FogLifter® focuses on correlation, validation, and domain context so teams can move from fragmented records to defensible answers.
Each value is grounded in validated data and queryable through natural language — so every stakeholder gets answers they can defend.
Verified ITAM and CMDB records that account for ephemeral and elastic assets — VMs, containers, and cloud instances that change over time. FogLifter normalizes naming, deduplicates across sources, and tracks deltas month over month so your asset counts are defensible for compliance, audits, and operational planning.
FogLifter strengthens the data that TBM and FinOps platforms depend on — it doesn't replace them. If you run Apptio®, Cloudability®, or a homegrown model, FogLifter validates the asset counts, service mappings, and cost allocations feeding those systems so financial outputs are defensible and deployments accelerate.
SLA-to-KPI-to-SLO chaining that measures end-to-end service outcomes, not just infrastructure uptime. Instead of knowing your NAS was up 99.99% while the application was slow, FogLifter bundles infrastructure components into service-level measurements — clinician app availability, consumer banking uptime — that reflect what the business actually cares about.
Full cost attribution from invoice to service to owner. FogLifter resolves disputes about cost and caliber by giving both parties — IT and service providers, IT and business units — a shared, reconciled view. Chargeback allocations move from peanut-butter-spread estimates to evidence-based consumption, lowering vended cost and recovering previously invisible spend.
Higher patching rates, lower vulnerability exposure, and both at greatly reduced cost. FogLifter connects patching and vulnerability data to asset ownership and service context — so compliance teams know not just what's unpatched, but what service it supports, who owns it, and what the risk exposure is if it stays unpatched.
Every value above is queryable through FogLifter NLQ — grounded in the ontology and validated data, not bolted onto raw exports. Ask a question about asset counts, follow the thread into cost implications, pivot to service performance, and save the result as a dashboard. The AI doesn't need to be smarter — it needs better data. FogLifter provides it.
Most evaluators aren't comparing FogLifter to a direct competitor. They're comparing it to the tools they already have — and asking whether they still need something else.
Traditional data catalogs scan and tag metadata but don't model the relationships between assets, services, cost, and ownership. FogLifter's ontology — built over eight years on enterprise IT systems — encodes tower structures, naming taxonomies, and classification rules so queries return context, not just keyword matches.
Tools like Tableau® and Power BI® visualize whatever data you feed them — but they can't reconcile conflicting records, normalize vendor-specific naming, or flag data quality issues at ingestion. Hitachi® labels a storage line one way, Dell™ EMC labels it another. Without a semantic layer, you're making pivot tables on top of contradictions.
Apptio®, Cloudability®, and similar platforms measure cost of assets — the per-unit price of a server or gigabyte of storage. FogLifter layers on cost of service: underutilization, human effort to maintain optimal performance, KPI discrepancies, and the financial impact of delays. The unit price is the surface. The iceberg is underneath.
ServiceNow® uses a rigid SQL-based architecture where assets have fixed attributes. FogLifter's noSQL approach lets assets change attributes over time, tracking the elasticity and ephemerality that a CMDB structure can't accommodate. FogLifter integrates with ServiceNow® — placing a validation token — so you pass audits while reflecting real-world conditions.
Measured outcomes from enterprise deployments — not projections.
Published savings figure from a single customer engagement, driven by validated billing, reduced disputes, and recovered chargeback revenue.
Operational labor reduction at a major outsourced environment — reconciliation, dispute management, and manual reporting hours returned to higher-value work.
A large healthcare customer with 52,000 production servers was disputing 7–10% of them every billing cycle. The Validation View resolved disputes in the same cycle they were raised.
Multi-country, multi-currency financial reconciliation in a single FogLifter environment — with 70 tax structures normalized across regions.
Consumption, capacity, and SLA measurement across 70,000+ servers, 27 PB of storage, and 3,300 applications at a single customer site.
Invoice generation and validation cycles compressed from multi-day manual processes to hours — with full auditability at every step.
The differentiator depends on who's looking. Here's what each stakeholder takes away.
Single-pane visibility across every source of record, with validated baselines within 90 days. Stop re-litigating data quality in every meeting and start governing it — with exception lists, confidence scores, and reconciliation evidence that the rest of the organization accepts.
Showback and chargeback disputes decline because both sides see the same reconciled record. Leadership accepts the numbers without re-arguing sources. Cost of service becomes explainable — not just what you spend, but why, and whether it's justified by utilization and performance.
Verified inventory baselines, exception lists, and a credible starting point for allocations. The CMDB becomes trustworthy because FogLifter validates what's in it against every other system of record — and surfaces the differences that matter while flagging the ones that don't.
Book a demo to see how FogLifter validates, correlates, and surfaces answers across your environment.
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