AI training for employees, built on your team's own work
Our corporate AI training programs teach your employees AI by automating a real task from their own week, inside the tools they already use, with Ovidius engineers building alongside them. Each team leaves with a working automation it owns and the judgment to build the next one.
Jason, our COO, runs the call and the diagnostic that picks the tasks.
Finance operations: invoice approvalsBuilt in the team's own ERP and inbox, on staging data
- 01Map the taskWho touches an invoice, where it waits, which checks repeat
- 02Build the workflowThe team builds triage and routing, an engineer beside them
- 03Run it on real volumeLast week's invoices go through it before anyone signs off
- 04Hand it overOne owner on the team, and coaching while it goes live
Leaves with: a working automation the team owns
Clients include
Unguided AI use already costs your team hours
of US desk workers received AI-generated workslop in the past month
Source: BetterUp Labs and Stanford Social Media Lab, 2025Workslop is AI-generated work that looks polished but lacks the substance to move a task forward. A sales rep pastes a generated account summary into the CRM, and the manager spends the afternoon checking it against the call notes.
AI output already enters your workflows
AI use at work has doubled since 2023, according to Gallup. The diagnostic finds where generated output already reaches each team, as an AI readiness assessment does for the whole company.
The receiver pays for it
Each piece of workslop costs its receiver 1 hour 56 minutes on average. In build sessions, each team learns to check output before it moves on.
Nobody decided where AI belongs
Workslop costs an estimated $186 per employee per month in lost time. The leadership track sets where AI is used and who reviews it.
Pilots stop short of production
95% of generative AI pilots show no measurable P&L impact. Coaching stays with each workflow until it runs in production.
Sources: BetterUp Labs and Stanford Social Media Lab survey of 1,150 US desk workers, published in Harvard Business Review (September 2025), which also cites the Gallup figure; MIT NANDA, The GenAI Divide: State of AI in Business 2025.
Employee track
AI training for employees, on the tasks they repeat every week
We map your team's real operations, such as CRM updates, ERP handoffs and recurring manual tasks, and build each session around one of them. Employees build low-code automations on the tools they already use, with an Ovidius engineer beside them.
Prompts that hold up against your own records
Employees write prompts against your real documents and records, and learn where a model's answer needs checking before anyone relies on it.
Workflows in n8n, on your CRM and ERP
Each team connects AI to the systems it already works in, with an engineer handling anything that needs code.
A check before output moves on
Employees learn how models get things wrong, and add a check that stops unverified output reaching a customer or a colleague.
One automation per team
Each team leaves with an automation that runs after the session ends, and an owner on the team who keeps it running.
Leadership track
AI training for executives who decide where AI gets used
Leaders pick the processes with the highest automation return, govern what gets built, and manage the friction that comes with changing how people work.
- An impact and feasibility matrix for your own processes
- Governance that fits your regulators
- A rollout sequence for which teams go first
- Who reviews AI output, and when it needs a second check
One task map for both tracks
Leaders and employees work from the same map of your processes, so the people approving the work and the people doing it agree on what comes first.
Methods from our own engagements
The matrix follows our AI Audit, the controls come from our enterprise AI governance work, and the rollout is set out like an enterprise AI roadmap.
How a program runs
The diagnostic picks the tasks, the sessions build them, and coaching keeps them running once the trainers leave.
- 01Diagnostic
Find the tasks worth training on
Before any curriculum is written, we map your stack and the bottlenecks in each team's week with the method behind our AI Audit. Training time goes to the tasks where AI saves real hours.
- A task map per team, ranked by impact and ease
- 02Build sessions
Build live, on your own systems
Employees build working low-code automations on the tools they use every day, the way our AI consulting team builds for clients, with error alerts and a human check where one is needed.
- One working automation per team, owned by that team
- 03Coaching
Stay until the workflows run
We coach employees as they put the new workflows to work, with engineers answering questions as they come up, the same way we run AI systems in production.
- Workflows in daily use, and a team that can build the next one
A training program or licences alone
Both put AI tools in front of your employees. They differ in what your teams can do afterwards.
| Ovidius training program | Licences with no training | |
|---|---|---|
| Built around | Your workflows, your tools and your data | The vendor's feature list |
| What employees do | Build an automation on a task from their own week | Experiment alone, with no review |
| What exists afterwards | A working automation per team, in daily use | Scattered prompts and unchecked output |
| Support after | Coaching from engineers while workflows go live | The vendor's help centre |
| Leadership | A dedicated track on priorities, governance and change | Not covered |
When a trained team is ready for a bigger build
Training often surfaces a workflow too large for a session: a support assistant on your own knowledge, a finance process across three systems, or company data AI cannot yet read. The same team takes it from there, so nothing your employees learned is thrown away. GoKickflip's multi-agent content pipeline, built and shipped in 30 days, shows the pace of a build. Read the GoKickflip case
Enterprise AI chatbot
An assistant that answers from your own systems, with a second check on each reply.
See the chatbotAI invoice automation
Invoice intake, matching and approval, built into your ERP.
See invoice automationWhat teams ask before booking corporate AI training
Ask us something elseWho is corporate AI training for?
The employee track is for the people who do the repeatable work in operations, sales, finance, marketing and support. The leadership track is for executives and operations heads who decide which processes to automate and who answers for the result. Several departments can run at once, each building on its own tools.
Do our employees need to know how to code?
No. Employees build low-code automations in tools such as n8n, on top of the tools they already use. An Ovidius engineer handles anything that needs code during the session and shows the team how it works.
Which tools do you train on?
Yours. We build on the systems your team works in every day, whether that is a Salesforce instance, an Odoo ERP or a custom internal database, connected to the AI models that suit the task. The diagnostic confirms what each system allows before any session is planned.
How long does a program take, and what does it cost?
It depends on how many teams take part and how many workflows they build, so we scope each program after the diagnostic. A discovery call about your teams and tools is the quickest way to a number.
How do you handle our data during the sessions?
We sign an NDA and a data governance agreement before anyone touches a system. Session builds can run on staging or sample data, so live customer records stay out of the training room. The same terms apply as in our AI Audit.
How is this different from the AI Audit?
The AI Audit is a separate engagement that assesses your whole company and ends in a 90-day roadmap. Training uses the audit's diagnostic method at team level to pick which tasks each group builds. If you already have an audit, the program starts from its findings.
What happens after the training ends?
Each team keeps the automation it built, and coaching continues while those workflows go live. When a team surfaces something larger than a session can hold, our AI consulting team scopes it as a build. How we work sets out how that hand-off runs.
Put your first workflow on the board
Answer a few questions about your team and what you want automated, then Jason scopes it with you on the call.
