MindSpace AI

MindSpace AI

AI consulting for clients and teams

Turn manual workflows, fragmented knowledge and repetitive decisions into governed AI systems that are useful, measurable and ready for real users.

Discuss an AI project

Practical AI support

MindSpace AI helps organisations adopt AI where it genuinely improves operations, decision-making, knowledge work and delivery, without losing sight of governance, security, reliability and human judgement.

Engagements cover AI strategy, use-case discovery, chat products, scheduled agents, workflow tools, metadata systems and governed human-in-the-loop deployment across client operations, education, support, research and automation programmes.

Services

From AI idea to working system

Every engagement starts with business value and ends with something teams can use, support and improve.

Use-case discovery
Find the problems worth solving, quantify the value, define success criteria and stop weak ideas early.
Workflow automation
Map repetitive work and design the right mix of agents, deterministic automation and human approval.
Chat and copilots
Create assistants and knowledge tools with the right model, retrieval, permissions and escalation paths.
Data readiness
Review documents, data quality, access, APIs and integrations before committing to a build.
Governance
Set guardrails, audit trails, evaluation criteria and human-in-the-loop controls from the start.
Deployment
Move beyond demos with monitoring, documentation, ownership, training and ongoing improvement.

Engagement options

Start small, prove value, then scale

These are indicative starting points for planning. Final scope depends on data access, integrations, risk, delivery timescale and support needs.

  • From £2,500

    AI Readiness Review

    Use cases, workflow fit, data readiness, risks, likely value and next steps.

  • From £5,000

    Workflow Automation Sprint

    One high-value workflow mapped, designed and turned into a build-ready plan.

  • From £10,000

    Proof of Concept

    A focused AI workflow tested with real inputs and clear evaluation criteria.

  • Scoped

    Deployment or Retainer

    Production delivery, governance, training, monitoring and ongoing adviser support.

Process

How we work

A clear path from first conversation to production, with decision points where a project can be refined, paused or scaled.

  1. 01

    Information gathering

    Clarify the problem, workflow, data, people, risk and what a useful outcome would look like.

  2. 02

    Investigation and options

    Compare practical options across tools, vendors, models, integrations and costs.

  3. 03

    Proof of concept

    Build a focused proof of concept around a real workflow and measurable criteria.

  4. 04

    Testing and validation

    Test output quality, failure cases, security, privacy, handovers, performance and approval points.

  5. 05

    Training and adoption

    Support users and managers with guidance on how to use, challenge and operate the system.

  6. 06

    Deployment and support

    Move to production with governance, documentation, monitoring, ownership and a support model.

Built from real project work

Guidance is grounded in hands-on delivery across AI guide content for clients, multi-model chat platforms, scheduled AI agents, email and workflow automation, metadata governance and AI strategy work for education and operations.

It also draws on more than 30 years of technology delivery, where reliability, operational simplicity, security and commercial clarity matter as much as the technology itself.

Common questions

What does an AI consultancy help with?

An AI consultancy helps organisations find useful AI opportunities, assess data and workflow readiness, choose tools and models, build proofs of concept, test outputs, manage governance and deploy systems safely.

How are the right AI use cases chosen?

Strong AI use cases are repetitive, measurable, supported by usable data, connected to existing systems, and valuable enough to justify change. They also need clear ownership, risk controls and success criteria.

How does AI move from pilot to production?

Moving from pilot to production requires evaluation, data readiness, integration, monitoring, user training, support ownership, governance, documentation and clear exit criteria for whether the pilot should scale.

How much does AI consulting cost?

Cost depends on scope, data readiness, integrations and risk. As a guide, readiness reviews start from £2,500, workflow automation sprints from £5,000 and focused proofs of concept from £10,000.