AI agents that do real work, not just answer questions

What problem does this solve?

Many teams want AI to do useful work, not sit as a disconnected experiment. The challenge is turning language models and agents into reliable systems that fit real operations.

How does Zygrix approach it?

Answers come from your approved content, with source references, guardrails and fallback to a person when confidence is low.

Where is this used?

• Lead qualification and website chat
• Appointment booking and scheduling
• Order status and customer support
• HR and IT helpdesk
• Policy and contract questions
• Sales research and follow-up

What we deliver

• Website chatbots and assistants that answer questions, qualify leads and hand off to humans
• Voice calling agents for inbound support and outbound follow-up
• Booking and scheduling agents connected to calendars, CRMs and payment tools
• Internal knowledge assistants over your documents, wikis and databases (RAG)
• Multi-step task agents that research, draft, update records and trigger workflows
• Human-in-the-loop controls, logging and escalation rules

What tools do we use?

We select models, agent frameworks, retrieval stores and voice platforms based on the job, the data boundary and the systems the agent must call.

Who is this for?

Teams that need an assistant, agent or model grounded in company data.

What is the outcome?

You get practical intelligence in the product or process: fewer manual steps, faster answers and systems that help people work with more clarity.

See an agent demo