Corporate AI Workshop
Bring your teams up to speed on building and operating AI safely, with your own systems as the material.
- Typical timeline
- 3 to 6 weeks
- Typical timeline
- Listed below
- 7 deliverables
- Listed below
- No obligation
- Quoted after scoping
- No obligation
Built for
- Engineering teams starting to build with agents, retrieval or model APIs
- Leadership teams who have to make decisions about AI and answer for them
- Security and risk teams who need to understand how AI systems fail
You recognise this
- Your team is building with AI, but mostly self-taught
- Leaders are asked to approve AI projects without a way to judge them
- You want a shared understanding of AI risk across technical and non-technical staff
The problem
Generic AI training explains concepts and leaves people unsure what to do next week. Engineers need to see the failure modes in systems like theirs, and leaders need a way to judge proposals and risk in plain language. We build the sessions around your own stack and use cases, so people leave able to apply what they learned.
What you receive
- 01
Pre-workshop discovery
A call with your organiser and a short questionnaire for attendees, so the sessions match their level and your systems.
- 02
Tailored sessions
Hands-on engineering workshops on agents, retrieval, evaluation and production failure modes, leadership sessions on AI risk and decisions, or both.
- 03
Exercises on your use cases
Worked examples built from your own systems and use cases, so the practice is directly relevant.
- 04
Secure AI practices
Identity, permissions, oversight and evidence as everyday habits, for the people who build and the people who approve.
- 05
Materials to keep
Slides, exercises and reference notes for attendees.
- 06
Follow-up session
A session after the workshop to answer the questions that come up once people start applying it.
- 07
Recommendations note
A short written note, at team level, on where your team is strong and where to focus next.
Phases and expected timeline
- 01
Tailoring
1 to 3 weeks
Discovery call, attendee questionnaire, and the sessions and exercises adapted to your stack.
- 02
Delivery
1 week
One to three days of sessions, run together or spread across a week.
- 03
Follow-up
1 to 2 weeks
The follow-up session and the recommendations note.
Typical timeline: 3 to 6 weeks
Typical range for a single, well-defined scope. The clock starts once access and the people we need are in place. Your quote confirms the timeline after a scoping call. From the scoping call to the follow-up session. The sessions themselves run over one to three days.
Before we start
- An organiser who can tell us who is attending and what they need
- Attendee numbers, roles and experience levels
- Example use cases or systems to build the exercises around
- For hands-on engineering sessions, laptops with the agreed tools installed and access to any sandbox accounts
- A room and a screen, if the sessions are in person
- Any accessibility needs, so we can plan for them
What you can do afterwards
- Engineers can recognise and test for the common ways AI systems fail in production
- Leaders have a shared way to judge AI proposals and the risks they carry
- Technical and non-technical staff use the same words for the same risks
- Your team keeps materials and exercises it can reuse
What this work is designed to achieve. Results depend on your systems and your data.
Questions about this package
Hands-on sessions work best in small groups, so everyone gets help when they need it. Tell us your numbers and we will suggest a format, such as several smaller sessions.
They can, but we recommend separate sessions with a shared closing session, because each group needs different questions answered.
Because the work depends on your systems, your data and how far the scope reaches. After a scoping call we send a written quote that states the scope, the deliverables, the timeline and the cost. Larger enterprise projects are quoted separately, based on scope, integrations, deployment requirements and ongoing support.
Yes. Say so in your enquiry and we will sign one before you share details of your systems.
Yes. For example, an architecture review can lead straight into a build, and we can quote the combined work as one engagement with one plan.
Handover includes the documentation, runbook and working session your team needs to run what we delivered. If you want us to stay involved, ongoing support is quoted separately.
Get a quote for this package
Tell us about your systems and what you need. We reply with questions or times for a scoping call, then send a written quote that sets out the scope, the deliverables, the timeline and the cost.
Larger enterprise projects are quoted separately, based on scope, integrations, deployment requirements and ongoing support.
Prefer email? info@bastionshieldtechnologies.com
Often considered alongside
AI Governance Implementation
Controls around the AI your organisation uses: an inventory, clear policies, human checkpoints and an evidence trail you can show a reviewer.
AI Architecture Review
A second opinion on your AI design before you commit budget to it, with a written report and a prioritised roadmap.