Company Profile
Company Type
Specialty healthcare practice
Team Size
50-200 employees
Industry
Healthcare
Key Challenge
Struggling with inefficient manual customer onboarding processes that were slowing growth and increasing operational costs. Their primary concern was patient data security.
Tools Connected
The Challenge
Onboarding was this specialty healthcare practice's Achilles heel. Despite having a solid healthcare product and 50-200 employees, new customers were falling through the cracks during the critical first 30 days. The onboarding process relied on a patchwork of spreadsheet checklists, calendar reminders, and manual email sends that broke down at any meaningful scale.
The impact on retention was severe. Customers who completed onboarding within 14 days had a 92% retention rate at 6 months, but only 40% of customers hit that benchmark. The rest were left to figure things out on their own, with predictable results: 22% churn within 90 days. Each churned healthcare customer represented $8,000-$15,000 in lost annual revenue, making onboarding failures one of the most expensive problems in the business. The team knew what good onboarding looked like — they just couldn't execute it consistently at scale.
The Solution
Arahi AI provided the automation backbone this healthcare team needed. They deployed a multi-agent workflow that breaks the customer onboarding process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from Epic and Kareo. The second agent analyzes and processes incoming requests using healthcare-specific business logic. The third agent executes actions across connected tools and notifies team members via Slack.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full customer onboarding workflow was operational within a single afternoon. They used Arahi AI's template for healthcare customer onboarding as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 customer onboarding instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key healthcare customer onboarding metrics.
Time to First Value
76% faster
Before
21 days
After
5 days
Onboarding Completion Rate
45% improvement
Before
65%
After
94%
60-Day Churn Rate
78% reduction
Before
18%
After
4%
CS Team Time on Onboarding
64% freed up
Before
70% of capacity
After
25% of capacity
Customer Satisfaction (CSAT)
44% increase
Before
3.2/5
After
4.6/5
“The difference is night and day. Our healthcare clients used to wait days for customer onboarding to be completed. Now it happens in minutes, and the quality is consistently higher than what we achieved manually. Customer satisfaction scores went through the roof.”
VP of Customer Success
Specialty healthcare practice
Key Takeaways
The most important lessons from this healthcare customer onboarding automation project.
This healthcare team proved that customer onboarding automation doesn't require technical expertise — the no-code platform made it accessible to business users.
Scaling customer onboarding capacity by 10x without adding headcount fundamentally changed the economics of their healthcare operations.
Consistent AI-powered processing eliminated the quality variance that came with different team members handling customer onboarding differently.
Real-time visibility into customer onboarding metrics gave leadership the data they needed to make better strategic decisions.
Implementation Timeline
From zero to production in Half a day — here's how they did it.
Step 1: Mapped the existing customer onboarding workflow
Documented every step of the current manual customer onboarding process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.
Step 2: Built the automation in Arahi AI
Used Arahi AI's no-code builder to create the customer onboarding workflow: connected Epic and Athenahealth as data sources, configured AI decision logic for healthcare-specific requirements, and set up automated actions and notifications.
Step 3: Parallel run with manual process
Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on 98% of customer onboarding instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
Half a day
AI Agents
4 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating customer onboarding in healthcare.
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