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Service

Agents that finish the work, not just suggest it

Multi-step agents that plan, call tools and take action inside your systems, replacing manual, rules-based automation with something that can reason through exceptions.

What is included

What you get

Scope is agreed with you up front and tailored to your situation. These are the building blocks.

Workflow agents

Agents that handle multi-step tasks such as triage, research, reconciliation and follow-up across your tools.

Tool and API integration

Secure connections to your CRM, ERP, ticketing and internal services so agents can act, not just chat.

Human-in-the-loop controls

Approval steps, audit trails and limits on what an agent may do without sign-off.

Monitoring and evaluation

Traces, success metrics and regression tests so agent behaviour stays reliable as things change.

Who it is for

Is this right for you?

Operations and engineering teams carrying repetitive, exception-heavy processes that traditional automation handles poorly.

Typical uses

Common starting points

  • Ticket triage and routing with context pulled from several systems
  • Invoice, order or claims processing with exception handling
  • Research and reporting tasks assembled from multiple sources
  • Back-office workflows that currently depend on manual copy-and-paste
How we deliver

From first call to results

Short feedback loops and working output at every step, in overlap with your time zone.

01

Pick a process

Choose a workflow with clear inputs, outputs and a measurable baseline.

02

Design controls

Define what the agent can do alone and where a person approves.

03

Build & test

Implement with tool access, then test against real and edge-case examples.

04

Operate

Monitor outcomes, review failures and expand scope gradually.

Questions

Frequently asked

Are agents safe to let loose on production systems?

We start with narrow permissions, approval gates and full logging, and widen autonomy only as the evidence supports it.

How is this different from RPA?

Rules-based automation breaks when inputs vary. Agents can interpret messy inputs and decide next steps, with guardrails around what they may do.

What if the agent gets something wrong?

Actions are logged and reversible where possible, and uncertain cases are routed to a person instead of guessed.

Next step

Tell us what you are trying to achieve

Share a few details and we will reply with an honest view on whether and how we can help.

Contact Qualsys