Question 1

We're interested in AI, but we don't really know what we need. Is that a problem?

Accepted Answer

Not at all – that's exactly where most of our clients start. You don't need a fully formed AI strategy before talking to us. We'll help you clarify where AI can actually help, what's realistic in the short term, and where to not spend time or money.

Question 2

What kinds of organizations do you usually work with?

Accepted Answer

We focus on small to mid-sized organizations: fast-growing teams, established SMEs, and business units inside larger companies. You don't need a dedicated AI team to work with us; we'll plug into your existing leadership, operations, and product/tech teams.

Question 3

Do you only work with tech companies?

Accepted Answer

No. We work across industries: B2B/B2C services, SaaS, agencies, professional services, e-commerce, internal corporate functions and more. The patterns of where AI helps are surprisingly similar across domains. We adapt the solutions to your context, processes and constraints.

Question 4

What's the best way to start if we've never done anything with AI before?

Accepted Answer

A common starting point is either an AI Strategy & Roadmap engagement (to understand where AI fits), or an AI Readiness & Training engagement (to prepare your people, data and tools). From there, we usually move into one or two high-impact implementation projects.

Question 5

Can we start small, or do we have to commit to a big transformation?

Accepted Answer

You can absolutely start small. Many clients begin with a focused sprint to prove value and build internal confidence before scaling up.

Question 6

What types of AI services do you actually offer?

Accepted Answer

Our services cover: AI Strategy & Consulting, AI Readiness, Training & Education, Responsible AI, Governance & Compliance, Intelligent Automation & System Integration, AI Solutions & Product Development, AI Agents & Autonomous Systems, AI Tooling Selection & Enablement, and Data, Analytics & AI-Powered Insights. Plus specialized services by department.

Question 7

How do your "Signature" offerings fit into this?

Accepted Answer

Signature offerings like AI Business Acceleration Sprint or Listen → Show → Implement are structured ways to get momentum quickly. They bundle strategy, discovery and hands-on implementation into a focused timeframe, so you see tangible value instead of endless workshops.

Question 8

Do you just advise, or do you also implement?

Accepted Answer

We do both. We can come in purely as strategists, purely as builders, or as a partner that stays with you from "What should we do?" all the way to "It's live and people are using it every day." Our bias is towards making things real.

Question 9

Can you work with our internal teams and existing vendors?

Accepted Answer

Yes. We often collaborate with internal product, data, IT, security and operations teams, as well as existing implementation partners. We're happy to lead, co-lead, or take on specific parts while others handle parts of the stack.

Question 10

What happens with our data? Do you train models on it?

Accepted Answer

By default, your data stays under your control. We design solutions so that your proprietary data is not used to train broad, public models, we respect your data residency, privacy and security requirements, and access is controlled and auditable.

Question 11

Is using AI safe from a compliance and legal perspective?

Accepted Answer

It can be – if it's done deliberately. A big part of our work is Responsible AI & Governance: setting clear policies, guardrails and approval flows so people know what's allowed, what's not, and how to use AI responsibly.

Question 12

We're in a regulated industry. Can you still help us?

Accepted Answer

Yes, but the work will naturally involve more governance and collaboration with your compliance and legal functions. We'll focus on use cases and architectures that respect your regulatory constraints and risk appetite.

Question 13

How do you prevent AI from "hallucinating" or giving wrong answers?

Accepted Answer

We tackle this using retrieval-based approaches (RAG) grounded in your verified content, designing clear guardrails and fallback behaviors, implementing validation and human-in-the-loop workflows where needed, and focusing on use cases where outputs can be checked or corrected.

Question 14

Will AI replace our people?

Accepted Answer

Our goal is not headcount reduction – it's better work. We focus on removing repetitive, low-value tasks, supporting people with better tools and information, and freeing time for deep work, creativity and human relationships.

Question 15

Our teams aren't "technical." Can they still use AI effectively?

Accepted Answer

Yes. Most of the value comes from good workflows and simple interfaces, not from everyone becoming a data scientist. We train teams in practical skills: how to use AI tools, how to ask for what they need, how to check outputs, and where to apply them.

Question 16

Do you provide training and workshops?

Accepted Answer

Yes. Our AI Readiness, Training & Education services include role-based training, practical sessions on using AI tools, copilots and agents, internal playbooks, prompt libraries and guidelines, and ongoing support.

Question 17

What if our people are skeptical or worried about AI?

Accepted Answer

That's normal. We address this by listening and understanding concerns, focusing on real, concrete examples, giving them control over AI outputs, and emphasising upskilling, not replacing.

Question 18

How do you think about ROI for AI projects?

Accepted Answer

We quantify value across time saved, error reduction and quality improvements, revenue impact, and risk reduction. Many of our engagements include ROI modelling so you can track value over time.

Question 19

How quickly can we expect to see impact?

Accepted Answer

For focused projects we usually aim for first tangible wins within 4–8 weeks – things like a working automation, an internal copilot, an AI-enhanced report, or a clear roadmap.

Question 20

How do you price your services?

Accepted Answer

We typically work with fixed-price packages for well-defined sprints, project-based pricing for custom implementations, and longer-term retainers for ongoing support. We'll always agree on scope, outcomes and budget before we start.

Question 21

What if we invest and it doesn't work?

Accepted Answer

We design engagements to reduce this risk: start with discovery and prioritization, use prototypes and pilots early, and build in clear checkpoints where we evaluate progress and adjust or stop if needed.

Question 22

Which AI technologies and platforms do you use?

Accepted Answer

We're vendor-neutral. We work with modern AI/LLM platforms and the surrounding ecosystem, but we choose tools based on your needs, stack, security requirements and budget.

Question 23

Can you help us choose the right AI tools?

Accepted Answer

Yes. That's exactly what AI Tooling Selection & Enablement is about. We map your current tools and constraints, shortlist sensible options, help with evaluation, setup and configuration, and train your people.

Question 24

Do you build custom AI models or only use existing ones?

Accepted Answer

We do both, depending on the problem. For many use cases, large foundation models plus good prompting, retrieval and workflow design are enough. For specific needs, we may design custom ML models.

Question 25

Will we be locked into a specific technology if we work with you?

Accepted Answer

No. We design with portability and flexibility in mind: clear interfaces, documented architectures and patterns you can reuse even if tools change.

Question 26

Do you work remotely or on-site?

Accepted Answer

Most of our work is done remotely to keep things efficient and flexible. For certain workshops, discovery sessions or key milestones, we can discuss on-site sessions.

Question 27

How much time will you need from our team?

Accepted Answer

Typically we'll need a small core group for discovery and decision-making, selected subject-matter experts for specific sessions, and access to someone on IT/data/security when integrations or governance are involved.

Question 28

What does a typical project timeline look like?

Accepted Answer

A rough pattern: Discovery & design (1–3 weeks), Build/configure/train (3–8 weeks depending on scope), Pilot & iterate (2–4 weeks), Rollout & enablement (ongoing as needed).

Question 29

We already started some AI experiments internally. Can you build on those?

Accepted Answer

Yes. We're happy to review and extend what you've already done. Sometimes we refine and productionize existing prototypes; sometimes we integrate them into a broader strategy.

Question 30

What's the first step if we want to talk?

Accepted Answer

Simple: book a conversation. We'll listen to your story and context, explore where AI might help, and suggest a few practical starting points.

Frequently Asked Questions

1. Getting Started & Fit