AI solutions and services overview

Our Services

Three Services, One Consistent Standard

Each of our service lines is designed around a specific point of organisational need — and each is delivered to the same standard of quality, documentation, and knowledge transfer.

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Our Approach

How Every Engagement Is Structured

Regardless of which service you engage, every Sinergi Labs project follows a structured four-phase approach that prioritises understanding before action.

01

Discovery

We begin with structured conversations to understand the organisational context, current state, and what a successful outcome looks like for your team.

02

Scoping

Deliverables, timelines, responsibilities, and success criteria are documented and agreed before work begins. No surprises on either side.

03

Delivery

Senior consultants carry out the agreed work, maintaining open communication with your team throughout and flagging any material issues promptly.

04

Handover

All outputs are formally handed over with supporting materials, reference documentation, and a walkthrough session for your team.

Service 01

AI-Integrated Training Platform Design

This consulting engagement is designed for L&D directors and training managers who recognise that their current corporate training infrastructure needs to evolve — but want to do so deliberately rather than being pulled along by vendor marketing. We help you design what an AI-enhanced version of your training ecosystem should look like, and how to get there from where you are today.

The output is not a generic platform recommendation. It is a specification document tailored to your organisation's structure, learning objectives, technical environment, and budget — one that your technology team or chosen vendor can build against.

Adaptive learning path architecture specification

Knowledge gap identification and content recommendation logic design

Progress analytics framework and reporting approach

Integration planning with existing HRIS and LMS systems

Pilot programme design and evaluation criteria

Starting from

RM 850

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AI training platform design

Process Steps

1
Training ecosystem audit
2
AI opportunity mapping
3
Architecture specification
4
Pilot design & handover
Time-series forecasting workshop

Process Steps

1
Dataset assessment & preparation
2
Model selection & feature engineering
3
Hands-on model building sessions
4
Validation & stakeholder communication

Service 02

Time-Series Forecasting Workshop

Demand planning inaccuracies, poor resource utilisation, and financial projections that miss the mark are often symptoms of teams that understand their data but lack the tools to extract forward-looking signals from it. This workshop addresses that gap through direct, applied training on AI-driven forecasting methods.

Participants work with datasets that reflect the kinds of business challenges they face day-to-day — seasonal demand patterns, cyclical financial indicators, and resource utilisation trends. The curriculum covers the full workflow from raw data to a model that stakeholders outside the team can understand and act on.

Demand planning, resource utilisation, and financial forecasting contexts

Model selection guidance appropriate to business context

Validation techniques and confidence interval communication

Post-workshop assessment to confirm learning transfer

Reference materials and methodology guide for continued use

Starting from

RM 2,250

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Service 03

AI Vendor Evaluation Advisory

The AI vendor market in Malaysia and globally is expanding rapidly — and not uniformly. For every well-suited solution, there are several that are over-promised, poorly matched to local operational contexts, or priced in ways that make long-term value difficult to assess. CIOs and procurement teams navigating this landscape frequently face a shortage of independent guidance.

Our advisory engagement provides that independent perspective. We document your requirements rigorously, map the relevant vendor landscape, design and oversee proof-of-concept evaluations, build a transparent scoring framework, and support the final selection and early contract negotiation.

Structured requirements documentation workshop

Vendor landscape mapping across relevant AI categories

Proof-of-concept design and evaluation facilitation

Scoring framework development and vendor shortlisting

Contract negotiation support and red flag identification

Starting from

RM 3,710

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AI vendor evaluation process

Process Steps

1
Requirements documentation
2
Vendor landscape mapping
3
POC design & scoring
4
Selection & contract support

Choose Your Path

Which Service Fits Your Situation?

Consideration Platform Design Forecasting Workshop Vendor Advisory
Primary audience L&D directors, HR leaders Analytics teams, planners CIOs, procurement leads
Typical engagement 4–8 weeks 2–3 days intensive 3–6 weeks
Starting price RM 850 RM 2,250 RM 3,710
Best for Building AI training infrastructure Upskilling on forecasting methods Selecting an AI technology vendor
Primary output Platform specification document Applied skill + reference materials Scored vendor evaluation report

Across All Services

Shared Professional Standards

Data Confidentiality

All client data governed by PDPA-aligned practices and mutual NDA before any work begins.

Senior-Led Delivery

Named consultants from the proposal deliver the work — no delegation to junior staff after signing.

Documented Scope

Scope, deliverables, and success criteria are written and agreed before any engagement begins.

Vendor Neutrality

No commercial relationships with any AI vendor influence our recommendations on any engagement.

Knowledge Transfer

All projects include materials for continued independent use by your team after the engagement closes.

Transparent Communication

Material issues, scope considerations, or changed circumstances are communicated promptly and clearly.

Not Sure Which Service Fits?

We are happy to have a brief initial conversation to understand your situation and recommend which engagement — if any — would be a sensible fit. There is no obligation attached to that initial discussion.

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