Company Profile
Company Type
Specialty healthcare practice
Team Size
30-150 employees
Industry
Healthcare
Key Challenge
Struggling with inefficient manual lead qualification processes that were slowing growth and increasing operational costs. Their primary concern was HIPAA compliance.
Tools Connected
The Challenge
This specialty healthcare practice was struggling with a fundamental problem: they couldn't tell good leads from bad ones fast enough. With a team of 30-150 employees, their healthcare business was generating 500+ inbound leads per month across multiple channels — website forms, phone calls, trade show contacts, and referral partners. Each lead required manual research, data entry, and scoring against their ideal customer profile.
The bottleneck was crushing their growth. Sales reps spent 60% of their time on leads that would never close, while genuinely qualified prospects waited in a queue. Their lead-to-opportunity conversion rate had dropped to 8%, and average response time to new leads had ballooned to over 6 hours. In the competitive healthcare market, that delay was the difference between winning and losing deals. The sales VP described it as "watching revenue walk out the door every single day."
The Solution
The team deployed Arahi AI to completely reimagine their healthcare lead qualification workflow. Rather than replacing their existing tools, they connected Epic and Kareo to Arahi AI's platform and configured three specialized AI agents: one for lead enrichment, one for scoring, and one for routing and follow-up.
The enrichment agent automatically pulled company data, social profiles, and healthcare-specific signals for every new lead. The scoring agent evaluated each enriched profile against a weighted scorecard that the sales team helped design — factoring in budget, authority, need, timeline, and healthcare-specific criteria like regulatory readiness and technology maturity. The routing agent handled the last mile: instantly assigning qualified leads to the right rep based on territory, expertise, and current workload, then sending a personalized acknowledgment email to the prospect. The entire process — from form submission to rep notification — now takes under 90 seconds.
The Results
Measurable improvements across key healthcare lead qualification metrics.
First Response Time
99.6% faster
Before
6+ hours
After
< 90 seconds
Conversion Rate
163% increase
Before
11%
After
29%
Manual Qualification Time
88% reduction
Before
25 hrs/week
After
3 hrs/week
Pipeline Value
133% growth
Before
$180K/month
After
$420K/month
Lead Data Accuracy
36% improvement
Before
72%
After
98%
“What impressed me most was the setup speed. I expected a months-long implementation, but we had AI agents handling our healthcare lead qualification workflow within a single afternoon. The no-code approach meant our team could configure everything themselves without waiting on IT.”
Director of Business Operations
Specialty healthcare practice
Key Takeaways
The most important lessons from this healthcare lead qualification automation project.
Automating lead qualification in healthcare delivered immediate, measurable results: faster processing, higher accuracy, and lower costs.
The key to success was connecting existing healthcare tools to AI agents rather than replacing the entire tech stack.
24/7 automated processing eliminated backlogs and ensured consistent service quality regardless of volume fluctuations.
Starting with a pre-built template and customizing for healthcare-specific requirements dramatically reduced time-to-value.
Implementation Timeline
From zero to production in Half a day — here's how they did it.
Step 1: Mapped the existing lead qualification workflow
Documented every step of the current manual lead qualification 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 lead qualification 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 lead qualification instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
Half a day
AI Agents
3 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating lead qualification in healthcare.
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