Where does AI actually fit in my company?
Diagnosis before prescription.
Most AI pilots fail because nobody understood the organization first. Aria tells you exactly which workflows to automate, in what order, and what each one saves — before you spend a dollar on the wrong pilot.
What Aria does in AI Readiness.
- 01 / 04CapabilityDiagnosis first
Diagnosis first
Aria learns how your operation actually runs before prescribing a single automation. Readiness is measured, not assumed.
- 02 / 04CapabilityRanked roadmap
Ranked roadmap
Top automation candidates, each sized in dollars, each tied to an observed workflow you can interrogate.
- 03 / 04CapabilityBuild, buy or deploy
Build, buy or deploy
Each candidate gets a recommendation — build internally, buy a tool, or deploy an Aria agent — with the reasoning disclosed.
- 04 / 04CapabilityNo pilot purgatory
No pilot purgatory
Every deployment ships with success criteria. If it doesn't move the metric, Aria kills it — before it becomes permanent.
How Aria runs AI Readiness, end to end.
- Operating assessment
Diagnose the operation first.
Readiness is not a questionnaire. Aria maps the actual operation — data maturity, workflow observability, change capacity, integration posture — before scoring anything.
Artifact · Operating diagnosticOperating diagnosticObserving- Vendor-invoice triage$1.1M
- Customer-service FAQ routing$740K
- Quality inspection anomaly$1.4M
- Readiness scorecard
Score readiness across the organization.
A scorecard across the dimensions that actually predict pilot success. Where you're ready, where you're not, and what would have to change to move.
Artifact · AI readiness scorecardAI readiness scorecardMapping- Customer-service FAQ routing$740K
- Quality inspection anomaly$1.4M
- Forecast assembly$680K
- Automation roadmap
Rank the candidates in dollars.
Top automation candidates, each sized in dollars, each tied to an observed workflow. The roadmap is specific enough to commit to — and to walk back.
Artifact · Ranked automation roadmapRanked automation roadmapRanking- Quality inspection anomaly$1.4M
- Forecast assembly$680K
- HR onboarding automation$420K
- Build / Buy / Deploy
Decide per workflow, not per vendor.
Each candidate gets a recommendation — build internally, buy a tool, or deploy an Aria agent — with the trade-offs disclosed and the assumption log visible.
Artifact · Build-vs-buy-vs-deploy matrixBuild-vs-buy-vs-deploy matrixDeploying- Quality inspection anomaly$1.4M
- Forecast assembly$680K
- HR onboarding automation$420K
- Wave deployment
Ship in waves. Kill what doesn't move.
Every deployment has success criteria and a kill rule declared up front. Pilots that don't move the metric get killed on schedule — before they become permanent infrastructure.
Artifact · Wave deployment planWave deployment planProving- Quality inspection anomaly$1.4M
- Forecast assembly$680K
- HR onboarding automation$420K
“Ninety-five percent of AI pilots fail because nobody diagnosed the company first. Aria closes the first ninety-five percent.”Aria methodology · AI Readiness
What Aria ships.
Every engagement surfaces as a live Synapse workspace. The readout below is how AI Readiness looks the week it ships — scenario data from the published live demo.
- Vendor-invoice triageOn trackReady · deploy an Aria agent$1.1M
- Customer-service FAQ routingOn trackReady · deploy an Aria agent$740K
- Quality inspection anomalyWatchPartial · build — data label gap$1.4M
- Forecast assemblyWatchPartial · buy — off-the-shelf fit$680K
- HR onboarding automationCriticalNot ready · pre-req workflow cleanup$420K
Setting a new standard for operating intelligence.
“The findings were gold.”VP · Electric Grid Operations
- Client
- Fortune 500 energy utility
- 20,000+ employees · U.S. regulated utility
- Scope
- Electric Grid Operations
- Three-week diagnostic
- What Aria found
- Fifteen automations identified. Eighty percent of operational time mapped to repetitive work — all sized, ranked and handed off to the operating team.
What you leave with.
Artifacts that outlive the engagement — every deliverable grounded in the operating model Aria builds during the assessment, maintained live after close.
- AI readiness scorecard across the operation
- Ranked automation roadmap with per-candidate sizing
- Build/buy/deploy recommendation per workflow
- Wave-based deployment plan
Explore the surfaces behind every engagement.
Every Aria engagement rides on the same four product surfaces — whichever solution you scope, you get the same assessment cadence, agent deployment, interview system, and research model.
- Operating readoutOperating readout
Assessment & Diagnosis
The six-week operational intelligence assessment behind every engagement.
Explore - Autonomous agentsKYC triage agentLiveThroughput+38%Cycle time−44%Exceptions2Running
Agent Deployment
Custom AI agents that ship against measured waste — success criteria up front.
Explore - Conversation intelligenceARA
Stakeholder Interviews
Aria runs targeted operator interviews to close the gaps the systems can't fill.
Explore - ResearchMcKinsey 7SSCORPorter 5FBLSFREDIBISWorldAPQC PCF
Aria V1 Research Model
Twelve industries, forty-plus frameworks, eighteen named benchmark sources.
Explore
The questions buyers ask before signing.
If the answer isn't here, ask Aria in the live demo — Aria will answer with the same benchmark discipline the engagement uses.
How is readiness actually measured?
Across four axes: data maturity, workflow observability, change capacity, integration posture. Each has a scored rubric with the evidence behind the score disclosed.Why not just pilot everything and see what sticks?
Most pilots fail because of operational fit, not model performance. Spending the budget on pilots before you know which workflows are ready is the well-documented way to burn a year.What if we want to build internally?
Build is a valid recommendation. Aria ships with the reasoning and the trade-offs disclosed; the build decision can be made with the same evidence as the deploy decision.How do you prevent pilot purgatory?
Every deployment ships with success criteria and a kill rule. If the metric doesn't move by the deadline, the pilot gets killed — not extended.We've done an AI readiness assessment before — what's different?
Most readiness assessments are maturity-model questionnaires that produce a grade. Aria produces a ranked roadmap of specific workflows, sized in dollars, with a deployment plan. Graded readiness is a report; ranked workflows is a plan.Does Aria cover generative AI specifically, or all AI categories?
All of them — plus automation that isn't AI at all. The question is always what's the cheapest reliable way to move a metric, and the answer is sometimes RPA, sometimes GenAI, sometimes a script, sometimes a process change.Can we start with one workflow rather than a full assessment?
Yes. For tightly-scoped pilots — one workflow, one KPI — deployment can run in parallel with assessment. Most customers start with the assessment because it sizes the prize across the business, not just one workflow.
Diagnosis before prescription.
Book a demo and see how Aria works through AI Readiness.