AI Project Pricing, Engagement Models & Commercials

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AI Commercials

Start small, prove value, then scale

Every AI engagement is quoted from a defined scope, so we do not publish one-size-fits-all price lists. What we do publish is how we structure commercials, what moves the price and how we track return - so you can budget with confidence.

What We Deliver

Capabilities included in AI Commercials

How We Deliver

A proven path from idea to production

Free intro call

Understand goals, constraints and timeline.

Scoped proposal

Fixed scope, deliverables, assumptions and cost drivers.

Pilot with exit point

Prove value before committing to scale.

Scale or stop

Decide on production rollout with real data.

Optimise

Ongoing improvement and cost reviews.

Use Cases

Where it creates business value

First AI project

Start with a workshop and a fixed-price pilot.

Enterprise programme

Dedicated pod with quarterly roadmap and governance.

Run & maintain

Managed AI operations on a monthly SLA.

ROI-driven rollout

Outcome-linked milestones on well-measured processes.

Commercials & Engagement Models

Flexible ways to start and scale

Pick the model that fits your stage and risk appetite. Every quote is tailored to your scope - and every cost driver is explained upfront.

FIXED SCOPE

AI Discovery Workshop

1-2 weeks. Use-case discovery, data and architecture review, ROI model and a costed roadmap.

FIXED PRICE

Proof of Concept / Pilot

3-6 weeks. A working solution on your real data with success metrics and a clear go / no-go.

MILESTONE

Fixed-Scope Project

Scoped build with milestone payments, defined deliverables and acceptance criteria.

MONTHLY

Dedicated AI Pod

A cross-functional team - AI engineer, data engineer, solution architect, QA - on a monthly retainer.

SLA

Managed AI Operations

LLMOps monitoring, evaluation, tuning, cost control and incident response under a monthly SLA.

PASS-THROUGH

Usage-Based Costs

LLM tokens, vector databases and GPU compute billed at cost, or run in your own cloud account.

PERFORMANCE

Outcome-Linked Options

For well-measured processes, part of the fee tied to agreed KPIs such as hours saved or cases resolved.

LICENCE

Product & Platform Licences

Subscription for our reusable orchestrator, RAG and MCP accelerators to cut build time.

What drives the price

Scope & number of use cases

Data readiness & quality

Number of integrations (ERP, CRM, APIs)

Model choice & token volume

Cloud, private cloud or on-prem GPUs

Security, privacy & compliance needs

Languages & channels (WhatsApp, voice, web)

Accuracy targets & human review level

Support SLA & hours of coverage

Training & change management

Request a Tailored AI Quote

FAQ

Frequently asked questions

How much does an AI project cost?

It depends on scope, data readiness, integrations, security needs and model usage. A discovery workshop gives a firm estimate; pilots are fixed-scope so cost is known upfront.

Who pays for LLM API and cloud GPU usage?

These are passed through at cost with transparent reporting, or run in your own cloud tenant so you pay the provider directly.

Is there a minimum commitment?

No long lock-in for workshops and pilots. Dedicated pods and managed services use monthly or quarterly terms.

How do you prove ROI?

We baseline the current process, define metrics upfront and report on time saved, accuracy, cost and revenue impact.

Do you offer support after go-live?

Yes - managed AI operations include monitoring, tuning, incident response and enhancements.

Do you sign NDAs and data processing agreements?

Yes, as standard before we see any data.

AI Engagement Models & Commercials