Pain
Manual effort, bottlenecks, time burden, and operational drag.
Operational AI assessment
Find the workflows in your business that are actually worth automating with AI.
Evaluate workflow pain, repetition, data readiness, integration complexity, risk, ROI potential, and human-in-the-loop needs before investing in a build.
0
100
Workflow painHigh signal
Data accessValidated
GuardrailsDesigned
ROI caseMeasurable
What it measures
Score the workflow, not the AI hype.
Automation fit
Repetition, volume, decision structure, and approval needs.
Readiness
Data quality, system access, integration complexity, and maturity.
Controls
Risk, compliance sensitivity, review paths, and measurable rollout gates.
10 minute assessment
AI workflow scorecard
Readiness result
0
out of 100
Subscore breakdown
Why this score
Recommended pattern
Tailored recommendations
Human-in-the-loop controls
Risks and mitigations
2-6 week roadmap
Success metrics
Portfolio case study
From workflow ambiguity to an automation investment decision.
Problem
Many teams start with a model idea instead of a workflow diagnosis, which leads to pilots without measurable business value.
Workflow
The app captures operator context, operational pain, data readiness, systems, approval requirements, and risk posture.
AI design
Scores are deterministic. The LLM layer only summarizes and tailors recommendations from grounded inputs and calculated scores.
Guardrails
Every result includes human review controls, auditability, rollout gates, risks, mitigations, and success metrics.
Business value
Leaders can prioritize workflows where AI has enough pain, repetition, data access, and ROI potential to justify delivery effort.
Decision output
Each assessment gives leaders a clear recommendation: automate now, prepare the workflow first, run discovery, or choose a better first use case.