Eagentix Hands-On AI Training

Sales & Marketing AI Training Singapore

Hands-on AI training in Singapore for sales and marketing teams on Copilot, ChatGPT, Gemini, Claude or Amazon Q, using your own proposals and content.

AI training for sales & marketing teams

AI training for sales and marketing teams

Sales and marketing teams already use AI to write faster. What most have not been shown is how to keep it accurate: separating what a source says from what the assistant inferred, and keeping unapproved claims out of proposals and campaigns. This is a hands-on programme for account managers, sales teams and marketers who need to apply Microsoft Copilot, Claude Cowork, Gemini Enterprise, Amazon Q Enterprise or ChatGPT Enterprise to account research, proposals, campaigns and follow-up — with the brand and factual checks built in. Sessions are delivered in Singapore, on site or remote, using your tool licences and anonymised versions of your own material.

Who this programme is for

Sales, account management and marketing teams.

  • Account managers and sales teams preparing for discovery meetings and renewals
  • Bid and proposal teams responding to RFPs and tenders
  • Marketers adapting approved content across channels and audiences
  • Sales and marketing leaders deciding which claims AI may draft and who approves them

Who it is not for

  • Teams looking for a vendor demo rather than hands-on practice
  • Anyone expecting AI to send customer communications or publish content without review
  • CRM implementation or marketing-automation build projects — this is applied assistant training

Assistants covered in the programme

The programme is delivered on the assistant your organisation already licenses. The techniques transfer between them.

Microsoft Copilot

Outlook, Teams, Word and PowerPoint inside Microsoft 365. Used for account briefs, meeting follow-ups, proposal drafts and pitch decks from material you already hold.

ChatGPT Enterprise

Research over uploaded files, custom GPTs for repeat proposal and content tasks, and prompt patterns for campaign briefs.

Gemini Enterprise

Google Workspace sales and marketing work: Docs for proposals, Slides for pitches, Gmail follow-ups and grounded answers over Drive content.

Claude Cowork

Long RFPs, tender packs and contracts, read into requirement matrices with every claim tied to its source.

Amazon Q Enterprise

Grounded answers over connected sales and product sources for organisations standardised on AWS.

Curriculum and hands-on modules

Module 1: Account research

Hands-on exercise. Build an account brief from approved sources, distinguish evidence from assumptions and prepare discovery questions.

What you leave with. A referenced account brief and meeting plan.

Module 2: Proposals and campaigns

Hands-on exercise. Turn a customer brief into a proposal outline, campaign concept and audience-specific messages.

What you leave with. A proposal template and campaign brief.

Module 3: Content and follow-up

Hands-on exercise. Adapt approved content across channels and draft follow-ups from meeting notes with brand and factual review.

What you leave with. A content pack and follow-up workflow.

The same sales & marketing day on each assistant

The modules stay the same; the exercise changes with the tool your team is licensed for.

Microsoft Copilot: Proposal summary from a Teams meeting

What goes in
The meeting recap from a discovery call and your approved capability deck.
What is asked
Draft an executive summary using only claims that appear in the deck, and list any customer need the deck does not address.
What comes out
A one-page Word summary plus a gap list for the account owner.
What the reviewer checks
Each claim is matched to the slide it came from, and the gap list goes to a person rather than being filled by the assistant.

ChatGPT Enterprise: An account brief that separates fact from guess

What goes in
A prospect's published annual report and your CRM notes export.
What is asked
Produce an account brief with two columns: what the sources say, and what we are inferring.
What comes out
A brief the account team can challenge line by line.
What the reviewer checks
Every item in the "sources say" column carries a page or note reference; anything without one moves to the inference column.

Claude Cowork: RFP to requirements matrix

What goes in
A 90-page tender document with appendices.
What is asked
List every mandatory and optional requirement, the clause it sits in, the submission format and the deadline.
What comes out
A requirements matrix the bid team answers against.
What the reviewer checks
The bid lead spot-checks a sample of clauses and reads the evaluation criteria in full, because a missed mandatory item disqualifies a bid.

Gemini Enterprise: Deck and follow-up email on one set of claims

What goes in
Your approved messaging document in Drive and a customer's brief.
What is asked
Draft a Slides outline and a Gmail follow-up that use only the approved claims.
What comes out
A deck outline and an email draft that say the same thing.
What the reviewer checks
Both are checked against the approved document; any new claim needs marketing sign-off.

Amazon Q Enterprise: Account research across CRM and documents

What goes in
Connected CRM and document sources.
What is asked
Summarise the account's history, open opportunities and last contact, separating evidence from assumption.
What comes out
An account brief with each fact sourced.
What the reviewer checks
The account owner confirms the brief against the CRM before the call.

Singapore rules the exercises respect

Sales and marketing output in Singapore carries obligations on both data and claims.

  • Prospect data used in research and outreach is subject to the PDPA, including the Do Not Call provisions for telephone and SMS marketing.
  • Marketing claims are checked against the Singapore Code of Advertising Practice and your own approved claims list.
  • Customer names and deal terms stay out of prompts unless your workspace terms and internal policy allow them.

How the sessions run

Delivery

On site in Singapore or remote, delivered live. Cohorts are kept small enough that every participant works on their own files rather than watching a screen share.

Duration and scheduling

Typically one full day, or two half-days scheduled around quarter-end. Module order is adjusted to your calendar and tool stack.

Session structure

Each module follows the same pattern: a short walkthrough of the technique, a hands-on exercise on your own data, then a review of what the assistant got wrong and how to catch it.

After the session

Participants leave with the prompt patterns, templates and review checklists produced during the session, so the work continues after the training day.

Prerequisites

  • A licensed seat on at least one of the covered assistants (we can run the programme on whichever your organisation has)
  • Working knowledge of your own sales process, offer and brand guidelines
  • Anonymised or sample working files — an account brief, a past proposal, approved product copy
  • No coding background required

Data handling and human review

  • Exercises run inside your own tenant and your own licences, so your data does not leave your environment for the training.
  • Files shared with the trainer in advance are anonymised extracts; customer records, pipeline data and pricing stay inside your own tenant and licences.
  • Every module includes verification: checking output against the source, confirming what the assistant left out, and marking what still needs a human read.
  • Customer-facing output is reviewed before it is sent or published. The programme teaches AI-assisted drafting and research, never unattended outreach.

Who delivers the training

Abhijit Ghosh

The programme is delivered by Abhijit Ghosh, who has spent 25 years in data and AI, including roles at Accenture, IBM, Deloitte, Cloudera, Tibco and Wipro. Sessions are run by the practitioner, not handed to a junior facilitator.

Frequently asked questions

Which AI assistant should our sales and marketing team use?

Start with the one your organisation already licenses. Microsoft Copilot suits teams working in Outlook, Word, Excel and Teams; Gemini Enterprise suits Google Workspace; ChatGPT Enterprise and Claude Cowork are stronger for long, document-heavy work; Amazon Q suits AWS-standardised estates. The programme runs on whichever you have, and the techniques transfer between them.

Do participants need a technical or coding background?

No. The programme is built for practitioners, not engineers. If you can describe how the work is done today and you know your own documents and systems, you have the prerequisites. Nothing in the sessions requires scripting.

Will we work on our own material?

Yes. Private sessions run on your own account briefs, proposals and approved content inside your own tenant. Where a file has to be shared with the trainer in advance, an anonymised extract is used, so customer names and pricing stay inside your environment.

How long is the programme and how is it scheduled?

Typically one full day, or two half-days. Sales teams usually schedule it away from quarter-end. Module order is adjusted to your tool stack and calendar.

Is the training delivered in Singapore?

Yes. Sessions are delivered on site in Singapore, or live and remote for teams spread across the region.

What do participants take away?

A referenced account brief and meeting plan, a proposal template and campaign brief, and a content pack with a follow-up workflow — all produced during the exercises using your own material.

How is this different from a vendor product demo?

A demo shows features on prepared data. This programme applies the assistant to your own work, including the cases where it produces confident, wrong output — because recognising and catching those is the skill that matters once the team uses it unsupervised.

How do you stop AI from inventing claims in proposals?

By building the workflow so it cannot quietly fill gaps. Proposals are drafted from approved material only, every claim is tied to its source, and anything the assistant inferred is marked as inferred so a person can confirm or remove it before it reaches a customer.

Can we put prospect lists into the assistant?

Only within your workspace terms and internal policy, and outreach still has to respect the PDPA's Do Not Call provisions. The session uses public sources and anonymised CRM extracts for the research exercises.

How do we keep generated claims accurate?

Every exercise works from an approved claims list. Anything the assistant produces outside that list is flagged for marketing sign-off before it reaches a customer.

Choose the assistant your team already licenses

Sales & Marketing training by assistant