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Case StudyHealthcareSocial Media

From Manual to AI: Social Media in Healthcare

Learn how a healthcare company used Arahi AI to automate social media, achieving 97% faster faster task completion time and 85% savings in monthly cost.

Company Profile

Company Type

Regional medical group

Team Size

50-200 employees

Industry

Healthcare

Key Challenge

Struggling with inefficient manual social media processes that were slowing growth and increasing operational costs. Their primary concern was patient data security.

Tools Connected

EpicCernerAthenahealthKareoGoogle Forms
Setup Time90 minutes
Agents Deployed4 AI agents

The Challenge

Manual social media was the biggest bottleneck in this regional medical group's operations. Their team of 50-200 employees processed hundreds of social media requests weekly, each requiring multiple steps, cross-referencing against healthcare-specific requirements, and coordination between departments. The average social media request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.

Beyond the time drain, the quality of their social media output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in healthcare. A recent audit revealed that 12% of completed social media records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.

The Solution

Arahi AI provided the automation backbone this healthcare team needed. They deployed a multi-agent workflow that breaks the social media 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 social media workflow was operational within a single afternoon. They used Arahi AI's template for healthcare social media 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 social media instances with 99%+ accuracy — more than the team typically handled in a month.

The Results

Measurable improvements across key healthcare social media metrics.

Task Completion Time

97% faster

Before

2-3 hours average

After

< 5 minutes

Team Productivity

250% increase

Before

Baseline

After

3.5x output

Quality Score

26% improvement

Before

78% accuracy

After

98.5% accuracy

Monthly Cost

85% savings

Before

$8,200/month

After

$1,200/month

Customer Satisfaction

35% increase

Before

3.4/5

After

4.6/5

The ROI was almost immediate. Within the first month, our social media throughput increased by over 300% while our error rate dropped to near zero. For a healthcare business of our size, that translates directly to the bottom line. Arahi AI paid for itself in the first week.

Operations Director

Regional medical group

Key Takeaways

The most important lessons from this healthcare social media automation project.

This healthcare team proved that social media automation doesn't require technical expertise — the no-code platform made it accessible to business users.

Scaling social media 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 social media differently.

Real-time visibility into social media metrics gave leadership the data they needed to make better strategic decisions.

Implementation Timeline

From zero to production in 90 minutes — here's how they did it.

Step 1: Mapped the existing social media workflow

Documented every step of the current manual social media 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 social media 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 social media instances, with the 2% of edge cases automatically flagged for human review.

Setup Time

90 minutes

AI Agents

4 AI agents

Tools Connected

5 integrations

Frequently Asked Questions

Common questions about automating social media in healthcare.

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This case study represents a typical customer scenario. Individual results may vary.