AI Deploy Network
Amaresh Kumar

AI Deploy Network / Builder

Amaresh Kumar

AI Implementation Consultant & AI-Native Product Builder

MalaysiaSeniorAvailable Now

Published evidence

1 AI Deployment

1 publicly identified

01

About Amaresh

AI-native engineer and implementation consultant building production-ready AI systems with Claude, OpenAI, RAG, agentic workflows, PostgreSQL/pgvector, Node.js, TypeScript, React and AWS. I work end to end from solution architecture and rapid prototyping to testing, rollout and adoption.

Professional profile

Location
Malaysia
Time zone
Asia/Kuala_Lumpur
Work mode
Remote
Availability
Available Now
AI experience
3+ years
Industry experience
3+ years
Languages
English
Working hours
09:00 - 05:00 PM
Typical response
Within a few hours
Preferred engagement
Medium (multi-team programmes)
Travel
Occasional travel
Available in
Malaysia

02

Proven on the network

Implementation records and publicly available work, where published.

1 AI Deployment delivered, including 1 publicly identified implementation available to inspect.

Reported business outcomes
  • Hours Automated150 hours

    period not specified

    Automated 150 hours (period not specified)

Builder-reported outcomes, recorded on deployment and case study records that AI Deploy Network reviewed before publication. AI Deploy Network does not currently capture a measurement basis or calculation methodology for reported outcomes, so none is shown.

03

What Amaresh builds

Implementation domains listed on this profile. Evidence-supported items are identified separately below.

Specialisations

AI Agents

Builder-listed deployment types

  • AI Agent
  • Conversational AI
  • Knowledge Assistant
  • RAG System

04

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

Navigation Assistant — Multilingual AI Knowledge System

Production AI knowledge assistant delivering grounded, context-aware answers across 54 structured product guides with multilingual support, routing, validation, analytics and memory.

150 hours automated

IT Services & Systems Integration · AI Agent · Conversational AI · Knowledge Assistant · RAG System

View Deployment

05

Implementation capabilities

Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.

Evidence-supported

  • AI Agent1 record
  • Conversational AI1 record
  • Knowledge Assistant1 record
  • RAG System1 record

Builder declared

  • AI Agents

06

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

    No published evidence linked yet.

    Builder declared

    • AWS
    • Claude Code
    • Docker
    • Next.js
    • Node.js
    • OpenAI Codex CLI
    • PostgreSQL
    • React
    • Supabase
    • TypeScript
    • pgvector

    07

    Industry experience

    Published Deployments support the listed counts. Other industries are Builder declared.

    IT Services & Systems Integration

    1 published Deployment

    Cross-Industry / Horizontal

    Builder declared

    EdTech

    Builder declared

    08

    Trust & verification

    A closer look at how this profile and its evidence are reviewed.

    Verified Builder

    Published evidence is reviewed against the AI Deploy Network Evidence Standard.

    How verification works
    Verified

    Verified Builder

    Independently reviewed by AI Deploy Labs against the platform Evidence Standard.

    How this is verifiedWhat the platform has established, and what remains builder-declared.
    Identity and organisation
    Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
    AI Deployments
    An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
    Business outcomes
    Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
    Evidence
    Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
    Currency
    Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
    Traceability
    Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.

    The platform does not independently audit client systems or financial records. How this is verified

    Professional record and further evidence

    Client Portfolio

    Portfolio started

    • Skipso

      AI Transformation • IT Services & Systems Integration

      Italy2026

      As an internal AI product builder, independently designed and shipped production AI solutions using Claude, OpenAI embeddings, PostgreSQL/pgvector, Node.js, TypeScript, React and AWS. Led the complete lifecycle from requirements and architecture through development, testing, rollout and adoption.

      1 AI Deployment
      Hours
      150
      View Related AI Deployments →

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