A lead engine rebuilt around action—not admin.
An anonymized lead-operations case study with multi-list routing, booking removal, lifecycle guards, 180+ recovered accounts, and a 39.6% unique dial rate.
Explore this service →Selected systems · evidence
AI automation work with the theatre removed.
These case studies describe the constraint, architecture, controls, evidence basis, and documented result. Client identities are withheld where required; scope counts are not presented as outcomes; no result is a promise of future performance.
Direct answer
A useful AI automation case study should distinguish verified outcomes from implementation scope, explain how the system worked, identify the evidence source, and state what readers should not infer from the result.
Published system evidence.
Each page separates business context, delivered architecture, measured evidence, and interpretation limits.
Fifteen-plus channels. One operational view.
An anonymized automation case study unifying data from 15+ channels through APIs, n8n, Airtable, Looker Studio, and scheduled Slack reporting.
Explore this service →A migration factory—not 108 copied workflows.
A documented automation migration architecture that grouped 108 Make scenarios into reusable n8n workflow families with parity and QA gates.
Explore this service →What Aixcel will publish—and what it will not.
Evidence is useful only when readers know what it means.
Clearly labelled
Anonymized work, internal records, documented scope, and measured outcomes are identified as such.
Specific definitions
Metrics retain their original meaning, context, and limits rather than being inflated into a larger claim.
No borrowed credibility
No invented logos, anonymous praise presented as fact, scraped reviews, or implied client endorsement.
No result guarantees
Past evidence informs an evaluation; it does not promise that another business will produce the same result.
Bring us the constraint. Leave with a clearer next move.
In 25 focused minutes, we will map where work or revenue is getting stuck, test whether AI is the right intervention, and identify the highest-leverage first step.
Book a free systems audit