AI solutions for healthcare
AI solutions for healthcare are transforming patient care, but navigating the tech landscape can be a headache. Clunky legacy systems, data security nightmares, and AI integration challenges make innovation an uphill battle. That’s where Vention stands out as the healthcare software development partner of choice.
From MVP to unicorn with Thirty Madison, from Series A to IPO with Dialogue — we’ve been there, bringing engineering peace of mind every step of the way. And we’ll be there for you, too.
How AI can benefit healthcare market players
Healthcare providers
Sharper medical diagnosis, smarter treatments, and intelligent medication management for faster, more accurate decisions. But that’s not all — healthcare AI solutions also streamline hospital workflows and optimize resources, shifting the focus to patients.
Telemedicine providers
AI fuels every stage of telehealth — from virtual diagnostics and remote monitoring to personalized treatment recommendations. And it goes beyond patient care, enhancing and accelerating internal processes for greater efficiency.
Pharmaceutical manufacturers, life science, and biotech companies
AI brings value at every stage of drug production. It’s behind faster research and development, safer trials, higher-quality medicines, enhanced manufacturing efficiency, and streamlined distribution.
Health insurance providers
AI is reinventing health insurance with smarter risk assessments, lightning-fast claims processing, fraud detection, and personalized plans. With predictive analytics and automation, insurers can accelerate approvals, lower costs, and provide more proactive care.
Medical device and SaMD manufacturers
AI boosts product innovation, quality control, manufacturing efficiency, supply chain management, and patient outcomes — all thanks to medical devices and SaMD that deliver more accurate diagnostics, real-time monitoring, and personalized treatments.
AI is transforming the healthcare industry. If you’re still on the fence, don’t be: The latest stats on AI in healthcare speak for themselves.
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94 percent of healthcare companies are already leveraging AI. The future isn’t coming — it’s here.
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AI in the drug discovery market is exploding — from $0.9B in 2023 to $4.9B by 2028, growing at a CAGR of 40.2 percent.
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Healthcare chatbots? Growing from $116.9M in 2018 to $345.3M by 2026 (CAGR of 14.5 percent).
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Virtual assistants? Expected to skyrocket at a 44.2 percent CAGR from 2024 to 2030.
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FDA approvals are surging —169 ML/AI-powered medical devices cleared in just Q1–Q3 2024, nearly matching 2023’s total of 223 and already exceeding 2022’s total of 160.
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In January 2025, the FDA issued clear recommendations on AI devices and software, signaling even greater momentum.
Our AI solutions for healthcare
Know a hero when you see one. AI solutions in healthcare streamline workflows, enhance diagnostics, and improve patient outcomes. See how the right approach to AI can transform the way you deliver care.
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Diagnose diseases with medical imaging software that reads MRIs, CTs, and ultrasound scans.
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Bring precision to the operation room with AI-assisted surgeries.
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Control drug manufacturing quality: Know if the dosage is accurate and formulation consistent.
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Secure medical device production with immediate automated alerts for misplacements and potential future malfunctions.
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Ensure safe drug storage and transportation: leave no temperature fluctuations, packaging damage, or condensation unnoticed.
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Detect fraud, verifying claims with pinpoint accuracy.
AI-driven predictive analytics to forecast future trends and outcomes
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Spot hidden risks of complications and early warning signs among health and lifestyle data.
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Detect the next breakthrough drug by identifying promising targets through biological and genetic analysis.
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Give old drugs new life: AI uncovers existing medications that can be repurposed for new treatments.
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Optimize trials by predicting how a patient may respond to a drug.
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Prevent costly breakdowns of manufacturing equipment before they cause downtime.
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Anticipate drug demand to prevent shortages and overproduction.
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Optimize logistics and distribution routes.
Data mining to turn tons of data into insights
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Spot insights, patterns, and trends among medical research papers, industry news, public health databases, and other relevant data sources.
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Find the most effective treatments by analyzing past patient outcomes, medication responses, and lab results.
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Facilitate real-world evidence analysis, sifting through large-scale patient data for drug effectiveness and treatment outcome patterns.
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Enable remote health monitoring, make wearable devices your ally, and quickly recognize abnormal vital signs and patterns that require attention.
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Detect fraud like irregular billing patterns and duplicate claims.
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Appointment scheduling tools: AI-enabled reminders, rescheduling, and waitlist optimization that help keep schedules full.
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Medical information retrieval: It’s a matter of seconds, and the retrieved clinical insights are accurate and context-aware.
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24/7 symptom checkers and triage bots: AI evaluates symptoms, provides initial assessments, and directs patients to the right care.
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AI-powered virtual nurses: Keep patients on track with medication, chronic disease management, and post-treatment care.
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Medication adherence with smart reminders for doses, refills, and treatment plans.
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Personalized insights and recommendations tailored to lifestyle, diet, and health conditions.
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Voice recognition tools: Let deep learning models create transcripts and summaries of doctor-patient interactions. This will enhance understanding and reduce paperwork.
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Medical coding and billing: Translate clinical notes into billing codes automatically, reducing errors and administrative workload.
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Automated insurance claims processing: AI-driven text recognition solutions can convert transcripts and summaries of patient visits into claims.
All it takes is an idea — we’ll handle the rest. From strategy to implementation, we guide you at every stage, ensuring AI delivers real impact.
Get clarity on your biggest questions:
- What tangible value will AI bring?
- Are my systems and data ready?
- Where do I even start?
Why Vention
Years of custom software development expertise
Projects delivered for the healthcare industry leaders like Thirty Madison and Dialogue
Dedicated experts with deep healthcare knowledge and AI proficiency
Engineers with experience in all major healthcare regulations, including HIPAA, HITECH, HITRUST, FDA
ISO 27001-certified to ensure top-tier security management practices
Our commitment? Engineering peace of mind.
That’s why we launched the Vention AI Group — a powerhouse of AI expertise, proven tools, best practices, and hands-on training. From pioneering innovations to industry-leading education, this is where AI excellence takes shape.
And our dedication doesn’t go unnoticed. We’re proud to be recognized globally and within the healthcare industry:
Most Innovative Healthcare Software Development Enterprise 2024
HealthTech AI Engineering Pioneers of the Year 2024
Inc. 5000
Six-time honoree among America’s fastest-growing private companies
Financial Times
Five-time honoree among the fastest-growing companies in the Americas
IAOP
Four-time honoree on the Global Outsourcing 100 list by the International Association of Outsourcing Professionals
Trusted by healthcare leaders: See the difference we make
Nothing motivates us more than our clients' success. Their feedback fuels our passion, drives innovation, and pushes us to deliver more outstanding results — because when they thrive, so does healthcare.
We have successfully launched the integration projects and product features to increase conversion rate and captured wider markets. It results in a good retention rate in our user base and increased our clients' satisfactions.
Not only they were highly skilled professionals in their own domain, but also they have good communication skills. They are very honest and constructive and provided invaluable feedback to us as well.”
Jun Seki
CTO, Healthera
I was impressed with how quickly they were able to integrate into our existing teams. Despite their remote locations, they’re already embedded within our internal operations.
They easily adjusted to the dynamic and continue to manage a high level of communication to assure they’re always on pace with our full-time team.”
Co-founder and CTO
They recently built an AI agent with Ph.D.-level research and development skills; the result was a breakthrough for that industry.”
Paul Steckler
Founder & Senior Partner, Ramp Catalyst
I'm the owner of an AI startup. Developing a platform for customer relationship intelligence. The level of expertise of the developers they let me interview is impressive.
The programmers are a fantastic addition to the group. They were promptly integrated and brought up to speed. When we had a developer that wasn't a good fit, they swiftly offered a replacement.”
Lior Harel
CTO, Staircase AI
The Vention team has been a truly supportive and professional partner throughout our project. They’ve shown a remarkable level of personal engagement with our goals, demonstrating a genuine commitment to our success as a startup.
The management team, in particular, understood the unique challenges we face as a startup, offering innovative solutions while being mindful of our limitations. Their flexibility, collaboration, and proactive approach have played a key role in the smooth progress of the project, making them an invaluable asset to our team.”
Elena Minich
Head of Content, Export Hunter UAB
See our work in action
Choosing a development partner is a big decision — especially in healthcare, where outcomes and lives are at stake.
With deep AI expertise and a keen understanding of healthcare’s complexities, we do more than build custom AI solutions. We anticipate challenges, uncover opportunities, and eliminate uncertainty with a proven, professional approach — just as we’ve done for our clients, time and again.
Triage chatbot and AI-powered solution for precision medicine
To ease the administrative staff's workload, we built a medical triage chatbot that efficiently assigns patients. Our experts also developed a precision medicine app featuring an AI-powered symptom checker for accurate assessments.
App transforming scans into anatomical models
Our AI developers built a mixed-reality app that transforms CT and MRI scans into interactive 3D models. With the ability to rotate, zoom, and explore tissue layers in detail, medical professionals gain unprecedented insights into patient anatomy.
AR-assisted visualization enhances surgical precision, helping surgeons navigate complex structures confidently, reducing risks, and improving patient outcomes.
Neural networks monitoring solution for Comet
We developed a monitoring solution that tracks and manages neural network training. It automatically identifies key metrics, compares experiments, and optimizes the training process on the go. All this helps streamline the development of healthcare IT solutions for their end clients.
Preclinical imaging analysis platform for an optical imaging company
To streamline preclinical imaging analysis, we developed a platform that enables region of interest detection based on luminescent images. The solution also facilitates image merging and shape adjustments, optimizing research efficiency and advancing medical discoveries.
How we build AI solutions for healthcare
Many vendors talk about AI in healthcare the same way — but the real difference lies in how it’s delivered.
The Vention way? A focus on your needs, attention to detail, and a commitment to engineering peace of mind.
Needs analysis
We listen closely to your requests while identifying hidden challenges, unspoken pain points, and untapped opportunities — so we can recommend the best-fitting AI solutions.
Risk assessment and mitigation
Lack of trust in AI? Concerned about its accuracy and security? We proactively mitigate AI-related risks. Our AI developers train models with high-quality, bias-free data and, if needed, implement interpretable AI models while keeping clinicians in the loop.
Data collection and preparation
We analyze the data an AI solution needs — think EHR records, lab results, medical images, or public data sets — and clean and anonymize it to ensure high-quality results.
Choice of AI model
Our AI engineers assess open-source models, test their performance, and explore whether fine-tuning can deliver the desired results. When off-the-shelf solutions fall short, we build custom models tailored to specific healthcare challenges, factoring in data complexity, real-time processing requirements, and model interpretability.
Integration with healthcare systems
We recommend suitable APIs and middleware or develop custom integrations to connect your AI solution with key healthcare IT systems. These may include EHRs, patient portals, laboratory information systems, medical imaging archives, and health information exchanges.
To ensure smooth data exchange, our integration approach follows healthcare standards like FHIR, HL7, and DICOM.
Compliance and security
We prioritize compliance and security from the very start, embedding critical features and regulatory requirements into the software design process. Our approach includes preparing for regulatory submission and clearance early.
Vention specialists have deep expertise in ISO 13485, IEC 62304, HIPAA, HITECH, ONC, and FDA regulations. We also implement robust security controls like data encryption and role-based access to safeguard sensitive healthcare data.
Testing and validation
Performance, scalability, load, and security testing are essential, but AI solutions for healthcare require more. Subject matter experts must be involved to validate AI model outputs, ensuring accuracy and clinical reliability. We have structured processes to establish close collaboration with medical professionals, allowing us to verify every detail.
Deployment and scalability
We only go live when we’re confident in the solution’s quality and reliability. From there, it’s built to scale, ready to handle more data sources, heavier workloads, and a growing user base. All without compromising performance.
Continuous monitoring and optimization
Upon your request, we can also equip you with monitoring solutions that track important AI model parameters such as accuracy, recall, and F1-score to ensure it’s performing as expected and not degrading.
Hear from our expert
At the very start of our journey, it's great to know if you plan to scale AI solutions, as your scalability goals influence our decisions regarding software design and implementation.
For example, an AI model trained for one hospital or region can underperform for a hospital network and other locations. Likewise, medical imaging software optimized for a single device brand may lock you into that ecosystem or require additional compatibility work if you decide to expand to other brands.”
Eugene Kruglik
Healthcare engineering manager
Investments and return on investments
Advanced AI solutions for healthcare require medium-to-high investments — but these aren’t just costs; they’re strategic investments with high-impact returns. The payoff? Better patient outcomes, reduced costs, revenue growth, and more efficient operations.
We've handpicked a standout example from each category of AI solutions to showcase the investment potential and ROI impact.
Computer vision
Solution example:
Medical imaging analysis for diagnostics
Investment range:
Medium to high
Cost influencing factors:
- Data set availability for model training
- Need to involve external subject-matter domain experts
- Need for compliance and certification
- Number of integrations with other hospital systems
ROI drivers:
- Potential for improved outcomes due to early disease detection
- Fewer misdiagnoses and false positives/negatives
- Lower operating costs compared to manual assessment
AI-powered predictive analytics
Solution example:
Predictive analytics for drug discovery
Investment range:
Medium
Cost influencing factors:
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Availability and quality of data sets
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Need for custom AI model development
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Number and complexity of data sources
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Need for real-time insights
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AI model explainability efforts
ROI drivers:
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Faster drug discovery
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Reduced R&D costs
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Stats: AI can cut timelines from five or six years to just one. It also has the potential to reduce costs by up to 70 percent.
Data mining
Solution example:
AI-powered insurance fraud detection
Investment range:
Medium to high
Cost influencing factors:
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AI model complexity
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Need for real-time processing
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Number of required integrations with other systems
ROI drivers:
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Reduced payouts
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Faster and less costly claim processing
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Real-time prevention
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Minimized compliance risks
AI-powered chatbots
Solution example:
AI-enabled symptom checker
Investment range:
Medium
Cost influencing factors:
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Number of symptoms, diseases, and conditions covered
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Need for custom AI model development
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Number and complexity of data sources
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Text- or voice-based
ROI drivers:
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Reduced patient triage costs
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Optimized provider processes (e.g., pre-screening patients before consultations, faster routing of high-risk patients)
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Low-cost scalability compared to extra staff hiring
Natural language processing
Solution example:
AI-driven medical transcription model
Investment range:
High
Cost influencing factors:
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AI model complexity
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Need for custom model development
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Required accuracy of medical speech recognition
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Need for multi-language support or dialect adaptation
ROI drivers:
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Reduced administrative overload
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Improved patient engagement and care continuity
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Error-free billing
Tell us the challenge you’re tackling with AI, and we’ll break down the investment required.
AI technologies in healthcare
The secret to AI success? The right technology. From machine learning frameworks to natural language processing, computer vision, and big data, these advanced tools lay the foundation for AI solutions that truly redefine healthcare.
Programming languages
Python
R
C++
Machine learning and deep learning
TensorFlow
scikit-learn
Keras
XGBoost
LightGBM
CatBoost
Sktime
Prophet
fast.ai
PyTorch
Transformers
PyTorch Lightning
Sentence-Transformers
Natural language processing
NLTK
spaCy
Gensim
FastText
TorchText
Transformers (by Hugging Face)
Computer vision
OpenCV
Detectron2
YOLO
Mask R-CNN
Torchvision
Mmdetection
Pillow
Albumentations
Generative AI
OpenAI GPT
DALL-E
Stable Diffusion
Midjourney
Big data technologies
Apache Hadoop
Apache Spark
Apache Kafka
Cloud
AWS
Azure
Google Cloud Platform (GCP)
FAQs
How do you ensure seamless integration with existing telemedicine platforms or medical devices?
If the platform or device vendor provides an API or integration toolkit, we rigorously test it for functionality, performance, security, and interoperability, answering key questions:
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Does it perform as expected?
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Can it handle the high load without lag?
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Will your data stay safe during the transfer?
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Does it speak the same language as your EHRs and other systems?
If no plug-and-play solution exists, we engineer a custom one, considering healthcare gold standards like HL7, FHIR, and DICOM — so data flows securely and seamlessly between platforms, wearable devices, and remote monitoring devices.
How do you manage international regulations when deploying AI across multiple regions?
We have experience navigating various regulations — from HIPAA, HITRUST, and FDA in the US to GDPR in the EU. Our team implements all the required security safeguards and can assist in preparing documentation for regulatory clearance.
While we help ensure our custom AI solutions align with regulatory requirements, compliance certification and final oversight rest with your team. Our aim as an AI development company is to develop AI that meets industry standards, incorporating security and compliance best practices from the start.
How is AI trained to ensure accuracy in diagnostics or decision-making?
The key to AI success is high-quality training data. In a medical context, this means:
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Diverse demographics and conditions to avoid bias
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Consistent image capture across devices to ensure uniform scan quality
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Expert-labeled data by domain specialists
Still, data alone doesn’t cut it. Choosing the right AI model is a game-changer.
What to do with the AI model that produces incorrect results?
If AI flags a healthy person as sick, misses a disease, or misdiagnoses, it calls for root-cause analysis.
The most common fix is AI retraining. If the dataset is biased, it should be upgraded to include more diverse medical cases. If the model is outdated, we fine-tune it with fresh data to catch evolving trends.
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