Think: the Data Intelligence Engine and its data products
Think is the second of the platform's three moves. It tells a customer which technology to stop paying for, and who owns it: Asato reviews licenses, devices, contracts and AI spend, and each recommendation names the item, its price and the person or team that owns it. The Data Intelligence Engine does this with data products, each built to answer one business question. What Think produces is called a recommendation; Execute acts on an approved recommendation.
Where this sits
The platform works in three moves, and each move runs on one part of the platform.
| Move | Part of the platform | Layers | What it holds | Page |
|---|---|---|---|---|
| Link | Asset Knowledge Graph | L1 Ingestion, L2 Transformation, L3 Asset Knowledge Graph | Sources | Link: Asset Knowledge Graph |
| Think | Data Intelligence Engine | L4 Intelligence | Data products | Think: Data Intelligence Engine |
| Execute | Agentic AI | L5 Action, L6 Interfaces | Agentic solutions | Execute: Agentic AI Solutions |
This page covers Think. A data product is the unit of the Data Intelligence Engine.
What Think produces
Example, with example data. The question: "Which Microsoft licenses are not being used?" The recommendation: 212 licenses with no sign-in in 90 days, $92,000 a year, owned by end-user computing. Sources: asset list, contract, IAM and network logs. Confidence: high. The recommendation is in the Found state.
Caption on the page: Example data. A recommendation names the item, its price and its owner, and lists the records it came from.
Measured results
The page's heading for this section: A price and an owner. At CDW, each dollar of software spend has a named owner. The three figures below are CDW's: one is Found and two are Measured.
- Found: about 15% of productivity-suite spend sat with inactive or invalid accounts. CDW, in a four-week engagement.
- Measured: $100M+ a year of software spend attributed to a consuming unit, each dollar with a named owner. CDW, technology economics.
- Measured: 100% of labor and software spend carries a named owner. CDW, technology economics.
Caption on the page: CDW. The Found figure is from the four-week engagement, and no Approved or Saved figure is published for it. The two Measured figures are from CDW's technology economics model, built on Asato, and are not savings.
DART, on its Microsoft licenses ahead of a renewal: "Every recommendation was tied to a named user and actual usage data, which made decisions defensible rather than debatable." Ravi Campbell, VP Information Technology, DART.
How Think works
Ask one question and get back a priced recommendation. The page follows the example above through one data product:
- From Link: IAM, the asset list, the contract and network logs.
- The data product works out: the licenses with no sign-in in 90 days, the price per license from the contract, and the team that owns them. It uses rules, machine learning and language models. Customer data never trains any model.
- The recommendation: it names the item, its price and its owner, and lists the records it came from, with a confidence level. The figures of the example are in "What Think produces" above.
- After it: the recommendation becomes a task with an owner, tracked to its outcome.
Caption on the page: Example data. The price comes with the records it was worked out from, so a finance team can check it.
Four rules every data product follows:
- It reads the record Link has already cleaned and matched.
- It is built to answer one stated business question.
- The same access rules and lifecycle policy apply to each one.
- It is built for the person who will act on what it finds.
The questions it answers
The page's heading for this section: The questions it answers. The line under it: One for each place to start. Find yours.
The page shows five tiles, one for each of the five solutions of the site, the places a customer can start. Each tile carries the name of the solution, one sentence with the questions Think answers there, in the buyer's own words, and a link to the page of that solution. The page names no data product. The five tiles, in the page's order:
- Control AI spend: "Who uses our AI tools, what does it cost, and who owns each dollar of AI spend?" Link on the tile: "How Asato controls AI spend", to https://www.asato.ai/control-ai-spend
- Right-size software: "Which seats sit idle, and who holds a higher tier than they use?" Link on the tile: "How Asato right-sizes software", to https://www.asato.ai/right-size-software
- Stop paying for idle hardware: "Which devices are out of warranty, and what will the next refresh cost?" Link on the tile: "How Asato finds idle hardware", to https://www.asato.ai/idle-hardware
- Rationalize your portfolio: "Which software do we run, who uses it, and where do paid and unapproved applications do the same job?" Link on the tile: "How Asato rationalizes a portfolio", to https://www.asato.ai/rationalize-portfolio
- Stay ahead of contracts: "What do we spend with each vendor, and which terms in our contracts drive cost and risk?" Link on the tile: "How Asato prepares a renewal", to https://www.asato.ai/stay-ahead-of-contracts
A closing cell follows the five tiles. It reads: "More data products answer questions on installed software, telephony, engineering, cloud, security and service management, and across the estate." It carries one link, "Ask about a question you need answered", to https://www.asato.ai/contact
Which groups of data products each tile draws on: Control AI spend, AI usage and AI Spend Ledger; Right-size software, License optimization; Stop paying for idle hardware, Hardware; Rationalize your portfolio, Software; Stay ahead of contracts, Finance. The closing cell covers the other groups: Installed software, Telephony, Engineering, Across the estate, Cloud, Security, Service management.
The full catalog
The page does not show this list. The full catalog of data products is given here, in the agent version, as reference. Each data product answers one business question, and the data products are grouped. The question each group answers:
- Software: Which software do we run, who uses it, and what does it cost?
- License optimization: Which seats sit idle, and who holds a higher tier than they use?
- AI usage: Who uses our AI tools, how much, and what does it cost?
- AI Spend Ledger: Who owns each dollar of AI spend, and what limit is in force?
- Finance: What do we spend with each vendor, and which business unit consumes it?
- Hardware: Which devices are out of warranty, and what will the next refresh cost?
- Installed software: Does our installed software, Java included, match what we own?
- Telephony: Which phone licenses and extensions sit idle or underused?
- Engineering: How fast do our engineering teams deliver, and what does the effort cost?
- Across the estate: What does the whole estate cost, across SaaS, hardware, AI and cloud?
- Cloud: Which cloud resources sit idle or oversized, and who owns them?
- Security: Which security tools overlap, and which assets does none of them cover?
- Service management: Which applications and devices drive our support cost?
Where the "What it reports" column carries figures, they are example data and belong to no customer. The list is not complete: new data products ship regularly.
The software spend measured at CDW, reported under "Measured results" above, belongs to the Finance group. It is not a saving.
Software
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Software Visibility | Lists the software in use, paid and unapproved, with who uses it and what it costs. | 1,410 software assets: 278 paid, 1,132 free; $1.47M total spend on paid apps. | Renewal Prep, Shadow IT Governance, Compliance Evidence, Portfolio Consolidation, SaaS App Rationalization, Seat Reclaim, Drift Remediation, Offboarding, Entitlement Review, User & Identity Analysis, Entitlement Builder, Executive Digest, SaaS Center Assistant, Dashboard Builder, Upload Assistant, Adobe Rightsizing, Google Workspace Rightsizing, Installed Apps Center |
| App Utilization | Compares the seats in use with the seats bought for each seat-based application, and shows which licenses are underused. | 86 of 278 paid apps are seat-based (30.9%) but drive 95.5% of spend ($1.4M of $1.47M). | Portfolio Consolidation, SaaS App Rationalization, Seat Reclaim, Executive Digest, Unified Action Queue, SaaS Center Assistant, CRM Rightsizing, Adobe Rightsizing, Zoom Rightsizing, Google Workspace Rightsizing, Slack Rightsizing, Smartsheet Rightsizing, Figma Rightsizing, GitHub Rightsizing, HubSpot Rightsizing, Gong Rightsizing, Outreach Rightsizing, Asana / Monday Rightsizing, Notion Rightsizing, Box / Dropbox Rightsizing |
| App Rationalization | Shows where paid applications and unapproved ones do the same job, so the customer can decide which to keep. | 333 of 613 in-scope apps are Enterprise Shadow IT (54.3%); spans 43 of 65 categories. | Shadow IT Governance, Portfolio Consolidation, SaaS App Rationalization, Procurement Compliance, Security Consolidation, Integration Planner |
| Shadow IT | Finds unapproved software, whether enterprise, embedded or personal, with its usage and risk. | 333 Enterprise Shadow IT apps (23.6% of portfolio); 611 GB data consumed. | Shadow IT Governance, App Sanctioning |
| SaaS Center | Shows SaaS cost, usage, compliance and renewals in one view. | Executive Digest, Unified Action Queue, SaaS Center Assistant | |
| SaaS Compliance | Shows which applications have SOC 2 and HIPAA compliance information on record, and which have none. | 631 apps SOC 2 compliant; 385 HIPAA compliant; 285 apps have no compliance info. | App Sanctioning, Compliance Evidence, Vendor Attestation, Executive Digest |
| User 360 | Shows what each person is entitled to, what they use, what it costs and which department they sit in. | 163 guest identities; 31 inactive identities: access/security/cost risk. | License Optimization, Device Reclaim, Offboarding, Entitlement Review, User & Identity Analysis, Onboarding Orchestration, CRM Rightsizing, Okta Rightsizing, Integration Planner, Access Evidence |
| Microsoft Utilization | Tracks actual Microsoft 365 usage across applications and license tiers, by department and by person. | M365 bundles: 87.27% fully utilized, 1.82% partially used. | License Optimization, Telephony License Reclaim, AI Seat Reclaim, Offboarding |
| M365 Governance | Tracks policy drift, sharing exposure and configuration standards across the Microsoft 365 tenant. | Tenant-wide policy, sharing, and configuration posture in one place. | M365 Posture Remediation |
| M365 Lifecycle Governance | Tracks teams, sites and groups from creation to disposal, and flags the ones that are orphaned, stale or without an owner. | Group, team, and site lifecycle from creation to defensible disposal. | Offboarding, User & Identity Analysis, M365 Posture Remediation |
| M365 Posture | Assesses the Microsoft 365 tenant against security baselines, and ranks drift by what to fix first. | Security posture of the productivity tenant, scored against baseline. | Compliance Evidence, M365 Posture Remediation |
| Installed Software | Lists installed software with its names, versions, install dates and user counts. | 250 apps across 40 devices; avg 3.9 versions per app. | Audit Defense Pack, Perpetual License Compliance, Installed Apps Center, Installed SW Hygiene |
| Renewal Intelligence | Brings renewal information from reseller, contract and finance sources into one place. | Consolidated renewal calendar with 30/60/90-day windows and missing-metadata flags. | Renewal Prep, Renewal Assistant, Negotiation Brief |
| Atlassian Visibility | Shows which Atlassian products are in use, and by whom. | Licensed Atlassian users against active ones. | Atlassian Seat Reclaim |
| Atlassian Realization | Measures the value realized from Atlassian products, by team and by user. | Value realization of Atlassian seats by team. | Atlassian Seat Reclaim |
| Software Access & Sign-in Intelligence | Turns sign-in events into evidence of use for each application, which separates a license in use from a license that is only assigned. | Sign-in evidence per application, per user. | Access Evidence |
License optimization
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Microsoft Optimization | Recommends Microsoft 365 downgrades, deactivations and bundle changes, user by user, from actual usage. | Found: about $1K from reallocating 5 users' licenses. | License Optimization, Renewal Prep |
| Salesforce Optimization | Recommends a cheaper seat type where the work allows it and finds dormant seats by comparing entitlement with what each user does, and flags revenue risk on customer-facing roles. | Seat type fit by login recency, feature depth and object access. | CRM Rightsizing |
| Adobe Optimization | Recommends single-app or all-apps Adobe Creative Cloud licenses from each user's actual app usage. | Per-user Creative Cloud tier fit; reclaim candidates against all-apps seats. | Adobe Rightsizing |
| Zoom Optimization | Finds idle Zoom hosts, users on a higher tier than they use, and unused add-ons across the account. | Host activity, add-on usage (webinar, large meeting), tier fit. | Zoom Rightsizing |
| Atlassian Optimization | Finds Jira and Confluence licenses assigned to people who do not use them. | Per-user activity against license tier; reclaim candidates. | Atlassian Seat Reclaim |
| Google Workspace Optimization | Matches each user's collaboration and storage usage to the Google Workspace license that fits. | Per-user tier fit across Business Starter/Standard/Plus/Enterprise. | Google Workspace Rightsizing |
| Slack Optimization | Finds inactive Slack seats, guests set up as full members, and workspaces that could be combined. | Paid seats against activity; guest and full-member fit; Grid workspace audit. | Slack Rightsizing |
| Smartsheet Optimization | Shows which Smartsheet collaborators should be reclassified, and which licensed users are inactive. | Ratio of licensed users to viewers; collaborator sprawl. | Smartsheet Rightsizing |
| Figma Optimization | Finds Figma editors who could be viewers, dev-mode seats that drive cost, and design seats nobody uses. | Editor, viewer and dev-mode seat fit. | Figma Rightsizing |
| GitHub Optimization | Finds dormant GitHub Enterprise seats, and compares Copilot allocations with their use. | Enterprise seat activity; Copilot adoption against licenses. | GitHub Rightsizing |
| Okta Optimization | Compares the Okta modules the customer is entitled to with the capabilities in use. | Module entitlement (SSO, Lifecycle, Workflows) against actual usage. | Okta Rightsizing |
| HubSpot Optimization | Compares HubSpot Hub tiers with their use, and finds dormant paid seats. | Hub tier (Starter/Pro/Enterprise) and paid-seat fit. | HubSpot Rightsizing |
| Gong Optimization | Finds dormant Gong recorders, and users who only listen while holding a recorder license. | Recorder, listener and coaching seats. | Gong Rightsizing |
| Outreach Optimization | Finds sales-engagement seats held by reps who no longer run cadences. | Active cadence owners against licensed reps. | Outreach Rightsizing |
| Asana / Monday Optimization | Finds inactive paid editors in Asana or Monday, and checks each plan tier against its use. | Paid editors against viewers; tier fit. | Asana / Monday Rightsizing |
| Notion Optimization | Checks Notion membership and plan tier against how people collaborate. | Member and guest counts; plan tier fit. | Notion Rightsizing |
| Box / Dropbox Optimization | Matches Box or Dropbox storage tiers to usage, and finds idle accounts. | Storage tier against actual usage; inactive users. | Box / Dropbox Rightsizing |
| Canva Optimization | Checks Canva tiers against their use, and finds dormant paid seats. | Pro / Teams / Enterprise tier fit. | None listed |
| Miro / Mural Optimization | Finds Miro or Mural editors who could be commenters, and idle paid seats. | Editor and commenter counts. | None listed |
| Intercom Optimization | Checks Intercom agent seats and product modules against their use. | Agent seat activity; product-module fit. | None listed |
AI usage
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| AI Utilization | Shows seats, tokens, model mix, cost and adoption by team across the AI tools the customer runs. | Cross-vendor AI adoption, token consumption, and cost trend in one view. | AI Seat Reclaim, AI Spend Anomaly, Credit Governance, AI Impact Analysis, Runaway Agent Stop, AI Renewal Readiness |
| AI Credit Governance | Tracks AI billed by credit or token against each team's budget, attributes it to a workload and forecasts the run rate. | Consumption-based AI spend attributed to team, workflow, and purpose. | AI Spend Anomaly, Credit Governance |
| Cursor Utilization | Tracks Cursor usage, with daily cost and trends. | 32 active Cursor users; 512.5M tokens per month. | AI Seat Reclaim, AI Spend Anomaly |
| OpenAI Utilization | Tracks OpenAI API usage: cost, tokens, model mix and adoption by user. | 35 active users; 13 active API keys; 909.9M tokens per month. | AI Seat Reclaim, AI Spend Anomaly |
| Copilot License & Adoption | Compares assigned Copilot seats with real adoption and workload usage, and shows the seats that were never activated. | Assigned Copilot seats against measured adoption. | AI Impact Analysis |
| GitHub Copilot Insights | Analyzes GitHub Copilot activity, including acceptance rates, active seats and language mix, so seats can be matched to measured value. | Suggestion acceptance and active-seat evidence. | AI Impact Analysis |
AI Spend Ledger
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| AI Spend Coverage | Lists each source of AI spend with its feed freshness and coverage. A source that cannot be read is shown as a gap, with the connector that would cover it, and never as zero. | Each source of AI spend, how fresh it is, and what cannot be read. | AI Owner Acceptance, AI Monthly Close |
| AI Key & Agent Register | Register of the AI keys, workspaces, seats, and agents found in vendor admin feeds, each tied to an owner, a cost center, and a contract. Flags keys that several services share. | Each API key, workspace, seat and agent held as an owned asset. | AI Owner Acceptance, AI Monthly Close, AI Budget Enforcement, Runaway Agent Stop, AI Renewal Readiness |
| AI Spend Attribution | Attributes AI spend by department, owner, and contract. Each row says how its amount was obtained (read from the vendor, priced at the contract rate, or split from a seat fee) and how its owner was chosen. Spend without an owner stays on screen with a reason. | Each AI dollar tied to an owner, a cost center and a contract. | AI Monthly Close, AI Usage Request Intake, Confirmed Savings Reporting |
| AI Budget & Limit Position | Compares the budget set for each person, team, and agent with the limit in force at each vendor or gateway, showing where a limit is written, where the vendor is alert-only, and where no limit exists. | One budget policy against the limit each vendor actually enforces. | AI Budget Enforcement, AI Usage Request Intake, Runaway Agent Stop |
| AI Savings Confirmation | Tracks each saving from found to approved to saved. A saving counts as saved only when the source is read again and shows the change, such as a reclaimed seat no longer on the vendor's roster. | Savings reported as found, approved, and saved. | Confirmed Savings Reporting |
| AI Renewal Exposure | Shows idle seats and credit pools that will expire, by AI vendor and contract, ahead of each renewal date, so the renewal is sized on measured use. | Idle AI seats and expiring credits, known before the renewal. | AI Renewal Readiness |
Finance
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Vendor Financial 360 | Shows vendor spend, contracts and savings opportunities across departments in one view. | Renewal Prep, Renewal Assistant, Negotiation Brief, Portfolio Consolidation, Procurement Compliance, Top-Vendor Negotiation, Quote Benchmarking, Cost Transparency Reporting, Executive Digest, SaaS Center Assistant, Security Consolidation, Showback Reporting | |
| IT Cost Transparency | Breaks IT spend into services and the business units that consume them, and shows the basis for each allocation. | Invoice-to-service-to-business-unit allocation across the IT tower model. | Credit Governance, Cost Transparency Reporting, Dashboard Builder, KPI Trends, Cloud Rightsizing, Engineering Cost Attribution, Showback Reporting |
| Entitlement Position | Reconciles what each contract entitles the customer to with what is deployed and used, and gives a license position for each publisher. | What the customer bought against what it deployed and what the publisher will claim. | Entitlement Review, Onboarding Orchestration, Entitlement Builder, Audit Defense Pack |
| Procured-Spend Benchmarking | Compares past and live purchase prices with price benchmarks, and shows above-market spend before the purchase order is issued. | Where the price paid sits against the benchmark band, SKU by SKU. | Negotiation Brief, Top-Vendor Negotiation, Quote Benchmarking |
| Contract Intelligence | Extracts the terms that drive cost and risk from the customer's contracts, so renewal leverage and exposure can be searched. | Clause-level extraction across the contract estate: auto-renew, uplift caps, change of control. | Renewal Assistant, Negotiation Brief, Vendor Attestation, Entitlement Builder, Audit Defense Pack, Top-Vendor Negotiation, Integration Planner |
| Labor Cost Attribution | Attributes internal labor cost to services and time periods, the part of IT cost that vendor invoices do not show. | Internal labor cost attributed by time period and service. | Engineering Cost Attribution, Showback Reporting |
| TBM Showback | Produces the recurring showback view, cost by service and by consuming business unit, and shows the basis for each allocation. | Business-unit showback pack, generated on a schedule. | Showback Reporting |
| Entitlement Intelligence | Shows what is owned, where it is deployed and what the gap is worth, publisher by publisher. | Entitlement position made queryable across publishers. | Perpetual License Compliance, Access Evidence |
Hardware
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Hardware Visibility | Tracks devices with expired or expiring warranties, so a hardware refresh can be planned ahead. | Warranty Management, Device Reclaim, Hardware Center, Drift Remediation, Ticket Insights, Refresh Planner | |
| Intune Hardware Visibility | Shows hardware managed in Intune: compliance, monitoring, user assignments and security. | 63 assets total; 6 users with multiple devices; 4 shared-asset duplicates. | Warranty Management, Device Reclaim, Hardware Center |
| Asset Drift | Finds where asset systems of record disagree, across endpoint management, the CMDB, identity and HR, and ranks each conflict by its downstream impact. | Records that disagree across the systems that claim to own them. | Device Reclaim, Hardware Center, Drift Remediation, Ticket Insights, Installed Apps Center, Installed SW Hygiene |
| Compute Hardware Benchmark | Compares past device purchases with price benchmarks, by device class, and shows above-market spend. | The price paid against the benchmark for equivalent compute. | Refresh Planner |
| Compute Hardware Forecast | Forecasts refresh demand and cost by device cohort, so the hardware budget is built from the fleet. | Refresh demand and budget, modeled forward by cohort. | Refresh Planner |
| Hardware Warranty | Tracks warranty and support coverage for each device, with expiry windows and the assets that have no cover. | Coverage state and expiry windows across the fleet. | Refresh Planner |
Installed software
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Perpetual License Position | Reconciles installed perpetual software with entitlement, and gives a license position for software outside SaaS. | Installed-software license position for perpetual estates. | Perpetual License Compliance, Installed Apps Center, Installed SW Hygiene |
| Java Estate Analysis | Maps Java runtimes by version and distribution, and sizes the licensing exposure that follows a change in vendor terms. | Java runtime spread by version, vendor, and licensing exposure. | Perpetual License Compliance, Installed SW Hygiene |
Telephony
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| MS Telephony | Shows Microsoft Teams Phone activity by user and department, and which licenses are underused. | 100 users made 341 calls; 1,630 minutes; $7.6K spend. | Telephony License Reclaim, Telephony Estate Optimization |
| RingCentral Utilization | Classifies telephony extensions by real call activity, and shows idle licenses and licenses on a higher tier than needed. | Per-extension call activity against licensed extensions. | Telephony Estate Optimization |
| RingCentral Benchmark | Compares telephony extension cost and license mix with comparable deployments, ahead of a renewal. | Extension pricing and mix against comparable estates. | Telephony Estate Optimization |
| Avaya On-Prem Deployment Intelligence | Lists the on-premises voice estate, with stations, extensions and topology, so migration and decommissioning can be planned. | On-premise station inventory and deployment topology. | Telephony Estate Optimization |
Engineering
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| SEI Velocity | Measures engineering delivery velocity, including cycle time, throughput and flow, from repository and workflow activity. | Throughput and cycle time by team, sourced from the delivery estate. | Engineering Insights |
| SEI Delivery Performance | Tracks delivery performance across engineering teams. | Engineering Insights | |
| SEI Team Delivery Health | Shows delivery risk by team: work concentrated on individuals, review bottlenecks and sustained overload. | Per-team health signals: load, concentration, and review latency. | Engineering Insights |
| SEI PR Review Health | Analyzes code review practice, including time to first review, reviewer spread and depth, as an early sign of delivery risk. | Review latency, depth, and single-reviewer concentration. | Engineering Insights |
| SEI Effort & Cost Allocation | Attributes engineering effort and its labor cost to products, initiatives and business units, in the form finance uses for capitalization. | Engineering effort priced and attributed to product and initiative. | Engineering Cost Attribution |
| SEI AI Impact ROI | Measures whether AI coding tools change delivery outcomes, and prices the lift against the seat and token spend. | Measured delivery lift per AI seat, against its cost. | AI Impact Analysis |
Across the estate
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Portfolio Overview | Rolls up spend, coverage, risk and trend across SaaS, hardware, AI and cloud in one view for executives. | One estate-wide view across SaaS, hardware, AI, and cloud. | Cost Transparency Reporting, Executive Digest, Unified Action Queue, Dashboard Builder, KPI Trends, Upload Assistant, Data Freshness Monitor |
| Provisioning Velocity | Measures how fast new hires get access, and builds role bundles from what comparable users consume. | Time-to-access per role, and the gap between granted and used. | Onboarding Orchestration |
| Standards Conformance | Scores purchasing against the standards catalog, and prices the cost and risk of off-standard purchases by department. | Share of purchases that landed off-standard, and what they cost. | App Sanctioning, Procurement Compliance |
| M&A Overlap Analysis | Combines the acquired and acquiring estates into one portfolio, and sizes the savings available in each consolidation wave. | Two estates in one view: overlap, redundancy, and change-of-control exposure. | Integration Planner |
Cloud
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Cloud Cost Optimization | Finds idle and oversized cloud resources and names the team that owns each. | Idle and oversized resources by account, environment, and owning team. | Cloud Rightsizing, Commitment Planner |
| Commitment Coverage | Models reservations, savings plans and committed-use discounts against forecast consumption, to size the next commitment. | Reserved and committed-use coverage against forecast demand. | Commitment Planner |
Security
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Security Tool Coverage | Maps security tools to controls and to the assets each one covers, and shows duplicate capability and uncovered assets. | Which controls each tool claims, and how much of the estate it actually reaches. | Security Consolidation |
Service management
| Data product | What it does | What it reports | Agentic solutions built on it |
|---|---|---|---|
| Help Desk Ticket Analysis | Analyzes incident and request volume, and shows which applications and device cohorts generate support cost. | Ticket volume and effort concentrated by asset, app, and cause. | Ticket Insights |
What to notice in the App Utilization example: The seat-based applications, under a third of the paid ones, carry almost all of the spend, so a seat review starts there.
What to notice in the SaaS Compliance example: The 285 applications with no compliance record are the ones to chase first.
What to notice in the OpenAI Utilization example: 13 active API keys among 35 active users: each key needs a named owner.
Next step
The page's heading for this section: No savings, no fee. The line under it: Your Asset Clarity Report: a priced list of savings, in one week. The one action: "Get your Asset Clarity Report", at https://www.asato.ai/talk-to-sales
A customer sees the data products that fit its estate: in one week, the Asset Clarity Report shows what they find on the customer's own records for one area.
The Asset Clarity Report is a priced list of what to stop paying for in one area, with the owner of each item. It takes one week, and access for that week is read-only. If it finds no savings, the customer pays nothing.
Related pages
- Platform overview
- Link: Asset Knowledge Graph
- Think: Data Intelligence Engine
- Execute: Agentic AI Solutions
- Site index for agents
Last updated: 2026-10-09
