Corporate training on AI, automation, cloud and security
for your team
CodesSavvy runs corporate AI training for teams that use AI tools, automations, cloud and security systems at work. Engineers who build and run these systems teach live and remotely on your own stack, in short sessions around the working week. No build or other project needed: book training on its own.
From $1,500 per team
One fixed price, agreed after a free call.
Last updated
Start where you are
How much does corporate training cost?
CodesSavvy training starts from $1,500 per team. No build or other project needed: book training on its own. $1,500 is for training on a setup your team already has. Setting up tools, rules and permissions for a team is a separate service, from $3,000: see Claude Code for teams, Cursor for teams and Claude for business.
From $1,500
per team, not per seat
Included
- An agenda tailored to your tools
- Short live sessions for one team
- A sandbox lab and one trainer
- Recording, written notes and follow-up support
What changes the price
- More sessions, more people or cohorts
- Deeper tailoring to your systems
- A custom lab, repo access or a second trainer
- Ongoing coaching after training
| Format | Best for | What you get |
|---|---|---|
| Single focused session | One clear gap | Agenda, lab, recording, notes |
| Multi-session program | Adopting a tool | Baseline, rated tasks |
| Department or company-wide program | Mixed roles | Cohorts by role |
| Ongoing coaching after training | Keeping new habits | Reviews of real work |
AI training for employees and teams
CodesSavvy teaches employees and teams to use AI tools well and safely, inside the tools your company already pays for, such as Claude, ChatGPT, Gemini, Microsoft Copilot and Cursor, with practice on tasks from their own jobs.
The examples on this page are illustrative, not client results.
What the AI training covers
Hands-on.
- Clear requests
- Data rules
- Reviewing AI output and code
- A shared policy and setup
What your team can do after AI training
Rated on real work.
- Write requests that get usable drafts
- Know which data may go into each tool
- Check AI output against a source
- Review AI-written code with team rules
What should an AI use policy include?
An AI use policy should name the approved tools, list the company data that must never go into AI tools, and say who reviews AI output before it is used. It should also name who owns exceptions and how the team keeps the policy current as tools change. One page is usually enough.
A typical AI training session
A support team brings a refund reply and a ticket summary. Each person drafts the reply with Claude; the group improves the weakest request and agrees data rules. In the lab, each person checks a summary against the source tickets and fixes the errors.
Automation and AI integration training: use and manage what you have
CodesSavvy's automation training teaches the people who own an automation or AI feature to run it, check its output, report failures and change it safely, whoever built it.
What the automation training covers
On your workflows.
- How it works
- What a person approves
- Checking output and failures
- Safe changes, clear owners
What your team can do after automation training
On their own system.
- Explain each step and its data sources
- Spot and report a failed run
- Sample outputs against the source
- Make a change, test it and roll it back
A typical automation training session
An operations team owns an n8n workflow that sends form leads to the CRM and drafts a welcome email with AI. They trace one lead, find the AI step's instructions and open the last failed run. The lab: add a field, test on past entries, roll back.
Cloud and DevOps training: AWS, Azure, Kubernetes
CodesSavvy's cloud and DevOps training is about operations: keeping AWS, Azure and Kubernetes systems running, safe and affordable. Labs use a sandbox or staging, never production.
What the cloud and DevOps training covers
Each ends with a drill.
- Deploys and rollbacks
- Alerts that reach a person
- Incident drills
- Access and cost control
- Runbooks
What your team can do after cloud training
In a sandbox.
- Deploy a release and roll it back
- Tell whether an alert is real
- Start an incident from the runbook
- Review access and remove what is unused
A typical cloud training session
Only one engineer on a product team has ever restored its AWS database. In a sandbox copy, a second person deploys, sees an alert fire and rolls back with the runbook. The group restores a backup into staging, checks it, removes unused admin accounts and updates the runbook.
Security awareness training and secure practices for tech teams
CodesSavvy's security training covers awareness for every employee and secure practices for system owners.
What the security training covers
Awareness for every employee, plus a lab for system owners.
- Phishing and payment fraud
- Passwords and MFA
- Social engineering
- Company data in AI tools
- Access reviews and secrets
- Database access rules and first steps in an incident
What your team can do after security training
Staff and system owners.
- Spot and report a phishing email
- Turn on MFA and stop sharing accounts
- Keep company data out of AI tools
- Review access and move secrets out of code
A typical security training session
A finance group sees a realistic email asking to change a supplier's bank details and lists the giveaways: a lookalike domain, urgency, no call-back. Each person checks their MFA. In a separate lab, system owners fix a key pasted into chat and a shared admin login.
Already have a system, built by us or by someone else? We train your team to run it
Inherited a system? We learn it from its documentation and logs, check you hold admin access, then train its new owners. Handover training also comes with every build we do.
| What the team learns | Example: an AI step that files supplier invoices |
|---|---|
| How it works | An inbox triggers a run, AI reads the invoice, a check matches the order. |
| Where the data comes from | Inbox, purchase orders, supplier list, and the source of truth. |
| Checking output and failures | Sampling entries, and who gets the failure alert. |
| Who owns what | Named owners for workflow, prompts and credentials. |
Who this training is for
A good fit
A team, a department or the whole company that runs on cloud and AI tools.
- IT, operations, product and engineering teams
- Tooling leads, IT and engineering managers
- L&D for technical staff
Is your team ready? Six yes/no questions you can answer before the call
Each no points to a track.
Do you have an agreed AI use policy?
No: AI trackDo you know which data may go into AI tools?
No: AI trackDoes someone own each automation?
No: automation trackCan you tell when an automation has failed?
No: automation trackCan more than one person deploy or restore a backup?
No: cloud trackDo new joiners get written steps for key systems?
No: cloud track
How to choose a corporate AI training provider
Look for trainers who do the work they teach, check your team before writing an agenda, and can show a change in real work. Eight things to look for, and how we handle each:
Working practitioners teach
Us: our trainers build and run client systems.
An assessment before the agenda
Us: a baseline task comes first, then the agenda.
Labs on your own stack
Us: your tools, or a sandbox copy.
Before-and-after measurement
Us: the same real task, rated twice.
Current material
Us: agendas are written for each team, on today's tools.
Something the team keeps
Us: rules, runbooks, checklists and recordings.
Clear owners afterwards
Us: a named owner per system, in the runbook.
A clear scope and price
Us: written scope, fixed price, before work starts.
Questions to ask any provider
Questions to ask any training provider
Useful with anyone you talk to.
- Who teaches, and what have they built or run lately?
- How do you find where each person starts?
- Can labs use our own tools and data rules?
- What access do you need, and when does it end?
- What does the team keep?
- How will we know it worked?
- Is the price per seat, per session or per team?
- What changed in your material lately?
We are live, instructor-led and remote only. Choose someone else for on-site training, coding courses, exam preparation or self-paced libraries.
Working with us: from first message to follow-up
Send the team, tools and goal
Through the contact form.
Free scoping call
Where the team is stuck.
Written scope and fixed price
With a draft agenda and access needs.
Baseline
A short real task per person.
Agenda signed off
You approve modules, labs and schedule.
Short live sessions
Remote, in your time zone.
Follow-up
Support, then the same task again.
Bring a sample task or two from real work and name an owner per system. The written scope can go to procurement or into an RFP as it is.
How we measure whether the training worked
The same real task is rated at the baseline and at follow-up.
| Criterion | Not yet | Working | Confident |
|---|---|---|---|
| Correct result | Not done | Done with hints | Done, edge cases handled |
| Checks the output | Takes it on trust | When reminded | By habit |
| Data, access and secrets | Mishandled | Safe after review | Safe by default |
Sample agendas: AI and automation training
Short modules, written after the baseline. Sample agendas are illustrative.
See the sample agendas
AI for employees
Four short modules.
- 1: Where AI helps your work
- 2: Data rules, clear requests
- 3: Lab: review AI output
- 4: Agree the AI use policy
Automation handover
Four short modules.
- 1: Trigger to result
- 2: Data sources and owners
- 3: Lab: trace a failed run
- 4: Lab: a safe change and rollback
Why the engineers who build also teach
Our trainers build and run client systems.
Ways to get your team trained: agency, freelancer, training company or in-house
Companies that outsource this kind of training usually pick one of five options. Each suits a different need.
| Option | Good for | Watch for |
|---|---|---|
| The agency or engineers who run your systems How CodesSavvy works | Training on your own stack, system handover | Check they teach your people to run it without them |
| A freelance trainer or consultant | One session on one tool | Continuity and follow-up vary |
| A catalogue training company | Certifications, many seats | Generic content fits fewer workflows |
| A vendor academy (free courses from AI and cloud companies) | Basics on one product | Teaches the product, not your systems |
| Training in-house | Ongoing habits, internal champions | Needs someone with time and teaching skill |
See other providers' published prices
| Provider and offer | Published price | Source |
|---|---|---|
| AWS private virtual class (G-Cloud 14) | £6,300 per day | AWS price list |
| Konigi, AI coding workshop | $7,500 per day | konigi.com |
| SOT Labs, AI coding for dev teams | From ₹75,000 per day | sotlabs.net |
| Software Secured, secure coding | From $5,000 | softwaresecured.com |
| Improving, AI public class | $495 per student | improving.com |
Corporate training for teams: FAQ
Cost and buying
How it works and your data
AI, security and rules
Related reading
Plan your team's training
Tell us the team, the tools and the goal. You get a written scope, a fixed price and a draft agenda.
From $1,500 per team
One fixed price, agreed after a free call.