR and recruitment work the same way as customer-facing ones, grounded in your actual documents.
Frequently Asked Questions
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