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See how we've helped companies across healthcare, manufacturing, professional services, retail, and more eliminate manual work, reduce errors, and accelerate their operations with intelligent automation.
A 12-location retail chain struggled with inventory discrepancies costing $30K+ monthly in lost sales and overstock. Manual stock counts were done weekly but data wasn't consolidated until month-end. Each location used different methods for reordering, leading to frequent stockouts of popular items and overstock of slow movers.
A medical research institution needed to share clinical data with external researchers while maintaining HIPAA compliance. Manual redaction of PII (names, dates, locations, medical record numbers) from hundreds of documents per month was time-consuming and carried high risk of human error exposing protected health information.
An automotive parts manufacturer was losing $50K+ monthly due to quality defects discovered late in production. Manual quality inspections created data entry backlogs, and production metrics were only available at end of shift, making it impossible to catch issues early. Paper-based inspection reports were difficult to analyze for trends.
A 50-attorney law firm was overwhelmed with manual client intake processes. New matter setup required 12+ manual steps across 4 systems, taking 3-4 hours per client. Document processing involved manual data extraction from intake forms, and conflicts checks were done manually through spreadsheets, creating compliance risks.
A clinical research organization was spending 40+ hours per week manually reviewing study documents, extracting findings (protocol deviations and errors), and generating compliance reports for hospital partners. The manual process was error-prone and delayed critical communications to study sites.
This fast-growing SaaS company was struggling with inconsistent employee onboarding and offboarding across 12 different tools. IT spent 15+ hours per new hire manually creating accounts, and offboarding often missed critical systems, creating security vulnerabilities.
A cloud-native startup was experiencing alert fatigue with 200+ alerts per day. Mean time to resolution (MTTR) averaged 45 minutes, and engineers were spending nights and weekends responding to incidents that could be automated.
A fast-growing fintech company was experiencing rapid team expansion, leading to an overwhelming number of L2 support tickets for user provisioning and access requests. Manual processes took 3-5 days per request, creating bottlenecks and security risks from temporary overprivileged access.