Meet Agent Sherlock.
The first AI agent built on AquilaClouds Andromeda™
Agent Sherlock is the conversational AI agent within the Agentic AI Solution Layer of AquilaClouds Andromeda™. It reads cost and usage signals across every Intelligence Suite, Cloud AIQ, Platform AIQ, and Agentic AIQ, and turns them into plain-language answers, prioritized recommendations, and automated actions. No dashboards to hunt. No data exports to schedule. No guesswork.
Use Cases & Value
How Agent Sherlock accelerates
AI and cloud cost intelligence across your teams
Agent Sherlock brings FinOps, finance, and engineering teams onto a single, real-time view of cost and usage data spanning multi-cloud infrastructure, platform workloads, and agentic AI spend. It translates raw usage and cost signals into concrete insights and recommended actions, so your teams can stop reacting and start optimizing.
See what’s driving your spend
Sherlock surfaces real-time AI and cloud usage cost insights across AWS, Azure, GCP, OCI, Huawei Cloud and VMware, with unified visibility into Kubernetes, Databricks, Snowflake and GenAI/LLM workloads. Automatic anomaly detection flags unexpected cost events the moment they emerge, so nothing hides in the noise of a multi-cloud bill.
- Anomaly Detection
- Multi-cloud
Act on optimisation opportunities
Sherlock runs workload-based optimisation across Kubernetes clusters, Databricks jobs, and GenAI/LLM pipelines, continuously analysing utilisation patterns to generate automated rightsizing and waste reduction recommendations. Every suggestion is scoped to actual workload behaviour, not generic thresholds, so teams can act with confidence and typically unlock 20-30% in cloud cost savings.
- Rightsizing
- Waste Reduction
Keep budgets and teams on track
Sherlock enforces budget control and cloud governance through automated cost allocation, chargeback, and tag policy compliance, ensuring every dollar is attributed and owned. With shared visibility across finance, engineering, and operations, it closes the communication gap between who spends, who builds, and who approves, making accountability a default rather than an afterthought.
- Budget Control
- Chargeback
20–30%
~70%
Hours → Minutes
How It Works
From raw cost signals
to confident action, in plain language
Agent Sherlock sits within the Agentic AI Solution Layer of AquilaClouds Andromeda™, continuously reading cost and usage signals across every environment you run. It detects anomalies and optimization opportunities the moment they surface, then lets your FinOps, finance, and engineering teams act through plain-language conversation, without hunting through dashboards or scheduling data exports.
01
Ingest
Sherlock ingests financial and usage data across multi-cloud and hybrid cloud environments including AWS, Azure, GCP, OCI, and private cloud, as well as Kubernetes clusters, Databricks jobs, and GenAI and LLM workloads. All data is sourced directly through the AquilaClouds Andromeda™ platform.
02
Analyze
Sherlock runs continuous anomaly detection across cloud and AI spend, surfaces workload-based optimization signals for Kubernetes, Databricks, and LLM pipelines, and flags budget overrun and governance risks, including tag policy gaps and unallocated cost, before they compound.
03
Act
FinOps, finance, and engineering teams ask questions in natural language and receive prioritized recommendations: rightsizing, reservation and commitment adjustments, resource cleanup, and budget changes. Each recommendation links directly into the underlying Andromeda™ suite view for full context.
Testimonials
What teams achieve with Agent Sherlock
“Agent Sherlock completely changed how our FinOps team operates. Instead of hunting across dashboards, we ask Sherlock which clusters are driving cost this week and get an immediate answer with anomaly context and rightsizing recommendations attached.”
- FinOps Lead, Global SaaS Company
“Our finance team used to wait two weeks for cloud cost variance reports. With Agent Sherlock on AndromedaFinAI, we ask about GenAI project overruns in plain language and get forecast exposure with allocation detail, before month-end close.”
- VP Finance, Enterprise Cloud-Native Business