Investor Presentation
BonaLab
Medical Imaging AI Orchestration Platform
01 / The Problem
Hospitals want AI, but can't build it themselves.
Vendor AI underperforms on their patient populations
Building in-house requires ML expertise they don't have
Sending data externally creates regulatory complexity
"One size fits all" AI doesn't reflect local practice
"We bought three AI tools. None of them work as well as the demos."
Chief Medical Informatics Officer, Academic Medical Center
02 / The Distribution Shift Problem
AI performance varies by population.
Same model, different results
AI models must be trained or fine-tuned on local data to perform optimally.
03 / Our Solution
Own your AI. Train on your data.
Ingest
Connect to PACS
Annotate
Your team labels
Train
One-click training
Deploy
Production + monitor
All within your hospital's network. Data never leaves. Models are owned by the hospital.
04 / Architecture
Maximum control. Zero data leakage.
Hospital Firewall
Your PACS/VNA
Images stay here
BonaLab Platform
Deployed on-premise
Your AI Models
Owned by you
No cloud dependencies. No external data transfers. No third-party access.
05 / Why BonaLab
Build vs. Buy vs. BonaLab
| Option | Time | Cost | Risk |
|---|---|---|---|
| Build in-house | 18+ months | $2M+ (ML team) | High (expertise gaps) |
| Buy vendor AI | 3-6 months | $150K-500K/yr | Medium (performance gaps) |
| BonaLab | 3-6 months | $50K-150K/yr | Low (own data, own models) |
BonaLab provides the platform. Hospitals provide the data and clinical expertise.
06 / Use Cases
What hospitals build with BonaLab
Chest X-Ray Triage
Auto-prioritize critical findings like pneumothorax and cardiomegaly.
40% faster critical case routing
Incidental Finding Detection
AI second-read for nodules, masses, and other incidental findings.
Reduced miss rates
Quality Assurance
Compare AI predictions against final reports for peer review.
Continuous learning loop
Research Datasets
IRB-ready labeled datasets at scale for publications.
Accelerated research output
Every hospital's needs are different. BonaLab lets them build what matters to them.
07 / Market Opportunity
Healthcare AI infrastructure
Healthcare AI
$45B
by 2028
Medical Imaging AI
$7.4B
by 2028
MLOps Tools
$4.2B
by 2028
We're not building AI models. We're providing the infrastructure for hospitals to build their own.
08 / Our Customer
Health systems ready for AI ownership
| Attribute | Description |
|---|---|
| Who | Academic medical centers, large health systems, specialty hospitals |
| Size | 200+ beds, radiology volume of 100K+ studies/year |
| Trigger | Disappointment with vendor AI, strategic AI initiative |
| Champion | CMIO, Chief AI Officer, Radiology Chair |
| Budget | IT capital budget or innovation fund |
5,000+ hospitals in the US meet this profile. 50,000+ globally.
09 / Business Model
Platform licensing + professional services
Platform License
Core orchestration platform
$50K-150K/year
Implementation
Deployment, PACS integration, training
$25K-75K
Success Services
Ongoing optimization, new use cases
$2K-10K/month
Avg Contract Value
$100K ARR
Gross Margin
80%
Expansion Rate
150%
10 / Competitive Moats
Why incumbents can't replicate
01 / Healthcare-Native Design
Built by healthcare professionals for healthcare workflows. Not a generic MLOps tool adapted for healthcare.
02 / On-Premise First
Designed for air-gapped hospital networks. Competitors are cloud-native trying to go on-prem.
03 / Clinical Annotation Tools
Purpose-built for medical imaging. Not generic labeling tools with medical "features" added.
04 / Regulatory Framework
HIPAA, GDPR, SOC 2 compliance built from day one. Not afterthoughts.
11 / The Ask
Raising $3M Seed
Use of Funds
18-Month Goals
The Opportunity
Healthcare is the largest industry in the US, at $4.3T annually.
AI will transform every clinical workflow.
Hospitals need infrastructure to build, not just buy.
BonaLab is building that infrastructure.
Contact
BonaLab
founders@bonalab.ai
"The best AI for your patients is trained on your patients."