AI for Employee Training and Onboarding

The onboarding problem every company has

Most companies already own everything a new hire needs to learn. It's just scattered: a process doc in one drive, a recorded walkthrough in a meeting archive, a slide deck from last quarter's all-hands, a policy PDF, a Slack thread nobody can find again. Onboarding is really the work of turning that pile into something a person can actually absorb — and then checking that they did.

The usual answers are expensive and slow. You pay someone in L&D to hand-build a course. You record another training video that goes stale the day a process changes. Or you hand the new hire a folder of links and hope for the best. None of it scales, and none of it tells you whether the person understood anything.

This is exactly the gap AI is good at closing — as long as the AI is grounded in your material and not making things up. That grounding is the whole point of Scholarly. People bring their own PDFs, recordings, notes, videos, slides, and websites, and get cited answers, quizzes, study guides, podcasts, AI video lectures, AI slides, Deep Research, and AI Meeting Notes built from those exact sources. For a team, that turns your existing internal knowledge into training material without a content team rebuilding it from scratch.

Turn what you already have into training

Here's the shift: instead of authoring training, you convert it. Point Scholarly at the material a role actually needs and generate the formats that make it stick.

AI slides for structured walkthroughs. Drop in a dense process doc or a policy PDF and generate a clean training deck that pulls out the steps, the definitions, and the "why," organized to teach rather than to reference. A 40-page operations manual becomes a walkthrough a new hire can move through in an afternoon. See AI slides for how the generation works.

Podcasts for the commute and the pre-read. Not everyone learns by reading, and not every onboarding moment happens at a desk. Turn an onboarding handbook or a recorded kickoff into a podcast — a natural, two-voice audio explainer built from your material — that a new hire can listen to before day one or between meetings. It's the same content, in the format people will actually consume.

AI video lectures for the concepts that need showing. For the parts of a role that genuinely need explaining — how your billing model works, how a compliance process flows, how your product is architected — generate an AI video lecture from the source doc. It walks through the material visually and narrated, so a subject-matter expert doesn't have to re-record the same explanation for every new cohort.

Notes and study guides for reference. Scholarly can distill a long recording or a set of docs into clean, skimmable notes and a study guide — the "here's what matters" version that a new hire keeps open in another tab. Because it's grounded in the source, the notes cite where each point came from, so people can jump back to the original when they need the full detail.

Check understanding, not attendance

The part most training tools skip is verification. A completed video says nothing about whether the person learned. Scholarly's ethos is deliberately the opposite of engagement-farming: no streaks, no badges, no gamified attendance. The moat is genuinely useful tools that reinforce understanding over rote memorization — which is exactly what onboarding needs.

Quizzes and practice checks generated from your training material let a new hire test themselves as they go, and let a manager see where the gaps are. Because the questions come from your actual docs, they test grasp of your real processes — not generic trivia. Generate a quick quiz after each module, or a longer practice exam before someone takes on live responsibility.

Flashcards handle the genuinely-must-memorize slice — product SKUs, escalation paths, the fields on a form — without pretending that memorization is the whole job. They're one tool in the kit, built from your material, not the point of the product.

And when a new hire has a question the docs half-answer, they can just ask. Scholarly gives cited answers grounded in the team's shared library, so "where's the refund policy?" returns the actual passage from the actual doc — with a link back — instead of a hallucinated guess. That alone removes a huge amount of the "who do I ask?" friction that slows every new hire's first month.

Make your meetings part of onboarding

A surprising amount of institutional knowledge lives in meetings that no one writes down. AI Meeting Notes turns recorded kickoffs, training sessions, and process walkthroughs into searchable, structured notes — decisions, action items, and explanations captured and grounded in what was actually said.

For onboarding, that means the recording of "here's how our deploy process works" doesn't evaporate after the call. It becomes a searchable source a new hire can query months later, and a source you can generate a quiz or a deck from. Your live knowledge-transfer sessions stop being one-time events and start compounding.

Run the whole L&D team on one plan

Individually, all of this is powerful. The reason to run it as a team is that onboarding is never a solo activity — it involves L&D, managers, subject-matter experts, and the new hires themselves. Scholarly for Teams puts that whole group on one plan.

Every paid feature unlocks for every member automatically the moment they accept their invite. No per-person paywalls, no upgrade prompts blocking a manager mid-task, no expense reports for individual seats. Your SME builds the training deck, your new hire takes the quiz, your L&D lead audits the whole thing — all with full access.

Shared source libraries mean everyone works from the same canonical material. When the onboarding handbook updates, the decks, quizzes, and answers everyone generates come from the current version — not last quarter's copy sitting on someone's laptop.

The top tier of AI models, reserved for Enterprise — Opus 4.8, Fable 5, Sonnet 5, and GPT-5.5 — is available across every AI feature, and admins choose which model tiers the team may use. You dial in the balance of capability and cost that fits your L&D budget.

Every member gets their own 450 AI credits per week — per person, not a shared pool that a heavy user can drain. Credits reset weekly, so a big onboarding week never leaves anyone locked out. A quick chat is about one credit; a full AI video lecture is around 25, so a member can generate a real amount of training material before thinking about limits.

Admin controls keep it manageable: invite by email or link, assign Member and Admin roles, set team-wide model access, and get one central Stripe bill. You also get per-member usage broken down by feature and model, so you can see exactly how your team is using the tool.

Pricing and getting started

Scholarly Teams is $45 per seat / month, or $324 per seat / year — a 40% saving. Teams start at 3 seats and are self-serve up to 29 seats. For more seats, or if you're a school, district, or need invoicing, email hello@scholarly.so. You can compare tiers on the pricing page.

To start, sign up and choose My team or business, set your seats, and invite your people. From the moment they accept, they'll have every feature, the best AI models, and their own weekly credits — all pointed at your company's own material.

Onboarding doesn't need another course built from scratch. It needs your existing knowledge turned into something people can actually learn from, and a way to check that they did. That's what Scholarly does, grounded in the material you already own.

Ready to build your training on your own material? Start a team with Scholarly for Teams.