Customer service

Faster answers, in both languages, without losing quality

For customer-service and contact-centre leaders, especially with customers in two languages: English and French in Canada, English and Arabic in the GCC.

The question you are asked

iSystematic works with customer-service leaders who are asked whether the team can answer faster, in both languages, without losing quality. The answer has to come in the centre's own measures, against a baseline taken before anything changes.

Where most start

Most start with a six-week Pilot of the Bilingual Service Desk on one queue.

A different start fits a queue that runs in one language: a Pilot of the Front Door Agent on that queue.

How the pilot is measured

The pilot is measured in the centre's own terms, with the baseline taken before it starts.

  • First-contact resolution
  • Handle time
  • Escalation rate
  • QA sampling of replies

Quality, before go-live

Every bilingual knowledge base is reviewed by a fluent person at your organisation, and the action policy is agreed with you before go-live. Whether ARIA sits beside or in front of your existing contact-centre platform is decided and stated for your case. ARIA's assurance information is Simplification's to publish, on its own site; we never restate it as ours.

What you hold at the end: a fictional sample

This fictional pilot measurement note is for a fictional bilingual billing queue; it shows the structure, and a real note carries the centre's own figures.

MeasureHow it was takenWhat the note records
First-contact resolutionFrom two weeks of tickets before the pilot, then the same query after six weeksBefore and after, per language, and any tickets excluded with the reason
Handle timeIncluding the agent's review of every drafted replyBefore and after, per language
Escalation rateEscalations to a person, per languageThe rate, and the reasons given
QA samplingA fluent reviewer samples replies in each language every weekErrors found by type, and what was changed

Fictional, and shown without figures. A real note reports what the pilot measured, including no change or a worse result.

What it is built on

The desk is built from the same deposited frameworks as every iSystematic solution; the full stack is on How we build.

FrameworkIn this workYou keep
PARAPerception on every channel; reasoning by classification and confidence; action limited to the replies and routes the action policy lists; knowledge and skill changes only with the owner's sign-off.Agent registry entry
Tiered Human-in-the-Loop (AP-4), from the Pattern LanguageThree tiers: automatic, held for approval, and person only.Approval records
AI Data Governance Framework™Each answer exists in both languages, linked, with the translation's lineage and its fluent reviewer.Bilingual source register
AI Vendor Risk Framework (AVRF)™The front-door platform and every model provider are assessed as vendors.Vendor records; exit plan
Cross-Border AI Architecture Patterns™Where data and inference sit, chosen from the residency rules for Canada or each GCC jurisdiction.Boundary set; the chosen pattern

Until Simplification confirms that a message type can be held for approval regardless of confidence, the held tier is configured by routing to ARIA's review queue and tested before go-live.

Buying from us

You contract with iSystematic Inc., in Canada. Build work is delivered by the studio's team of 10+ expert builders; enterprise readiness work is led by Nabeel Khan personally.

First steps, such as the Automation Assessment and a Pilot, are fixed fees, shared on a short call. A build is scoped after the pilot, and AgentOps is monthly.

What the research says

These are published studies, not our results. Ours will come from documented pilots.

15% more
Customer-support agents with a generative AI assistant resolved 15% more issues per hour on average; less experienced and lower-skilled agents improved in both speed and quality.

5,172 customer-support agents at one firm, a Fortune 500 company that sells business-process software. The assistant was introduced in stages, not in a randomised trial. Task: customer-support chat, measured as issues resolved per hour.

The most experienced and highest-skilled agents saw small gains in speed and small declines in quality. The authors say the findings apply to one AI tool, used in one firm, in one occupation.

Brynjolfsson, Li and Raymond, Quarterly Journal of Economics, 2025 ↗

Published studies, not our results. Ours will come from documented pilots.

Conformance is self-declared; no regulator endorses this work.

Measure one queue before you change it