Milo & Atlas

Milo & Atlas turns corporate AI training from generic, one-size-fits-all courseware into a personalized, role-specific curriculum that is assessed, generated, and adapted for every individual learner.

The Problem

Generic learning platforms deliver the same content to everyone, so a marketing manager gets the same course as an operations analyst. The result is wasted time on irrelevant material, disengagement from cookie-cutter curricula, poor completion rates, and no measurable return on the training spend. For consultancies selling AI workforce transformation, that becomes a credibility problem: you cannot demonstrate the ROI of AI adoption when the training tool itself is not intelligent.

The System

Every learner gets two AI agents working in concert. Milo Guide runs a short conversational assessment grounded in the learner's job title, daily duties, pain points, and current tools, then produces a competency profile that maps the role to specific, actionable AI use cases like report automation, email triage, or data summarization. Atlas Forge takes that profile and generates a fully structured learning path, broken into modules, units, and lessons, each tailored to those use cases.

Every generated lesson carries a confidence score, so high-confidence content publishes automatically while lower-confidence lessons route to a consultant review queue before they ever reach a learner. And the loop stays closed: as learners progress, Milo periodically re-assesses mastery and Atlas adapts the curriculum, so the training sharpens over time instead of freezing on day one.

How an Engagement Flows

A consultant onboards a client organization as an isolated tenant, invites learners in bulk, monitors progress through analytics, reviews any flagged low-confidence lessons, and gives client executives a read-only stakeholder dashboard to justify the spend. A four-role model (learner, admin, stakeholder, super admin) carries an engagement from a single sign-up to a fully managed multi-client deployment.

The Technology

Milo & Atlas is a modular monolith built with domain-driven design on Next.js 16, React 19, and TypeScript, with PostgreSQL on Neon accessed through Drizzle ORM. Tenant isolation is enforced at the database level through row-level security rather than left to application code. Both AI agents are powered by the Claude API. Notably, the platform itself was built using AI Factory driving Claude Code agents in isolated git worktrees: the same AI-first philosophy the product sells is the one that produced it.

Why It Matters

For AI consultancies, it is a productized, repeatable delivery tool: multi-tenant by design, letting an operator onboard a new client organization in under a business day and show each client exactly how their team is progressing. For corporate learners, it is the difference between abandoning a generic course in week two and finishing a path whose very first lessons apply to Monday's work.

Who It Serves

AI consultancies and workforce-transformation teams deploying training across multiple client organizations, the corporate learners those engagements upskill, the executives who need to see progress and justify the spend, and the admins and consultants who run it day to day.