Most cost tools catch the obvious waste. The expensive items they miss usually require architectural judgment to spot, and that's why our reviews combine AI for speed with human analysis for context. Here's where each side pulls its weight.
Standard tools are a starting point, not the answer
Azure Advisor and Cost Management are useful. They flag underutilised VMs, suggest Reserved Instance purchases, catch unused public IPs. If you aren't using them, start there.
But they work from metrics in isolation. They can tell you a VM has low CPU. They can't tell you it's the secondary half of a disaster recovery pair that's supposed to sit idle. They can flag an "expensive resource group". They can't see that the cost is a backup vault protecting business-critical data with the right retention policy. The expensive misses are almost always the ones that need architectural context to interpret correctly.
Where AI earns its place
AI is fast at pattern recognition across thousands of line items. It cross-references resources against known optimisation patterns without fatigue. It correlates costs across services in a way that humans scanning a spreadsheet usually can't.
That's real value. A pure-human analysis is too slow to be thorough on an enterprise estate. AI compresses days of cost-categorisation work into minutes, freeing the human time for the work that actually requires judgment.
Where it doesn't
Every flagged cost needs context. Context requires understanding Azure architecture: not just what something costs, but why it costs what it does, and whether that cost is justified.
A hub-spoke network has inherent overheads. Azure Firewall in the hub isn't cheap, but it's centralising security for every spoke. Flagging it as "expensive" without understanding the architecture would be irresponsible. Disaster recovery configurations are supposed to have idle resources. That's the whole point. An automated tool will flag a secondary region's VMs as underutilised. Experience tells you they're DR failover targets.
This is the part automated tools can't replicate. AI can tell you what's expensive. Architectural judgment tells you what's unnecessarily expensive.
What we deliver
A prioritised set of recommendations, not a data dump. Every item ranked by:
- Confidence in the saving figure
- Implementation effort (a portal toggle vs. an architectural redesign)
- Risk (what changes if you act on it)
Conservative savings figures based on current pricing, not best-case projections. The high-confidence items typically pay for the work many times over. Lower-confidence architectural suggestions are flagged separately so you can decide what's worth deeper investigation.
The principle
AI alone produces lists of expensive things with no context. Human analysis alone is thorough but too slow to scale across an enterprise estate. The combination is what makes a review both fast and accurate.
When you're choosing between a tool and a partner, that's the actual trade-off.
Curious what our analysis would find in your Azure environment? Our free cost assessment is a manual review with the speed advantages of AI-assisted analysis, delivered as a prioritised set of findings.