- Agentic AI Advisory
AI that acts, decides and delivers. We help you govern what comes next.
Agentic AI — autonomous, multi-step AI that takes actions in the world — is arriving in your organisation faster than most governance frameworks can keep up. AgntiQ helps you adopt it strategically, govern the costs, and prove the return.
AI spend arrived before AI governance did. The gap is widening.
In two years, AI went from an experiment to a board-level line item — without the frameworks, governance structures, or commercial discipline to match. The organisations that close that gap fastest will compound the advantage.
98%
AI is now everyone's FinOps problem
98% of FinOps teams now manage AI spend — up from just 31% two years ago. Token costs, inference charges, and Copilot seat sprawl are material line items that most organisations still lack frameworks to govern.
#1
AI cost management is the top FinOps capability for 2026
For the first time, AI cost management has overtaken cloud optimisation as the most in-demand FinOps skill. Demand is outpacing the supply of practitioners who can actually do it.
$1T+
AI is the fastest-growing component of that spend
With over a trillion dollars in public cloud spend projected for 2026, AI workloads are the fastest-growing segment — and the least governed. Pre-deployment cost modelling is now the top desired FinOps capability.
Agentic AI-native
we use agent workflows in our own practice
Platform-agnostic
Microsoft and AWS, no bias
Cost governance built in
adoption and FinOps, together
ROI-first
frameworks that connect spend to business value
End-to-end agentic AI advisory — from first adoption to full governance.
We combine deep Microsoft and AWS platform knowledge with FinOps discipline and responsible AI practice to help your organisation adopt agentic AI with confidence — not anxiety.
AI readiness assessment & adoption strategy
Before you buy licences or build agents, you need to understand where AI will actually deliver value in your organisation — and where it carries risk. We build the strategic foundation that makes every investment that follows smarter.
- AI use-case discovery and prioritisation workshops
- Readiness assessment across people, process, and data
- Microsoft vs. AWS platform selection and mix strategy
- Buy vs. build vs. configure decision frameworks
- Responsible AI policy and data sovereignty review
AI cost governance & spend optimisation
Token costs, inference charges, Copilot seat sprawl, GPU workloads — AI costs are complex, fast-moving, and easy to over-run without the right controls in place. We build the governance layer that keeps AI spend predictable.
- AI workload cost modelling and pre-deployment forecasting
- Token and inference cost allocation by team and use-case
- Microsoft Copilot licence analysis and seat optimisation
- AWS Bedrock and Amazon Q spend governance
- AI spend anomaly detection and budget guardrails
Responsible AI & compliance framework
Agentic AI takes actions autonomously in your systems and on behalf of your users — which makes governance non-negotiable, not optional. We help you build the policies, controls, and oversight mechanisms that keep adoption on the right side of risk.
- Responsible AI policy design and implementation
- Data sovereignty and privacy impact assessment
- Agent access control and permission frameworks
- Audit trails and human-in-the-loop design patterns
- Regulatory alignment (GDPR, AI Act, sector-specific)
AI ROI measurement & value realisation
Boards are asking whether AI investment is paying off. Most organisations can’t answer with data. We build the measurement frameworks that connect AI spend to productivity outcomes, cost savings, and business value — so you can prove the return.
- AI value realisation framework design
- Productivity and efficiency baseline measurement
- Use-case ROI modelling and tracking dashboards
- Copilot adoption and impact reporting
- Board-level AI investment narratives backed by data
Deep expertise across both ecosystems.
We combine deep Microsoft and AWS platform knowledge with FinOps discipline and responsible AI practice to help your organisation adopt agentic AI with confidence — not anxiety.
Microsoft
Copilot, Azure AI Foundry & M365
From Microsoft 365 Copilot to Azure AI Foundry and Copilot Studio, the Microsoft AI ecosystem is vast, fast-moving, and deeply integrated with the productivity and infrastructure tools most organisations already use. We help you navigate it with clarity.
Microsoft 365 Copilot
Licence optimisation, usage analysis, seat rightsizing, and adoption measurement across your M365 estate.
Azure AI Foundry
Governed model deployment, cost attribution, and usage governance for enterprise AI workloads on Azure.
Copilot Studio
Agent design governance, capacity planning, and cost modelling for custom Copilot agents and workflows.
Amazon Web Services
Bedrock, Bedrock Agents & Amazon Q
Amazon Bedrock, Bedrock Agents, and Amazon Q are powerful, but inference costs can escalate rapidly without the right guardrails. We help you build the commercial and governance frameworks that keep AWS AI spend under control.
Amazon Bedrock & Bedrock Agents
Inference cost governance, model selection strategy, and spend allocation across agentic workloads.
Amazon Q
Business and developer edition cost governance, usage tracking, and ROI measurement frameworks.
AWS AI Services
SageMaker, Rekognition, Textract and more — rationalising the AI services portfolio within your AWS MACC commitments.
Not just generating text — taking action.
Agentic AI doesn’t just respond to prompts. It plans, uses tools, executes multi-step tasks, and makes decisions — often autonomously and at scale. That’s what makes it so powerful, and why the governance stakes are fundamentally higher than with previous generations of AI.
Perceive
Agentic AI ingests context from multiple sources — documents, emails, databases, APIs, previous interactions — to understand the current state of a task or situation.
Plan
Rather than producing a single output, agentic systems decompose complex goals into a series of steps, selecting tools and sub-agents to accomplish each one.
Act
Agents execute — calling APIs, writing to systems, generating content, sending communications, or triggering downstream processes — without waiting for human approval at each step.
Learn & iterate
Modern agentic systems adapt based on feedback, memory, and outcomes — becoming more effective over time and compounding the value (and complexity) of governance.
Speed without guardrails isn't innovation, it's risk.
Agentic AI can move fast and create real value. But without proper governance, it can also move fast in the wrong direction. AgntiQ builds the controls that let you accelerate with confidence.
Data sovereignty & privacy
Where does your data go when it enters an AI model? We map data flows across Microsoft and AWS AI services, identify sovereignty risks, and design architectures that keep sensitive data where it needs to be.
Human oversight & control
Autonomous AI that can take consequential actions needs clear human-in-the-loop checkpoints. We design approval workflows, escalation paths, and override mechanisms that keep people in control where it counts.
Audit trail & explainability
When an agentic system takes an action, you need to know why, when, and with what authority. We build audit logging, decision trails, and explainability frameworks that satisfy both internal governance and external audit requirements.
EU AI Act & regulatory alignment
The EU AI Act classifies many agentic AI use-cases as high-risk. We help you understand your obligations, conduct required conformity assessments, and build the documentation and technical controls that demonstrate compliance.
Access control & permissions
AI agents need access to systems, data, and tools — but the principle of least privilege is more important here than anywhere else. We design agent permission models that scope access tightly and reduce your blast radius if something goes wrong.
Cost controls & spend guardrails
Agentic AI can consume tokens and compute at scale, automatically. Without pre-set guardrails, costs can spiral before anyone notices. We embed spend limits, anomaly alerts, and pre-deployment cost forecasting into every AI workload deployment.
Boards want ROI data, not anecdotes.
Baseline before you deploy
You can't measure a productivity gain without a starting point. We establish meaningful baselines — time-on-task, error rates, throughput, cost-per-outcome — before AI tools go live.
Connect spend to outcomes
Token costs and licence fees are easy to measure. We build the allocation frameworks that tie those costs to the business processes they're supporting — so ROI becomes a real number, not a guess.
Track and report continuously
AI value doesn't arrive all at once. We set up the dashboards, cadences, and reporting structures that surface progress monthly and give leadership teams the data they need to make reinvestment decisions confidently.
98%
of FinOps teams now manage AI spend — up from 31% two years ago
#1
AI cost management is the most in-demand FinOps skill for 2026
$1T+
in public cloud spend projected in 2026 — AI is the fastest-growing segment
60%
of all software spend will be Cloud & SaaS in 2026 — AI is embedded throughout
Ready to adopt agentic AI with confidence?
Whether you’re evaluating your first Copilot deployment, governing an existing AI estate, or trying to prove ROI to your board, a conversation with AgntiQ typically surfaces opportunities and risks within the first hour.