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CASE STUDY · AI EMPLOYEE ASSISTANT
HEALTHCARE · MULTI-SITE DENTAL GROUP

One Source of Truth for a Team Spread Across Four Practices

A multi-site dental group was losing time to the same internal questions and slow new-hire ramp-up. MCEL built an internal AI assistant on the group's own procedures — so every team member gets consistent answers instantly.

CLIENT TYPE

Multi-location dental group

LOCATION

Ireland

TEAM SIZE

Four practices, ~40 staff

SOLUTION

AI Employee Assistant (incl. Knowledge Base setup)

DELIVERED BY

MCEL · mcel.ai

↓50%

fewer internal 'how do we do this?' interruptions

3 mo → 4 wks

new-starter ramp-up time

4

practices answering consistently

THE SITUATION

The Same Promise at Every Location — Held Together by a Few People

The group runs four dental practices under one brand, with around forty staff across reception, nursing and clinical roles. Consistency is part of the promise: a patient should get the same answer about a procedure, a price or a policy at any location. Delivering that consistently, though, depended on a handful of experienced people.

In practice, staff spent a surprising amount of the day asking each other the same questions — which consent form to use, how a particular treatment is priced, what the cancellation policy is, how to handle a specific booking scenario. The answers lived in long documents, old emails, and the memories of senior team members who were constantly interrupted.

The cost showed up most with new hires. Onboarding a new receptionist or nurse meant months of 'ask the person next to you' before they could work independently — and when an experienced staff member left, some of that knowledge left with them.

THE CHALLENGE

Knowledge Trapped in Too Few Heads

MCEL reviewed what the team asked most and where the answers actually lived. Four problems recurred across all four sites.

01

Constant internal interruptions

Experienced staff were pulled away repeatedly to answer routine questions instead of doing their own work.

02

Slow, inconsistent onboarding

New starters took months to become independent, and different people taught them slightly different things.

03

Inconsistent answers between sites

The same policy question could get two different answers at two practices.

04

Knowledge that walked out the door

When someone experienced left, their undocumented know-how went with them.

WHAT MCEL BUILT

A Private Assistant Trained on the Group's Own Knowledge

MCEL gathered, cleaned and structured the group's procedures, policies, pricing and FAQs, then built an internal AI assistant on top — available to every team member, with clear boundaries. The structured knowledge base is a lasting asset in its own right. Figures below are representative of typical outcomes for a group of this size.

01

Knowledge base setup

Procedures, policies, pricing and FAQs were gathered from scattered documents and people's heads, then cleaned and structured into one source of truth.

KNOWLEDGE BASEPROCEDURE ANSWERS
02

Plain-language assistant

Staff ask questions the way they'd ask a colleague; the assistant finds the answer and phrases it clearly, from the group's own content — not the open internet.

CONSISTENT RESPONSES
03

Safe boundaries

The assistant only knows what the group approves, and is configured to say 'check with a manager' on anything clinical, sensitive or out of scope.

SAFE BOUNDARIES
04

Always current

When a policy or price changes, it's updated once and everyone gets the new answer immediately — no re-briefing four sites.

POLICY ANSWERS
05

Onboarding mode

New starters get a patient, always-available teacher for the basic questions, cutting the load on senior staff.

CONSISTENT RESPONSESONBOARDING FLOW
IMPLEMENTATION

From Scattered Documents to Working Assistant

01

Knowledge review

Identified the most-asked questions and where the answers currently lived across the four sites.

02

Knowledge base build

Gathered, cleaned and structured the procedures, policies and service information.

03

Assistant setup

Configured the assistant, set access rules and boundaries the group approved, and connected it where the team works.

04

Test, launch & maintain

Staff tested it with real questions; MCEL refined, launched and set a routine to keep the knowledge current.

CLIENT FEEDBACK

New staff get answers instantly instead of interrupting the senior team, and everyone gives the same answer now — whichever practice you walk into.

— Group Operations Manager, Dental Group
THE RESULTS

Consistent Answers, Faster Onboarding, Fewer Interruptions

The change was felt first by the senior staff who'd been the group's unofficial help desk. Figures are representative of typical outcomes for a multi-site group of this size.

↓50%

fewer internal 'how do we do this?' interruptions

3 mo → 4 wks

new-starter ramp-up to independence

4

practices now answering consistently from one source

100%

of core policies and pricing in one structured, current place

24/7

instant answers for staff across every shift

1

lasting knowledge base owned by the group, independent of the AI

Before & After

AREABEFOREAFTERSTATUS
Routine questions

Senior staff interrupted all day

Answered instantly by the assistant

RESOLVED
Onboarding

Months of 'ask the person next to you'

Weeks, with a 24/7 teacher

RESOLVED
Consistency

Answers varied by site and person

Same accurate answer everywhere

RESOLVED
Knowledge retention

Left when experienced staff left

Captured in a structured knowledge base

RESOLVED
Updates

Re-briefing four sites by hand

Updated once, live everywhere

RESOLVED
Representative example — this study illustrates a typical engagement and typical outcomes for this service, drawn from MCEL delivery experience. Figures are deliberately conservative; individual results vary.
WHY IT MATTERED

A Knowledge Base You Own, With an Assistant on Top

The group's problem wasn't a lack of knowledge — it was that the knowledge was scattered and locked in a few heads. Structuring it was valuable on its own; putting an assistant on top made it usable by everyone, instantly.

Because the assistant answers only from approved content and defers on anything sensitive, the group got speed and consistency without giving up control — a genuine concern in a clinical setting.

The same structured knowledge can later power a patient-facing receptionist or response system, so the work compounds rather than being a one-off.

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