Piramilan Suthesakumaran

Full-Stack & AI Engineer

AI Consulting & Custom AI Development

Turn business problems into working AI products — strategy, prototypes, and production rollouts.

Updated April 11, 2026Canada-wide deliveryRemote-first

Who this is for

  • Founders validating an AI product idea
  • Operations teams looking to automate high-volume manual work
  • SaaS companies adding AI features to an existing product
  • Agencies bringing AI capability to client projects

What's included

Problem framing and opportunity mapping against business goals
Model selection: open-source vs. hosted, quality vs. cost trade-offs
Prompt design, evaluation loops, and guardrails
Retrieval, memory, and tool-use architecture (RAG, function calling)
Production engineering: APIs, auth, rate limits, observability, cost control
Handover and documentation so your team can own the system

How the engagement runs

  1. 01

    Discovery call

    Short, free call to understand the problem, success metrics, constraints, and existing systems. You leave with a direction regardless of whether we work together.

  2. 02

    Scoped proposal

    A fixed-scope proposal with concrete deliverables, a timeline, and a pricing structure that matches the risk profile of the work.

  3. 03

    Prototype

    Small, working prototype in days — the goal is to prove the approach, catch hidden blockers early, and validate the value with real data.

  4. 04

    Production build

    Harden the prototype into a production system: APIs, evaluation, monitoring, error handling, and security hardening.

  5. 05

    Handover

    Documentation, runbooks, and a walk-through for your team. Optional retainer for ongoing support, model updates, and feature work.

Proof, references, and recent work

View topic hub
Blog guide

AI consulting and custom AI development services

Published April 9, 2026. Covers how I scope AI products, automation systems, and production-ready workflows for growing businesses.

View cited page
Project update

XReporter operations platform

Updated April 11, 2026. Progressive web app for live staffing, reporting, and client workflows — a concrete example of automation-heavy product delivery.

View cited page
Blog guide

AI personal assistant development and OpenClaw setup

Published March 11, 2026. Explains where assistant workflows create value and how custom AI systems get deployed and supported.

View cited page

Related guides

View topic hub

FAQs

What kinds of AI projects do you take on?

Custom AI products, internal automations, AI assistants and copilots, document and knowledge workflows, AI-powered search and RAG systems, and AI features embedded in existing SaaS products. I work on both new builds and retrofits.

Do you build with open-source models or hosted APIs?

Both. The choice depends on quality, latency, cost, data residency, and operational complexity. I will recommend the option that best fits the problem, not a model family I am loyal to.

How fast can you deliver a prototype?

For well-scoped problems, working prototypes typically land within one to two weeks. Production hardening takes longer depending on the surface area, integration requirements, and evaluation depth.

Can you work alongside our internal engineering team?

Yes. I frequently embed with internal teams, pair on architecture decisions, review PRs, and hand over work with documentation so your team can own the system after launch.

Do you offer ongoing retainers after delivery?

Yes. Most AI systems need continuous evaluation, model updates, prompt tuning, and feature work. Retainers are optional and scoped to the real surface of the system.

Available across these Canadian markets

I take on ai consulting engagements across Canada. Each market page covers the local business context, industries, and how the work typically runs.

Need the full market overview first? Visit the service areas page for a Canada-wide view.

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