AI COST MANAGEMENT
See what AI really costs – and what it’s worth.
From GPUs to agents, LLMs to tokens, get total visibility and control of your AI costs.
Master AI economics
Stop flying blind on AI costs. Traditional FinOps tools weren’t built for GPU-heavy, multi-agent, hybrid AI environments. Mavvrik was.
Get a unified layer of cost intelligence across your AI stack — from GPUs and LLMs to tokens and agents — whether running in the cloud, on-prem, or hybrid — so you can track spend in real time, allocate, and forecast impact based on actual usage.
No guesswork. No black boxes. Just clear, connected data your finance, FinOps, and engineering teams can trust.
Uncover the true cost of every model
Break down GPU and LLM usage by model, team, or workload – across all clouds and environments. Stop relying on estimates. Start with facts.
Catch anomalies before they blow your budget
Get notified the moment spend spikes – whether it’s a stuck agent, a looping job, or a misconfigured script burning through GPUs.
Align engineering, product, and finance with cost-to-serve clarity
Expose the real costs behind every product, feature, or customer and build accountability with always-on visibility.
Recover revenue lost to underbilled GPU usage
Automatically track, allocate, and invoice shared GPU usage across internal teams or external tenants. No more leaks. No more spreadsheets.
Everything you need for cost governance in the AI era
Anomaly detection
Spot unusual activity instantly. Act before cost escalates.
Cost allocation
Attribute spend to teams, customers, models, or services with precision.
Forecasting
Model future costs based on actual usage and growth trends.
Chargeback
Automate billing across business units, products, or external clients.
Virtual tagging
Track resources even when native tags are missing or incomplete.
Perspectives
Slice cost data by any lens – feature, use case, customer, or outcome.
Mavvrik gave us a clear, consolidated view of our infrastructure spend across dozens of accounts. Instead of manually modelling costs, we get instant, data-backed recommendations that help us scale confidently without losing financial control.
Joel Miller
Director of Platform Engineering, Equinox
FAQs
Your questions, answered.
How does Mavvrik prevent surprise AI bills?
Mavvrik captures cost signals at the source, then layers accountability and governance on top. That means you get alerted before costs spiral, not after the invoice lands.
Why can’t cloud-native cost tools handle AI workloads?
Cloud provider tools were built for static VMs, not token-based LLMs, GPU clusters, or agent-driven workloads. They give you siloed slices of spend, while Mavvrik unifies AI, cloud, and on-prem costs into a single financial view.
What’s the risk of managing AI costs with spreadsheets or legacy FinOps tools?
Spreadsheets and legacy FinOps platforms weren’t built for real-time, consumption-based AI. They rely on batch updates and manual allocations, which creates blind spots that erode margins.
How does Mavvrik help engineering and finance work together?
We give both sides a common view of costs, down to the model, feature, or customer, so engineering decisions and financial guardrails are aligned from the start.
NO RISK PROOF OF VALUE
Ready to take control of your AI and hybrid costs?
Get a personalized demo and discover how Mavvrik helps:
Track every dollar across cloud, on-prem, AI, and SaaS in one platform.
Eliminate surprises with real-time cost allocation, anomaly detection, and predictive forecasting.
Automate cost control with chargebacks, budget guardrails, and AI-driven insights.
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