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AI Bootcamp · Singapore

Build an AI proof of concept with your Singapore team.

Give a regional or departmental challenge three focused days of learning, solution design and guided building.

3 full days · Guided learning + proof of concept

Discuss your projectExplore Singapore services
Colleagues collaborating in a workshop
3 full days

A practical path forward

From idea to working prototype

LearnBuildDemonstrate

Illustrative image and workflow

The Agentiv AI Bootcamp is a three-full-day learning and building program for teams in Singapore. Participants develop AI foundations, map an agreed business challenge and create a focused workflow or agent proof of concept. They receive reusable learning and design materials, prototype documentation, recorded testing observations and a backlog of recommended next steps.

Across the AI platforms your team uses

Gemini
Copilot
OpenAI
Claude
Perplexity AI
n8n
Make

Your next step

Your team has ideas. They need a structured way to test one.

Turning an AI idea into something useful requires more than an impressive prompt. Teams must understand the process, plan human review and test incomplete or incorrect answers. Your people deserve a learning experience that connects those pieces. We guide them through a focused challenge over three full days, helping them build a proof of concept they can explain and use to decide what comes next.

Colleagues collaborating in a workshop
Practical work. Shared understanding.Illustrative image

Shared foundations

Establish a common understanding of AI capabilities, limitations, prompting and responsible use. This helps the group discuss opportunities without assuming everyone has the same experience.

A clearly designed use case

Turn a business challenge into a defined process with users, inputs, outputs and review points. Decide what an initial solution should do and what can wait.

A demonstrable proof of concept

Build and test a focused workflow or agent prototype using the agreed tools. Document what works, what remains uncertain and what would be needed before operational use.

Who this helps

  • Teams that want an intensive introduction to applying and building with AI.
  • Business and operational staff with a practical challenge they can explore together.
  • Organizations considering a pilot and wanting a tangible learning output before a larger development engagement.
  • Teams able to commit three full days and participate actively in design, building and review.

What we help you do

Leave with work you can put to use.

Day 1: AI foundations and practical techniques

Explore suitable AI capabilities, prompting, output evaluation and responsible use. Work through practical exercises that prepare participants to approach the chosen challenge with clearer expectations.

Day 2: Business use-case and solution design

Map the current process, define the intended outcome and decide where AI could help. Identify required inputs, human decisions, dependencies and an achievable proof-of-concept boundary.

Day 3: Guided building and testing

Build a focused workflow or agent proof of concept with the agreed platform. Test representative scenarios, inspect results and prepare a demonstration that explains both capability and limitations.

Reusable learning and design materials

Training materials, prompting examples and templates for describing use cases, mapping processes and recording test observations. The team can reuse these when exploring later opportunities.

Prototype documentation and next-step backlog

A record of the initial solution, key assumptions, test findings and improvement priorities. Recommendations identify what needs further validation or engineering before a production decision.

Test a shared-services or regional-team idea with clear boundaries.

A useful proof of concept gives stakeholders evidence to discuss: what information it needs, how it behaves and where people must remain in control. We help your team select a focused problem and test representative scenarios. The topics below are illustrative learning applications, not completed projects or promises of operational readiness.

Prototype regional request triage

Build a workflow that suggests categories and prepares a request summary from approved samples. Test incomplete inputs and disagreement about ownership, with a person retaining the routing decision.

Create a regional update synthesis workflow

Combine sample country-team updates into a common brief format. Test inconsistent reporting periods, missing context and conflicting statements so the team can inspect limitations.

Explore an internal intake assistant

Design a prototype that helps staff identify the information needed for a shared-services request. Use approved guidance and make unanswered questions or unsupported interpretations visible.

A clear plan

Agree the outcome. Do the work. Take the next step.

Agree a challenge worth testing

Before the bootcamp, confirm the audience, selected tools and a manageable business problem. Prepare approved sample information and ensure participants can access the required environment.

Learn, design and build over three days

Move through a structured sequence of foundations, use-case design and guided implementation. Keep the prototype focused so the team has time to test and understand it.

Demonstrate and decide what comes next

Review the proof of concept against its intended outcome. Use the documented findings to decide whether to refine the design, run a controlled pilot or scope production development.

What we agree before starting

  • Three full days of facilitated learning and guided building. Dates, cohort size and delivery format are confirmed in the quotation.
  • The prototype fits the learning objectives and available tools. A full production system is outside this package.
  • Participants need devices, platform access and permission to use the agreed sample information.
  • A process owner should validate the problem, expected output and practical constraints.
  • Subscriptions, paid API usage, production integrations, deployment hardening and maintenance are quoted separately.

Delivery in Singapore

  • Select a single achievable problem and agree the cohort, tools and sample information before the three-day program.
  • For cross-market scenarios, specify which process is common and which local differences need a person to interpret rather than asking the prototype to assume.
  • Treat the output as a proof of concept. Document access needs, review points and testing gaps before considering a controlled pilot or production development.

How we evaluate progress

  • Assess whether participants can explain the problem, describe their design choices and identify where human oversight is required.
  • Test the proof of concept against a small set of representative cases and document observed strengths, failures and unresolved assumptions.
  • Agree a realistic next decision based on the findings. Potential savings or service improvements require further validation before being treated as achieved results.

Make a focused start

Give your team three days to move an idea forward.

Share the challenge you want to explore and who will take part. We will help define a focused bootcamp with a useful, achievable proof-of-concept goal.

Discuss your project

Share your business goal, intended users and current tools. We will agree the scope and delivery arrangements in a proposal.

AI Solution TrainingAI Enablement ProgramAI Application Development: Internal FacingThailand version

Questions, answered

AI Bootcamp in Singapore: frequently asked questions

Can a Singapore regional team use country-market examples?

Yes, when those examples are approved and suitable for the agreed tools. We define a common process boundary and record relevant market differences.

Does the bootcamp include a production deployment across APAC?

No. It includes a focused proof of concept and recommended next steps. A regional rollout needs a separately agreed implementation and validation scope.

What will we have built by the end of the bootcamp?

A focused workflow or agent proof of concept. Its features depend on the tools, information and scope agreed before delivery.

Do participants need to know how to code?

Coding is not a default prerequisite. We choose exercises and building methods appropriate to the agreed audience and starting level.

Is the proof of concept ready for customers or live operations?

Not automatically. Further testing, security controls, monitoring and engineering may be needed. Documentation identifies work required before deployment.

Can we use one of our own business problems?

Yes. We help narrow it to an achievable proof-of-concept scope and use approved or anonymized examples for exercises.

How is this different from AI Solution Training?

Solution Training teaches one platform in half a day. Bootcamp combines foundations, use-case design and prototype building over three full days.

How is this different from the AI Enablement Program?

Bootcamp is three concentrated days. Enablement allocates ten person-days across scoping, facilitated delivery and a later adoption review.