AI-powered learning operations platform

IgniteIQ

A serious learning platform built to help companies and institutions train people at scale without losing speed, structure, or trust.

I lead the product engineering across the public site, company-admin portal, learner experience, and super-admin surface. What mattered to me was not just delivering courses. It was building something an organization could actually run on when onboarding, compliance, awareness training, and certification all start happening at once.

Core belief
I did not want to build another LMS people log into and forget. If learning is meant to change how people work, the system behind it has to be just as serious as the work itself.

My role

I own the product layer end to end across the main surfaces: system flow, frontend architecture, backend-connected workflows, and the cleanup work that makes the platform usable after launch.

6 active companies

IgniteIQ is already live inside real company rollouts, not sitting as a concept deck or internal mock.

Tracked by department

Learner progress can be broken down by department, so teams can see where training is landing and where it is slipping.

Certificates are earned

Certificates are meant to mean something here. Completion is tied to real progress and assessment integrity, not empty clicks.

228 questions in one generated run

One generated course example came out with real assessment depth instead of a thin AI draft pretending to be enough.

Live surfaces

Product site Company admin Learner portal Super-admin

Problem

Most learning products either stop at content delivery or drift into generic academic software that does not fit how real organizations run training. IgniteIQ had to support workforce onboarding, awareness programs, assessments, certificates, analytics, and admin controls without losing clarity.

Why it wins

The value is in the combination: faster course creation, stronger oversight, certificate-backed delivery, plan-based controls, and assessment integrity that does not fall apart under real pressure. That is what turns it from another LMS into a platform an organization can actually depend on.

What I owned

I drove the product flow across company-admin, learner, and super-admin experiences, including course generation, onboarding, billing, certificates, analytics, role management, and the operational views people use every day.

Proof

Live rollout currently includes 6 active companies, with customer environments across healthcare, transportation, utilities, and IT services.

Who this is for

Enterprises running onboarding and workforce trainingAcademic institutions that need stronger digital delivery and oversightGovernment and public-sector training programsTeams rolling out AI or cybersecurity awareness at scale

Why this matters

What makes it interesting

Human-reviewed AI course generation

AI-generated courses default to draft. Nothing goes live until a human admin reviews and approves it, which keeps speed high without throwing away quality control.

Assessment integrity built into the workflow

Timed exams, randomized questions, focus-loss detection, restricted actions, microphone-based speaking detection, and malpractice logs make the platform credible for high-accountability training.

Real multi-surface operations

The product has separate company-admin, learner, and super-admin surfaces because the workflows are genuinely different. That separation is part of what makes the system feel serious.

Enterprise trust story, not just AI buzz

The product docs already define zero-retention AI usage, private retrieval, row-level isolation, test mode, sandbox support, and vendor-agnostic deployment. Those details matter when a buyer asks hard questions.

Why it holds up

Positioned as corporate learning operations software, not a generic academic LMS
AI authoring sits inside the real admin workflow instead of feeling bolted on
Certificate, onboarding, analytics, and billing flows all live inside the same system
Technical trust story includes private data handling, sandbox/test mode, and deployment flexibility

How I built it

I treated each surface like it had a real job. The learner space needed momentum. The admin space needed control. The super-admin space needed visibility across the whole system.

I kept AI inside a governed workflow. Draft first, human review after. That gave the platform speed without making it careless.

I kept the product grounded in work people actually do: onboarding teams, tracking progress, issuing certificates, controlling permissions, and seeing what is happening without guesswork.

What happened

Currently running across 6 active companies, with department-aware tracking and certificate-backed delivery built into the operating flow.
One production course-generation run produced 10 modules, 228 quiz questions, and a 133-question final exam.
The product can speak to enterprise, academic, and government buyers without changing its core operating model.

Stack

TypeScriptReactNext.jsNode.jsPostgreSQLTailwind CSSAI orchestrationPrivate retrieval / RAG

Next move

If you need someone who can own the product and still ship the code, we should talk.

Talktome

GitHub