Seguros Bolívar cuts prior authorization from three to four weeks to near real time with n8n and Gemini AI
Seguros Bolívar's prior authorization process required clinical staff to manually review each medical order, verify policy coverage and exclusions, and authorize or deny requests—a process taking three to four weeks per case. Orders arrived in inconsistent formats across images, PDFs, and other document types, and the company's 20-year-old legacy core system made automation through traditional development costly, rigid, and error-prone.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Medical order arrives
Medical orders arrive in inconsistent formats including images, PDFs, and different document types.
Tools used
n8nGemini AI
Outcome
The prior authorization process went from three to four weeks to near real time, with many authorizations now generated on the spot. Over 300 active n8n workflows run across the organization with 3,000 employees enabled, and the operational cost of the authorization process dropped drastically. Clinical staff can now focus on medical judgment rather than repetitive administrative tasks.
What failed first
Modifying the legacy core system to address the bottleneck was ruled out as not viable; traditional software development on the 20-year-old core was described as costly, inflexible, and error-prone.