Platform reference
Five pillars. 24 capabilities. One engine underneath.
DigiUsher is built as one domain-agnostic engine: ingestion, attribution, valuation, optimization and governed action behave identically whether the row is a GPU hour, a Snowflake credit or a SaaS seat.
That is why a new cost domain costs a connector rather than a re-platform, and why metrics from different domains compose into a single auditable number.
- 4 One Ingestion Engine every cost row in your estate, in one schema, at ingestion
- 4 Auditable Attribution every cost carries an owner and the evidence behind it
- 5 The Value Engine cost expressed as a ratio leadership can actually judge
- 300+ Optimization Libraries saving scenarios, tuned to your workloads
- 6 Governed Operations changes that ship through the process your teams already trust
One Ingestion Engine
Every cost row in your estate, in one schema, at ingestion.
DigiUsher writes every record into FOCUS at the moment it arrives, across cloud, AI, data platforms, Kubernetes, on-premise and SaaS. There is no proprietary intermediate model, which is why a new cost source is a connector rather than a release, and why the dataset you query is the dataset you can export.
4 capabilities
- 01
FOCUS-native ingestion
Records land conformant on arrival: around 30% lower data-processing cost than translate-then-store designs (DigiUsher internal measure, aggregated across customer deployments), no translation lag, and a portable dataset from day one.
Aligns to FinOps Framework · Data Ingestion - 02
Invoice and execution truth, joined
What the vendor billed and what actually ran, in the same query. Invoice-only tools cannot tell you which pipeline run caused a spike; telemetry-only tools cannot tell you what it cost.
Aligns to FinOps Framework · Data Ingestion - 03
Estate coverage
Five hyperscalers, seven coding agents, four data platforms, every Kubernetes distribution, mainframe MIPS and SaaS seats, normalized into the same columns.
Aligns to FinOps Framework · Data Ingestion - 04
Anomaly detection
One engine across every domain, tuned per domain because a GPU spike and a warehouse spike behave differently. Routed to the accountable owner with context, not to a shared alerts channel.
Aligns to FinOps Framework · Anomaly Management
Auditable Attribution
Every cost carries an owner and the evidence behind it.
Attribution is where cost programs fail invisibly: a chargeback that looks complete is indistinguishable from one that is complete, until someone disputes it in a quarterly review. DigiUsher makes the reasoning inspectable, sequenced so any number walks backwards to its source, and graded so confidence is stated rather than implied.
4 capabilities
- 05
Sequenced chargeback pipeline Industry first
Invoice → environment → project → team, each stage logging its rule, inputs and outputs. Auditable by construction rather than by report.
Aligns to FinOps Framework · Allocation · Invoicing & Chargeback - 06
Attribution quality grading
Every allocated cost is labeled directly tagged, inferred from usage, or rule-distributed. A CFO who can see 78% direct and 22% distributed can defend the number; one handed a single total cannot.
Aligns to FinOps Framework · Allocation - 07
Shared-cost handling
Fixed-percentage for shared services, real-time metric-based for variable consumption. Platform teams stop absorbing costs their consumers created.
Aligns to FinOps Framework · Allocation - 08
Untraced reported, never absorbed
Allocated plus untraced always equals the invoice. Nothing is silently redistributed to make coverage look better than it is.
Aligns to FinOps Framework · Allocation
The Value Engine
Cost expressed as a ratio leadership can actually judge.
A cost number without a denominator cannot be judged. Spend fell 8%: good or bad? Nobody can say. DigiUsher divides any cost slice by any business metric, and because every domain shares one schema, those ratios compose into a single number the board can hold.
5 capabilities
- 09
Unit economics engine Flagship
Cost per workload, per merged PR, per pipeline run, per service, per active seat, per VM, per MIPS. Any slice over any metric, computed on live data.
Aligns to FinOps Framework · Unit Economics - 10
Composite metrics
AI-inclusive cost per customer in one formula: the cloud, the tokens, the credits, the pods and the seats that serve that customer. Point tools each compute a fraction.
Aligns to FinOps Framework · Unit Economics - 11
BYOD forecasting
Your launches, campaigns, growth and hiring plans as forecast inputs, with explicit confidence bands. History-only forecasting is confidently wrong exactly when it matters.
Aligns to FinOps Framework · Planning & Estimating · Forecasting - 12
Budgets and variance
Budgets per team, product or scope with variance tracked continuously rather than discovered at month end.
Aligns to FinOps Framework · Budgeting - 13
Efficiency KPIs
Coverage, utilization, waste ratio and unit-metric trend as standing targets attached to owners, with outliers surfaced across the service catalog.
Aligns to FinOps Framework · KPIs & Benchmarking
Optimization Libraries
300+ saving scenarios, tuned to your business, always your 100% true savings.
DigiUsher ships more than 300 saving scenarios, each customizable to the nature of your business, your workloads and your applications. A generic recommendation engine tells you what is true of an average estate; a customized scenario library tells you what is true of yours, which is the difference between a backlog nobody applies and savings that are genuinely, exclusively yours. Every recommendation carries severity, saving and the evidence behind it, drawn from observed utilization rather than vendor defaults.
300+ scenarios · 5 capabilities
- 14
Usage optimization
Right-sizing with confidence intervals, non-production scheduling (typically around 70% of non-prod compute), and idle and orphaned resources surfaced as their own attributable line.
Aligns to FinOps Framework · Usage Optimization - 15
Commitment and rate engine
Savings Plans, RIs, CUDs and platform commitments modeled against actual and forecast usage. Coverage and utilization are tracked separately, because high coverage on the wrong family is a loss dressed as a saving.
Aligns to FinOps Framework · Rate Optimization - 16
Workload placement
Cost per workload computed consistently across cloud, Kubernetes and data center, so placement and migration decisions are arithmetic rather than a vendor spreadsheet.
Aligns to FinOps Framework · Architecting & Workload Placement - 17
License and SaaS optimization
SaaS allocated by seat activity rather than seats purchased, with license-inclusive instance premiums and duplicate entitlements surfaced before renewal.
Aligns to FinOps Framework · Licensing & SaaS - 18
Carbon alongside cost
Where providers expose emissions data it shares lineage with cost, so one optimization reports both outcomes.
Aligns to FinOps Framework · Sustainability
Always your 100% true savings.
Not a benchmark. Not an industry average. Not a percentage a vendor model asserts about estates that resemble yours. Every scenario is tuned to your workloads, your applications and how your business actually runs, so the number you report is yours and only yours, and it survives the first person who interrogates it.
- 300+
- saving scenarios, customizable per business, workload and application
- ~100 hrs
- of manual analysis saved every week, on average
- 100%
- of reported savings verified against subsequent billing data
Governed Operations
Changes that ship through the process your teams already trust.
The recognized failure mode of cost tooling is a recommendation backlog nobody applies. DigiUsher closes the loop through your existing change process: a recommendation becomes a pull request against the repository that owns the resource, a human approves it, and Terraform applies it. The pipeline never holds write credentials, and the audit trail is the git history.
6 capabilities
- 19
Governed workflow automation
Recommendation → pull request → approval → applied. Nothing changes silently, and the evidence lives where auditors already look.
Aligns to FinOps Framework · Governance, Policy & Risk - 20
Composes your automation stack
Automation Anywhere, Zapier, UiPath, Azure DevOps, GitHub and your own AI agents. DigiUsher does not ship a fixed module you have to adopt.
Aligns to FinOps Framework · Automation, Tools & Services - 21
Policy-as-code guardrails
Tagging standards, commitment rules and the optimization backlog in version control, with drift detection instead of quarterly clean-ups.
Aligns to FinOps Framework · Governance, Policy & Risk - 22
Savings lifecycle ledger
Identified → applied → verified in the bill, where the third state means the bill confirmed it. Most tools report the first and let everyone assume the third.
DigiUsher capability · no framework equivalent - 23
Executive reporting
Board-ready output on the same lineage as the engineering views, with no separate reconciliation exercise before each meeting.
Aligns to FinOps Framework · Executive Strategy Alignment - 24
Practice maturity and enablement
Crawl-Walk-Run staged per domain, because most enterprises run in cloud and crawl in AI. Cost is surfaced where each team already works.
Aligns to FinOps Framework · FinOps Practice Operations · Assessment · Education
Compatible with the FinOps Framework, organized around our own engine.
DigiUsher is a FinOps Foundation-aligned platform, and every capability above carries the framework capability it implements. We lead with our own pillars because that is how the product is actually built. The mapping below exists so a practitioner running the framework can confirm coverage without translating our vocabulary into theirs.
| FinOps Framework domain | Framework capabilities | Delivered by |
|---|---|---|
| Understand Usage & Cost | Data Ingestion · Allocation · Reporting & Analytics · Anomaly Management | One Ingestion Engine · Auditable Attribution |
| Quantify Business Value | Unit Economics · KPIs & Benchmarking · Planning · Budgeting · Forecasting | The Value Engine |
| Optimize Usage & Cost | Usage Optimization · Rate Optimization · Architecting & Workload Placement · Licensing & SaaS · Sustainability | Optimization Libraries |
| Manage the FinOps Practice | Governance, Policy & Risk · Automation, Tools & Services · Executive Strategy Alignment · Practice Operations · Assessment · Education & Enablement · Intersecting Disciplines | Governed Operations |
Framework capability names are drawn from the FinOps Foundation Framework, used under CC BY 4.0. DigiUsher is not affiliated with or endorsed by the FinOps Foundation.
Every domain inherits all 24.
Each edition then adds its own connectors, waste-scenario library and signature value metric.
- Cloud Cost per workload
- AI Cost per merged PR
- Data Cloud Cost per pipeline run
- Kubernetes Cost per service
- On-prem, SaaS & ANY Cost per VM · per active seat · per MIPS
The five pillars are the engine; an edition is the engine pointed at one cost domain. That is why a cost domain that does not exist yet costs a connector rather than a re-platform.
Direct answers on the platform engine.
What are DigiUsher's product capabilities?
24 capabilities across five pillars: One Ingestion Engine, Auditable Attribution, The Value Engine, Optimization Libraries and Governed Operations. Each is domain-agnostic: it behaves identically whether the row is a GPU hour, a Snowflake credit or a SaaS seat.
How many saving scenarios does DigiUsher have?
More than 300, each customizable to the nature of your business, your workloads and your applications. Scenario libraries are maintained per domain, so the same engine that schedules a non-production node group also right-sizes a GPU partition and flags an unbatched inference pipeline. Customers typically save around 100 hours of manual analysis every week.
What makes DigiUsher's attribution different?
It is sequenced and graded. Allocation runs as an ordered pipeline where every stage logs its rule, inputs and outputs, so any number walks backwards to its source. Every allocated cost is then labeled directly tagged, inferred from usage, or rule-distributed, and untraced spend is reported rather than silently redistributed.
Does DigiUsher apply cost changes automatically?
No. A recommendation becomes a pull request against the repository that owns the resource, a human approves it, and Terraform applies it. The pipeline never holds write credentials. If you want autonomous production resizing, this governance model will feel like friction rather than safety.
How does DigiUsher align to the FinOps Framework?
Every capability is annotated with the FinOps Foundation Framework capability it implements, and the alignment table on this page maps all four framework domains. The alignment is a compatibility statement for practitioners already using the framework; the product is organized around DigiUsher's own five pillars.
What does verified in the bill mean?
A saving whose reduction has been confirmed in subsequent billing data, as distinct from identified (recommended) or applied (changed but not yet confirmed in the bill). The gap between the first and third states is where cost programs lose executive confidence.
44 more answers: TVR, FinOps, AI cost, Kubernetes, allocation and vendor selection →
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