AI transformation, implementation and agentic systems — delivered properly

CedarPro helps organisations design AI roadmaps, implement bespoke AI solutions, co-build agents, train teams and create the operating systems needed for practical AI adoption.

Service 01

AI Implementation & Transformation Consulting

Most organisations do not need more AI experiments. They need a clear starting point, a prioritised roadmap and governance they can defend. This service turns AI interest, scattered pilots or tool adoption into a structured transformation programme with measurable workflow outcomes.

Best for

  • Leaders who know AI matters but need a clear starting point
  • Organisations with scattered AI pilots that never scale
  • Teams needing governance and adoption structure
  • Public sector, education and enterprise leaders planning AI transformation

What you get

  • AI readiness assessment
  • Workflow and opportunity discovery
  • AI transformation roadmap with prioritised pilots
  • Governance and acceptable-use model
  • Implementation plan and risk management
  • Operating model recommendations
  • Value and benefits framework, with measurement
  • Vendor and tool selection support

Typical engagement: 4–12 weeks, often continuing alongside build and training work.

What you get

  • Solution discovery and feasibility
  • Workflow and data mapping
  • AI agent / system design
  • Prototype, implementation and refinement
  • Governance and human oversight model
  • User handover and adoption support

Systems we build

AI agents and multi-agent systems, AI-powered workflow automation, AI search and knowledge systems, document intelligence, decision-support tools, internal AI command centres, public sector support systems, education AI workspaces and enterprise AI operating systems.

Typical engagement: scoped per build; discovery first, then iterative delivery.

Service 02

Bespoke AI & Agentic Solution Development

For organisations with a specific operational problem: a backlog that will not shrink, documents nobody has time to read, decisions that take weeks to prepare. We design and implement AI systems around the workflow, not the other way round.

Delivery principles

  • Practical first — the system must improve a real workflow
  • Secure by design, with permissions and auditability
  • Human-in-the-loop wherever judgement matters
  • Governance included, never an optional extra
  • Training and adoption built into delivery
Service 03

Co-building AI Agents With Your Team

The fastest way to build lasting capability is to build something real together. We work alongside your team to design, build and implement AI agents that support actual workflows — and your people learn the craft as we go. You finish with a working agent and the internal confidence to improve and govern it.

Agents we typically co-build

Sales research, procurement support, policy search, planning case support, meeting prep, report drafting, training support, client status reporting, onboarding, internal knowledge and workflow triage agents.

How a co-build runs

  • Identify the workflow and select the use case
  • Define users, decision points, data and documents
  • Design agent behaviour in co-build workshops
  • Build the prototype and test it with real users
  • Refine prompts, tools, permissions and outputs
  • Train staff and create the governance and usage guide
  • Hand over with a playbook and adoption support

Typical engagement: 4–10 weeks per agent, depending on workflow complexity.

Components of a team AI operating system

  • AI command centre
  • Team workflow maps
  • Approved tools and model guidance
  • Prompt and workflow library
  • Agent and automation catalogue
  • Governance rules and decision tracking
  • Training resources and performance measures
  • Reporting dashboards
Service 04

AI Operating Systems for Teams & Organisations

This is not just software. It is a working model for how a team operates with AI: a structured environment where people, AI tools, agents, workflows, tasks, documents and governance come together. Teams stop using AI randomly and start operating through structured, AI-enabled workflows.

Best for

  • Teams moving beyond random AI use
  • Transformation teams coordinating multiple workflows
  • Organisations that need a visible AI command centre
Service 05

AI Capability Training & Workforce Development

Confidence and skill across staff, students, leaders and transformation teams — from beginner to advanced. Training underpins everything else we do: systems only deliver value when people can operate, question and govern them.

Formats

  • 1, 2 and 3-day intensives
  • 3-month capability sprint
  • 6-month transformation programme
  • 12-month capability transformation partnership

What programmes cover

  • AI literacy, foundations and responsible use
  • Role-based AI use cases and workflows
  • Prompt and workflow training, verification and quality control
  • AI work harness setup
  • AI operating systems for individuals and teams
  • Governance, acceptable use and adoption routines
  • Practical projects, demos and implementation playbooks

Audience levels: beginner, emerging, intermediate, advanced, leadership and transformation teams.

Which service?

Match the service to your situation

If you need…Start withTypical length
Direction, governance and a roadmapAI Implementation & Transformation Consulting4–12 weeks
A system built around a specific problemBespoke AI & Agentic Solution DevelopmentScoped per build
To build with your team and keep the skillsCo-building AI Agents4–10 weeks per agent
Structured AI-enabled ways of workingAI Operating Systems for Teams6–16 weeks
Confidence and skills across your peopleAI Capability Training1 day – 12 months
Common client questions

The questions every engagement starts with

Start with an AI readiness assessment and workflow discovery, not with a tool purchase. Until you know which workflows carry the most manual effort and where your people stand on capability, any AI spend is a guess. That assessment is the first deliverable of our consulting service.
The ones that are document-heavy, repetitive and slow — and where a human already reviews the output. Procurement evaluation, case preparation, reporting and knowledge search usually rank highest. We score candidate workflows on value, feasibility and risk before anything is built.
With an operating model: approved tools, acceptable-use rules, a shared prompt and workflow library, and named owners. That is what our AI Operating Systems service puts in place. Bans don’t work; structure does.
At minimum: an acceptable-use policy, clarity on what data can go where, human review points for consequential decisions, and an audit trail. Public sector clients usually need more — evidence handling and decision tracking — which we design in from the start.
Pilots stall when nobody owns adoption. We pair every build with training, adoption routines and measurement, so the pilot’s users become its operators. That transition is a planned delivery stage, not a hope.
Agree the measures before building: hours saved per case, cycle-time reduction, backlog movement, quality and consistency indicators. We set a baseline during discovery and report against it — so leaders see a number, not a vibe.

Not sure which service fits?

That is exactly what a discovery call is for. Thirty minutes, no obligation, and a straight answer about where we would start.