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How We Work Together

Every engagement starts small and earns the right to grow. We don't ask for long commitments before we've demonstrated value and we don't hide how our engagements are structured or what they cost to get started.

THE ENGAGEMENT PHILOSOPHY

We Start With the Problem, Not the Proposal

Most consulting relationships begin with a vendor presenting a solution before they've fully understood the problem. We think that's backwards and it's one of the main reasons AI projects fail.

Our engagements are structured so that the first stage is always diagnostic. We invest time in understanding your situation, your data, your regulatory environment, your previous experience with AI, and your definition of success before we recommend an approach or scope a project.

This costs us time. It means we sometimes tell clients that what they're asking for isn't what they need, or that they're not yet ready for what they want to build. We think that honesty is what a real partnership looks like.

Stage 1: Free Consultation
Stage 1: Free Consultation

Duration: 30–60 minutes Cost: No charge

This is a genuine conversation not a pitch. We ask about your situation, your previous experience with AI, and what you're trying to achieve. You ask us whatever you need to assess whether we're the right team for your problem. We give you an honest view of whether and how AI can help including if we think it can't.

If there's a fit, we'll propose a Discovery engagement. If there isn't, we'll tell you that too and if we know of a better resource or approach for your situation, we'll share it.

What you get: An informed outside perspective on your AI situation, from a team that has seen a wide range of implementations succeed and fail. At minimum, you leave with a clearer picture of your options.

Stage 2: Discovery
Stage 2: Discovery

Duration: 1–2 weeks Investment: Fixed price, agreed upfront

The single most important stage of any AI engagement and the one most commonly skipped.

Discovery is a structured, time-boxed investigation into your problem, your data, and your environment. It is a standalone deliverable with a fixed scope and a fixed price. It does not obligate you to anything beyond itself.

What we do:

  • Review and assess the quality, coverage, and accessibility of your relevant data

  • Map your problem to the AI approaches most likely to succeed in your specific context

  • Identify regulatory, compliance, and integration requirements that will affect architecture and timeline

  • Assess organizational readiness: who needs to be involved, what workflow changes will be required or newly designd

  • Define success metrics that are meaningful for your business, not just for the model

  • Produce a clear recommendation: the right approach, a realistic timeline, a scoped proposal for Stage 3, and an honest view of risk

What you get: A Discovery Report, a concrete document that gives you everything you need to make an informed decision about whether to proceed, with whom, and on what terms. If you proceed with Vector Labs, the cost of Discovery is credited against the Stage 3 engagement.

Typical investment range: £8,000–£20,000 depending on complexity and scope

Stage 3: Proof of Concept (Prototype)
Stage 3: Proof of Concept (Prototype)

Duration: 4–8 weeks Investment: Fixed price or time-and-materials, agreed at scoping

The PoC is a working, validated demonstration of the AI solution in your specific environment on your data, against your success criteria, integrated into your infrastructure at a level sufficient to evaluate real-world performance.

This is not a demo built on synthetic data. It is not a slide deck showing what the model could do. It is a production-quality prototype that gives you and your stakeholders the evidence needed to make a confident go/no-go decision on full deployment.

What we do:

  • Develop the model architecture agreed in Discovery

  • Build and run the training pipeline on your data

  • Validate performance against agreed metrics and benchmarks

  • Produce full technical documentation

  • Present results transparently including failure modes and limitations, not just headline metrics

  • Provide a recommendation for MVP development with a scoped proposal

What you get: A validated, working model or system — plus the documentation and performance data to present internally, to regulators, or to a board. A clear go/no-go recommendation from our team, with reasons.

Typical investment range: £25,000–£80,000 depending on complexity and integration needs

Stage 4: MVP and Production Deployment
Stage 4: MVP and Production Deployment

Duration: 2–6 months Investment: Project-based or retainer, agreed at scoping

If the PoC /Prototype delivers, we expand it into a production-ready system. This phase covers performance optimization, full system integration, compliance and security hardening, operator training, and the monitoring infrastructure needed to keep the system performing reliably after deployment.

This is where the value is realized. Everything before this stage is investment in getting here safely.

What we do:

  • Optimize the model for production performance and scale

  • Build full integration with your existing systems (EMR, ERP, MES, CRM, or other)

  • Implement monitoring, alerting, and drift detection

  • Produce documentation for regulatory submission where required

  • Train your internal team to operate and maintain the system

  • Provide ongoing support during the transition to live operation

What you get: A production AI system that is integrated, monitored, documented, and supported. A team that has transferred enough knowledge that you are not permanently dependent on us to keep it running.

Typical investment range: £60,000–£400,000+ depending on complexity and scale

Stage 5: Ongoing Support and Evolution
Stage 5: Ongoing Support and Evolution

Duration: Ongoing Investment: Monthly retainer, scope agreed

AI systems are not static. Data distributions shift, business requirements evolve, new use cases emerge, and models need to be retrained and updated. We offer ongoing support relationships for clients who want a long-term AI partner rather than a series of discrete projects.

What this covers:

  • Model performance monitoring and retraining

  • New feature development and use case expansion

  • Advisory support for AI strategy as the organization evolves

  • Regulatory compliance updates as the landscape changes

Typical investment: £3,000–£15,000 per month depending on scope

WHAT THIS LOOKS LIKE IN PRACTICE

A Typical Engagement Timeline
Week 1–2

Free consultation and Discovery scoping 

Week 3–4

Discovery engagement: data assessment, problem definition, approach selection

Week 5

Discovery Report delivered. Go/no-go decision made.

Week 6–13

Proof of Concept / Prototype development

Week 14

PoC / Prototype results presented. Deployment decision made

Month 4–9

MVP and production deployment

Month 10+

Ongoing support and evolution (optional)

WHAT WE DON'T DO

Being clear about this saves time for everyone.
We don't do fixed-price, undefined-scope projects.

We've seen how these end. When scope is unclear, something always gets cut usually the validation, the documentation, or the integration. We scope clearly before we price.

We don't build prototypes we're not confident can reach production.

If the Discovery Phase reveals that the data or organizational conditions aren't right for a reliable deployment, we say so. We'd rather lose a project than deliver something that fails.

We don't disappear after deployment.

The companies that get the most from AI are the ones that treat it as an ongoing capability, not a one-time purchase. We build for the long term.

We don't pretend AI is always the answer.

Sometimes a well-designed rule-based system, a cleaner database, or a better workflow is more valuable than a machine learning model. We'll tell you when that's the case.

FAQs

Do we have to start with Discovery, or can we jump straight to development?

We strongly recommend starting with Discovery, particularly if you haven't worked with AI before, if your data situation is unclear, or if you're in a regulated industry. The cost of skipping Discovery is almost always paid later, at a much higher price. That said, for clients who have already done rigorous internal scoping, we can discuss whether a condensed or combined Discovery and PoC makes sense.

What happens if the PoC doesn't deliver the results we hoped for?

We present the results transparently, including what didn't work and why. Sometimes this means recommending a different approach. Sometimes it means advising that the conditions for a reliable AI system don't yet exist. We've had PoCs / Prototypes that led to a significant change of direction and clients who valued that honesty more than they would have valued a misleadingly positive result.

Do you work with clients outside the UK and Europe?

Yes. We have clients across North America and are experienced working with US regulatory frameworks including HIPAA and FDA guidance for AI/ML in medical devices. Our teams work across time zones and most client communication happens asynchronously with regular video checkpoints.

Can you work alongside our internal data science team?

Yes, and we often do. We can lead the engagement entirely, or contribute specific scientific and engineering depth to complement your team's capabilities. We document everything and transfer knowledge deliberately throughout the project.

Start With a Conversation

The free consultation is genuinely free and genuinely useful — whether or not we work together afterwards