P34 · Implementation blueprint · Mappls Video Safety Centre

Video Telematics, ADAS & Driver Safety

Unsafe driving and incidents are reviewed after the fact, with limited context or coaching closure.

01 · Target operating outcome

Define the change before choosing the technology

Can you identify and coach the riskiest driver-route combinations before the next incident?

Fewer preventable incidents; lower claims/downtime; better coaching completion and evidence availability.

Baseline

Measure current volume, time, cost, failure, service, risk and revenue at the workflow level.

Target

Event precision accepted; coaching SLA achieved; risky events/1,000 km trend improves; privacy/security passed.

02 · Solution architecture

One connected flow from source data to operational action

AI dashcam/MDVR, ADAS/DMS events, video evidence, harsh-driving analytics, risk scoring, coaching workflow and journey risk integration. Mappls connects proprietary map and location intelligence with ai dashcam/mdvr, adas/dms events, video evidence, harsh-driving analytics, risk scoring, coaching workflow and journey risk integration. We start with one measurable workflow, prove the operating impact, and scale through reusable data, APIs and SaaS rather than a one-off implementation.

Data foundation

Map, customer, asset, sensor and enterprise data

Intelligence services

Search, routing, GeoAI, rules and spatial models

Role workflows

Risk feed · Video review · Incidents · Coaching · Safety score

Decision and outcome

Fewer preventable incidents; lower claims/downtime; better coaching completion and evidence availability.

03 · Users and RBAC

Give every stakeholder the view and actions they actually need

Sponsor / owner

Head Safety

Sponsor / owner

Fleet Operations

Manager / analyst

HSE

Manager / analyst

COO

Manager / analyst

EHS Director

Operator / specialist

Risk Head

Operator / specialist

Telematics

Operator / specialist

Dashcam

Operator / specialist

AI/Video

Operator / specialist

Legal

The shared Mappls identity is separated from application membership. A user can be an administrator in one app, an analyst in another and a viewer elsewhere.

04 · Data and integration

Connect the minimum information needed to make the workflow real

Location foundation

Map, road, address, place, imagery, boundary and terrain layers appropriate to the decision.

Enterprise context

Customer, order, asset, vehicle, incident, task, sensor or transaction records from systems of record.

Integration pattern

APIs, SDKs, secure batch, streaming events, webhooks, files or on-premise integration depending on architecture.

Security and control

Least-privilege RBAC, audit events, encrypted transport, tenant separation and cloud, private or offline deployment.

Recommended Mappls building blocks

Dashcam / Video Telematics

AI video, ADAS/DMS events and evidence

Product details

Traffic, ETA & Road Events

Live/historical traffic, ETA and safety/road events

Product details

ClarityX Location Analytics

Market, territory, network and spatial decision analytics

Product details

ADAS/HD & Safety Data

Lane, road attribute, risk and predictive horizon data

Product details

05 · Proof of value

Use a bounded implementation to answer the scale decision

8-week cohort with calibrated events, evidence workflow, driver risk score and coaching cycle.

  • Confirm data, geography, users and workflow: Which events matter? What is incident/claim baseline? Who reviews video and closes coaching? What privacy rules apply?
  • Configure Mappls Video Safety Centre for the selected role set
  • Run baseline and intervention scenarios with real stakeholder reviews
  • Evaluate agreed criteria: Event precision accepted; coaching SLA achieved; risky events/1,000 km trend improves; privacy/security passed.
  • Package production scope and commercial model: Device + per-vehicle/month SaaS + managed review option.

06 · Rollout and operating model

Move from proof to governed adoption

Week 0–2
Discover

Baseline, data, stakeholders, security and architecture

Week 3–6
Configure

Data connection, role workflows, rules and dashboards

Week 7–10
Prove

Live users, measurement, change support and decision review

Production
Scale

Phased geographies, integrations, service model and continuous improvement