Leverage AI to Govern your AI infrastructure.
Cost control, Maximize ROI.
Agentic AIQ is the AI cost intelligence suite within AquilaClouds Andromeda, purpose-built to observe, optimize, and govern spend across OpenAI, Anthropic, Gemini, Microsoft 365 Copilot, GitHub Copilot, Azure AI, Amazon Bedrock, Vertex AI, AI agents, and MCP. As AI adoption accelerates, Agentic AIQ ensures every token, every call, and every agent workflow is accounted for.
TRUSTED BY LEADING ORGANISATIONS WORLDWIDE
Problems
AI spend is your fastest-growing cost.
It is also your least governed.
Token and API Costs That Arrive Without Warning
LLM costs scale with usage in ways that traditional budgeting tools cannot anticipate. Teams spin up models, run experiments, and build pipelines without any visibility into what each call costs or which product, team, or workflow is driving the bill.
AI Productivity Tools With No ROI Accountability
Copilot licenses, GitHub Copilot seats, and other AI productivity tools represent significant recurring spend. Without usage intelligence and productivity measurement, enterprises cannot determine whether the investment is delivering value or simply adding cost.
AI Agents and Workflows Running Without Cost Controls
As agentic AI workflows multiply across the enterprise, each agent making autonomous calls to models, APIs, and tools generates costs that accumulate silently. Without workload-level attribution and spend governance, AI agent costs become impossible to manage before they become impossible to justify.
Platform Capabilities
Agentic AIQ: Observe. Optimize. Govern.
One intelligence suite. Continuous AI across your entire agentic AI and LLM estate.
Agentic AIQ is one of five modular Intelligence Suites within the AquilaClouds Andromeda platform, powered by the Agentic AI Solution Layer that brings autonomous intelligence, workflow automation, and cross-suite reasoning to every action it takes.
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Unified AI Spend Dashboard
A real-time, single-pane view of token consumption, API call volumes, and cost across OpenAI, Anthropic, Gemini, Azure AI, Bedrock, and Vertex AI, broken down by model, team, product, and workflow. Finance and engineering always share one source of truth. -
AI Agent and Workflow Cost Attribution
Every agent call, workflow execution, and model interaction is mapped to the application, team, product, or user that triggered it. Agentic AIQ eliminates the attribution gaps that make AI cost reviews slow, opaque, and contentious. -
Token-Level Anomaly Detection
ML models detect unexpected spikes in token consumption, API call rates, and AI spend the moment they emerge, whether from a runaway agent, an inefficient prompt, or an unintended loop. Alerts route to, email, JIRA, ServiceNOW or PagerDuty with full model and workflow context attached.
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Token Usage and Prompt Optimization
Agentic AIQ analyzes token consumption patterns across LLM calls and surfaces recommendations to reduce prompt length, batch requests, and select cost-efficient models for specific use cases, without degrading output quality. -
Model Selection and Routing Intelligence
Not every task needs the most capable or most expensive model. Agentic AIQ recommends optimal model routing based on task type, cost, and performance, helping teams reduce inference costs while maintaining the right quality threshold for each workflow. -
Copilot and AI Tool Usage Optimization
Analyze seat utilization, feature adoption, and active usage across Microsoft 365 Copilot, GitHub Copilot, and other AI productivity tools. Identify underutilized licenses, consolidate where appropriate, and ensure every seat is generating measurable value.
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Policy Engine for AI Spend
Set token budgets, model access controls, and spend thresholds across teams, products, and AI workflows. Automated enforcement ensures cost policies are applied consistently without manual intervention. -
Chargeback and Showback for AI Cost
Allocate AI model costs accurately to business units, product teams, and AI programs. Generate finance-ready chargeback reports across every LLM provider and AI tool without reconciling data from multiple dashboards. -
Compliance and Audit Trails
Full audit logs on every model call, agent workflow, and cost policy enforcement, giving security, finance, and AI governance teams the accountability layer they need.
~ 30%
Under 24 Hrs
Millions Saved*
99.9%
Real Results
Enterprises that stopped guessing
and started optimizing
Global Engineering & Construction Enterprise
Azure AI Foundry Cost Observability
A global engineering and construction enterprise needed deeper visibility into Azure AI Foundry spend beyond deployment-level reporting. Aquila Clouds mapped AI consumption to the organization’s business taxonomy, enabling cost and token tracking by use case, application, user, and model. This transformed AI spend into accountable, business-aligned consumption and gave teams clearer visibility into who is consuming AI, for what purpose, using which models, and at what cost.
- Azure
- Cost Observability
- Attribution
U.S.-Based Biotech Pioneer · Life Sciences
72%
Total savings delivered, with monthly cloud spend cut by ~52% in 3 months
This Nobel Prize-winning cell therapy company had no budget tracking, chargeback visibility, or tagging compliance, leaving cloud costs ungoverned and idle resources unchecked. Aquila’s FinOps engagement automated idle resource cleanup, deployed chargeback dashboards with burn-down tracking, enforced tagging compliance, and delivered unified real-time cost visibility across the organization.
- Cloud Cost Governance
- Chargeback & Tagging
- Idle Resource Optimization