03

Knowledge and automation

Support and service operations automation

Triage, enrich, draft, route, and resolve service work while preserving escalation and quality review.

Primary buyer: Customer support and service operations leaders
01Primary buyerCustomer support and service operations leaders
02Target outcomeShorter handling time and better context without unsafe autonomous resolution
03Useful starting pointTicket history, categories, knowledge, tools, escalation rules, quality rubric, and handling-time baseline.
01

The real constraint

Business knowledge is fragmented, permissions matter, and a fluent answer is not the same as a correct action.

02

How we approach it

We make sources, tools, approvals, audit trails, confidence, and exceptions explicit in the workflow.

03

How we prove it

Representative tasks are evaluated end to end against correctness, completion time, exceptions, and reviewer effort.

Production system

Knowledge and automation

Controlled systems that retrieve, reason, extract, route, and ask for human judgment when needed.

  • 01Knowledge and permission model
  • 02Retrieval and structured extraction
  • 03Agent tools and workflow state
  • 04Human review and exception routing
  • 05Audit, monitoring, and retention

Typical fit

Shorter handling time and better context without unsafe autonomous resolution

IndustriesSoftware / SaaSRetail / e-commerceEnterprise teams
TechnologyLLMAgentsRAG

FAQ

Questions before a pilot

These answers describe how we normally work. Only a signed agreement creates commitments. Website enquiry terms

01Our documents are inconsistent and half of them are scans. Is that a problem?

It is normal, and it is the actual work. Clean, uniform documents would not need us. What matters is whether the variation is bounded, because twenty supplier formats is a project and an unbounded long tail is a different conversation. We establish which one you have during discovery, on your own documents.

02Will it act on its own, or does a person stay in the loop?

A person stays in the loop wherever an error is expensive to reverse. We agree the approval points and confidence thresholds with you, and anything below the threshold goes to a review queue with the supporting evidence attached rather than being silently guessed.

03How do you stop it inventing answers?

By grounding it in your own sources and showing them. Every answer carries the passage it came from, so a reader can check it in one click, and the system is built to say it does not know rather than to fill the gap. That reduces invention rather than eliminating it, which is why the review queue and the citations exist.

Service focus

Faster tickets without answering the wrong ones automatically

Most support automation either does too little or resolves things it should not have touched. We keep the agent in the loop: the system triages, enriches with context, and drafts, while a person still approves anything that carries risk. Quality is measured against your own rubric, not a vendor demo.

Built for
Customer support and service operations leaders
Designed to achieve
Shorter handling time and better context without unsafe autonomous resolution

What you get

  • Triage and routing tuned on your ticket history
  • Context enrichment from your knowledge and systems
  • Drafted replies with human approval retained
  • Quality scoring against your existing rubric

Need a different system?

Not quite your solution?

Explore nearby systems or bring the outcome, workflow, and constraints that do not fit a predefined category. Tandemora can scope a custom solution around the real operating problem.

Your version will have different constraints.

Bring the workflow, current system, available evidence, and the assumption you trust least. We will identify the smallest useful next step.

Discuss this system