From Evidence to Action

Five stages. Every advisory engagement.

The same method applies regardless of the advisory pathway, because evidence-gathering, assumption-testing, and actionable output are requirements of every sound advisory engagement.

Frame

People

Stakeholder interviews to understand the business question, constraints, and what a good answer looks like for the people who will act on it.

Technology

Current state mapping of systems, platforms, and integrations relevant to the decision. Identification of data sources and evidence needed.

Outcome

Agreed scope, success criteria, evidence plan, and a clear statement of the question or decision being addressed.

What We Examine

Six assessment domains, applied to your context

Architecture and Systems

Platform choices, technical debt, integration design, scalability and modernization risk.

People and Team Capability

Skills gap analysis, team structure, ownership clarity, and capability requirements.

Data and Analytics Readiness

Data quality, availability, governance, and fitness for AI or analytics use cases.

Security and Compliance

Control gaps, regulatory exposure, access risk, and remediation prioritisation.

Cost and Investment Value

Total cost of ownership, investment sequencing, and build versus buy analysis.

Delivery and Operations

Program health, governance, process maturity and operational resilience.

What You Receive

Three deliverable groups, structured to be acted on

Every advisory engagement produces outputs your organisation can act on immediately, no further interpretation required before execution begins.

01 Evidence

Evidence-based assessment reports

Explore Evidence-based assessment reports

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Why CodeCones

Advisory grounded in delivery

Our advisory recommendations are made by people who build and operate what they advise on.

200+ delivery and advisory resources

Our advisory team draws on specialists across AI and ML engineering, data architecture, cloud and platform, security, product strategy, and delivery leadership. Breadth of expertise means your assessment is not limited by the perspective of a single discipline.

Advisory grounded in production delivery

CodeCones built and operates ResolveCX, a production AI case management system. Our advisory recommendations reflect the practical realities of building and operating AI systems at scale, not theoretical frameworks.

See ResolveCX

Quality and security by default

All advisory deliverables are reviewed for accuracy, evidential basis, and commercial utility before handover. We do not present findings that cannot be supported by documented evidence gathered during the engagement.

Our principles and approach

Read how we work, what we believe about outcomes-driven advisory, and why we structure engagements the way we do.

About CodeCones

Advisory Principles

Evidence before recommendation

No recommendation is made without documented evidence gathered during the engagement. We do not rely on assumptions or received wisdom.

Independent of vendor interest

We hold no referral arrangements and receive no incentives from technology providers. Recommendations are based on your context alone.

Commercially grounded

Technical findings are always translated into business language. The people who make the investment decision need to understand what the evidence means.

Actionable on day one

Advisory deliverables include owners, sequencing, effort estimates, and dependencies. Nothing requires further interpretation before execution begins.

Transparent about limits

We state clearly what falls outside the scope of an engagement. If a formal audit, certification, or penetration test is needed, we will say so.

Advisory leads to delivery

Our teams build and operate what they advise on. Recommendations are grounded in the practical realities of delivery, not theory.

What Organisations Achieve

What changes after an advisory engagement

Advisory engagements produce decisions that were previously blocked, investments that were properly scoped, and programmes that move with clarity rather than assumption.

Advisory in Practice

Industry case studies

Verified client outcomes are published here once an engagement is complete and written approval for publication has been confirmed.

Related Solution Blueprints

Representative blueprints from advisory-led engagements

Illustrative approaches to problems our advisory practice commonly addresses — not specific client outcomes.

Engagement Options

Three ways to structure an advisory engagement

Focused Assessment

2 to 4 weeks

A targeted engagement addressing a single question, decision, or assessment domain. Scoped to produce a clear, actionable answer with full evidence documentation.

Best for: Vendor selection, architecture validation, investment evaluation, or any specific decision with a defined scope.

Discovery and Roadmap

4 to 8 weeks

A comprehensive assessment across multiple dimensions, producing a prioritized roadmap and investment plan your organization can execute against.

Best for: AI readiness planning, program recovery or any engagement requiring a comprehensive assessment before investment decisions are made.

Continuous Advisory

Ongoing retainer

An ongoing independent perspective throughout a major program or transformation. Structured checkpoints, architecture reviews and decision support on demand.

Best for: Multi-year transformation programs, ongoing M&A activity or where independent review is required throughout delivery.

Get in Touch

Bring us the question, uncertainty, or constraint you need to resolve.

Our team will respond within one business day with a clear outline of how we can help.

  • Dedicated project manager from day one
  • Fixed-scope or continuous engagement options
  • Full IP ownership: all deliverables are yours
  • Response within one business day

No commitment required. We typically respond within one business day.

FAQs

Advisory: Frequently Asked Questions

Bring us the question, uncertainty, or constraint you need to resolve.

Every advisory engagement starts with a conversation. No commitment required.

Advisory & Strategy Insights

AI MVP Development: Scope, Stack, Timeline and Risks
ARTICLE

AI MVP Development: Scope, Stack, Timeline and Risks

Why Case-First, Not Ticket-First? | Beyond the Ticket — Episode 1
VIDEO

Why Case-First, Not Ticket-First? | Beyond the Ticket — Episode 1

AI Software Development Lifecycle: From Discovery to Production
ARTICLE

AI Software Development Lifecycle: From Discovery to Production

ResolveCX: Problem Management Software | Eliminate Recurring Failures at the Root
VIDEO

ResolveCX: Problem Management Software | Eliminate Recurring Failures at the Root