AI agents that act on your operations

AxionIQ builds and operates AI agents that handle repetitive operational work end to end: routing leads, processing orders, reconciling exceptions, drafting and sending follow-ups. They run inside your real stack, with the right approval gates, so your team gets out of the inbox and into judgement work.

What it does

An operations agent takes a defined workflow you would otherwise pay a person to do and runs it on a schedule or in response to a trigger. Common patterns we see: routing inbound leads from web forms and email into the correct CRM owner with enrichment attached, processing supplier invoices against purchase orders and flagging only the exceptions, reconciling daily payments between Stripe and your ledger, drafting and sending personalised follow-ups to quotes that have gone quiet for more than five days.

Each action the agent takes is logged with its reasoning and the data it saw. You get an audit trail. The agent escalates anything outside its scope or confidence threshold to a named human, with the suggested action drafted ready to approve.

How AxionIQ implements it

We start by mapping a single workflow end to end with the team that owns it today. We agree the success metric: cycle time, error rate, percentage handled without human touch. We design the agent against your real systems, build the tool integrations, and deploy first in shadow mode where it proposes actions for human approval. Once accuracy is proven on real volume, we graduate it to autonomous within the agreed guardrails.

Build & Run keeps the integrations healthy, monitors accuracy week by week, and rolls in new edge cases as they appear. We do not ship and forget. The operating model is the product.

ROI examples

A logistics operator routed inbound carrier enquiries through an agent that pulled tracking, generated a tailored reply, and only escalated genuine exceptions. Around 80 percent of enquiries closed without human touch. An e-commerce finance team replaced four hours of daily Stripe-to-ledger reconciliation with an agent that flagged only mismatches above a tolerance, freeing the controller for higher value work. A B2B sales team recovered a meaningful number of stalled quotes through scheduled personalised follow-ups the team would not have had time to write.

Where this fits

Operations agents pair tightly with data unification, because an agent is only as good as the data it acts on. They also extend customer support agents from "answer the question" to "do the thing". Strongest fit by industry: logistics, e-commerce and estate agents.

Common questions