BEKHealth Deck
BEKHealth is a tech company selling an AI-powered patient-matching platform that helps sites and healthcare organizations identify qualified patients for clinical trials. They extract both structured and unstructured data from Electronic Medical Records (EMRs) to speed up patient identification.
Created with love ❤️
By Cristian @ Ken AI
Product
What it is
  • BEKplatform uses AI to analyze EMR data
  • Identifies qualified trial participants 10x faster than manual methods
  • Achieves 93% accuracy in interpreting EMR records
  • Processes structured data and unstructured data (doctor notes, PDFs, lab reports)
Benefits & Features
Benefits & Features:
  • Processes structured and unstructured data (doctor notes, PDFs, lab reports)
  • 93% accuracy in interpreting EMR records
  • Automated ETL pipeline with 25+ EMR connectors
  • Query and cohort builder functionality
  • Real-time feasibility reports
Problems it solves
Problems it solves: Manual chart reviews are time-consuming, expensive, and inefficient for finding trial participants
Why this matters
  • Manual patient identification is time-consuming and expensive
  • Sites currently use manual chart reviews or direct mail for recruitment
  • Process takes weeks instead of minutes
  • Requires dedicated staff for manual searches
Price
  • Average deal size: $40,000 per year
  • Range: $20,000 - $100,000 based on EMR connections and size
Target Market
Location
United States (focus on healthcare hubs)
Company Size
Large site networks and moderate-sized physician offices
Industry
Healthcare (specifically clinical research sites, hospitals, CROs)
Role
Clinical trial coordinators, Research directors, Site managers
Seniority
Director-level and above decision makers
50k
Total LinkedIn Market
50%
Valid Emails Found
Customer Pain Points
A list of top pain points that our product helps solve for our target audience.
1
Time-Consuming Manual Search
Clinical staff spend weeks manually searching EMRs instead of minutes
2
Hidden Eligible Patients
Missing qualified patients buried in unstructured data like doctor's notes and PDFs
3
Resource Inefficiency
High costs of dedicated personnel doing manual chart reviews
4
Slow Trial Enrollment
Delays in patient identification cause trials to miss enrollment deadlines
5
Staff Misallocation
Clinical coordinators stuck doing data entry instead of patient care
6
Competitive Disadvantage
Sites losing trial opportunities due to slow patient identification
Competitive Advantages

Unstructured Data Processing
93% accuracy in reading handwritten notes, PDFs, and lab reports where competitors fail

Rapid Implementation
2-8 weeks vs months for other solutions, with 25+ existing EMR connectors

Human-Verified AI
Proprietary human-in-the-loop system ensures reliability, unlike pure AI solutions

10x Patient Discovery Rate
Finds significantly more eligible patients than manual methods or basic EMR search tools

End-to-End Partnership
Exclusive Areti Health integration for complete identification-to-enrollment automation

Real-Time Feasibility
Instant trial feasibility reports vs days/weeks with traditional consulting methods
Customer Results & Case Studies
Memorial Cancer Institute (Oncology Clinical Research)
Director quote: "We were able to pre-screen 10+ new lung cancer patients in the last three weeks and offer the study to three patients." We were able to pre-screen 10+ new lung cancer patients in the last three weeks and offer the study to three patients. Result: Found patients for selective cancer trials they previously couldn't identify Impact: Enabled recruitment for cutting-edge clinical trials that were struggling to find qualified participants
First Joint Client with Areti Health Partnership
Results achieved within 60 minutes of implementation:
200 clinically-eligible patients identified by BEKHealth 12 patients pre-screened by Areti Health 8 patients scheduled for appointments
Impact: Immediate return on investment with rapid patient identification and enrollment
General Customer Results (Aggregate Data)
10x more patients identified compared to manual methods 3x more qualified patients enrolled Patients found in days instead of months 2x faster enrollment goals achievement
Additional Insights
  • Current Marketing Status & Challenges:
  • Emily Nichols started in January 2025 as marketing lead
  • Previous marketing team dissolved in 2024 (one person let go, one quit)
  • Current email campaigns: 5% open rate, 0.1% click rate
  • HubSpot has 45,000 contacts but only 23,000 are relevant
  • Demo requests were coming in but not being followed up on
  • Sales team has been "recklessly dumping" contacts into HubSpot without proper qualification
Sales Team Structure:
  • 3 salespeople with distinct territories (Ciara, Andrew, Brian)
  • Territory conflicts have caused "squabbles" between sales reps
  • Sales team functions as both SDRs (prospecting) and account executives
  • Need to route leads based on company headquarters location
What Hasn't Worked:
  • Automated email campaigns (poor engagement rates)
  • Manual contact dumping into HubSpot
  • Lack of follow-up on demo requests
  • No proper lead qualification system
Current Lead Generation Sources:
  • Conferences/trade shows (primary source)
  • Sales team prospecting
  • Limited inbound from website
  • Very few weekly leads (1-2 per week)
Recent Improvements:
  • Automated demo request follow-ups (15-minute response)
  • 3-step sequence reduced to 1-step with calendar link
  • New thank you pages with demo video
  • Partnership with Areti Health showing promise
Strategic Considerations:
  • Most prospects are problem-aware but not solution-aware
  • Focus on Tier 1 (large site networks) and Tier 2 (physician-owned)
  • Avoid Tier 3 (large academic hospitals) due to slow sales cycles
  • Need to clean up HubSpot data for better targeting
  • Calendly integration required for proper lead routing
Areti Health Partnership:
  • Launched December 2024
  • Two joint customers showing strong results
  • Considering deeper integration or merger
  • Creates end-to-end solution (identification + enrollment)
Funnel
1
Awareness Email → Demo Video → Discovery Meeting
  • Focus: Patient identification challenges
  • Lead magnet: Free EMR analysis report
  • CTA: Schedule discovery meeting to review findings
2
Solution Email → Demo Video → Strategy Meeting
  • Focus: AI-powered patient matching
  • Lead magnet: 5-minute platform demo video
  • CTA: Book strategy session to discuss implementation
3
Social Proof Email → Case Study → ROI Discussion
  • Focus: Results achieved by other sites
  • Lead magnet: Detailed case study
  • CTA: Schedule ROI discussion meeting
4
Value Email → Discovery Call
  • Focus: Direct value proposition
  • CTA: Book implementation planning call
Email Sequence
These are the email sequence steps we will follow. Each step should be unique and have a clear goal.
1
Problem Recognition
  • Description: Highlights the pain of manual patient identification and lost revenue from slow trial enrollment. References industry statistics about trial delays and costs.
  • CTA: Watch 5-minute demo video showing the platform in action
2
Solution Introduction
  • Description: Introduces AI-powered patient matching as the solution. Briefly explains how BEKHealth processes structured and unstructured EMR data to find 10x more patients.
  • CTA: Watch 5-minute demo video showing the platform in action
3
Social Proof
  • Description: Features Memorial Cancer Institute case study with specific results: finding patients for selective trials they previously couldn't identify.
  • CTA: Access full case study collection (3 available)
4
Partnership Value
  • Description: Showcases BEKHealth + Areti Health partnership results: 200 eligible patients identified, 8 scheduled within 60 minutes of implementation.
  • CTA: Schedule 30-minute discovery meeting to explore implementation
5
Direct Meeting Request
  • Description: Summarizes ROI potential (2x faster enrollment, 3x more qualified patients). Emphasizes rapid 2-8 week implementation and existing EMR connectors.
  • CTA: Schedule 30-minute discovery meeting to explore implementation