Custom Healthcare Software Development Services
DBB Software provides custom healthcare software development for teams that handle patient data: scheduling and intake, specialist directories, provider portals, patient apps, and the AI that sits alongside them.
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Six
AI builds designed or shipped for healthcare platforms
4h to 20m
deployment time on a global patient review platform
Six weeks
two engineers, the care-request API behind a production voice agent
Healthcare and Medical Software Development Services We Provide
Patient scheduling and intake
Self-scheduling flows, digital onboarding, insurance and eligibility capture, address and time-window booking, and care-request APIs that a voice agent or a web form can both call.
Specialist directories and search
Provider directories with per-tenant search indices, filtered specialist matching, review and rating systems, and natural-language search over the same ranking the platform already runs.
Provider portals and clinician tools
Clinician-facing portals for patient records and risk scores, clinician profile management, practice dashboards, and enterprise SSO with SAML 2.0 multi-tenancy.
Patient mobile apps
Healthcare app development on Flutter and React Native, with risk dashboards, push reminders, in-app education libraries, and the same backend the provider portal reads.
Healthcare platform modernisation
Decomposing monoliths into services, migrating infrastructure to AWS with Terraform, cutting deployment times, and CMS replatforming for location-aware sites.
Device and wearable data
Ingesting biometric data from wearables and smart textiles, running clinical risk algorithms against patient inputs, and returning scores and screening recommendations to both patient and clinician.
Scope Your Healthcare Build With HIPAA Considered
Describe your patients, your clinicians and the systems this has to talk to. Receive a rough scope back for free, before any calls.
Scope My Healthcare Build
AI Capabilities for Healthcare Software Development
DESIGNED
Patient-facing chatbot
Answers patient questions with a deterministic emergency check ahead of the model, and a server-side check clearing every answer before a patient reads it.
DESIGNED
After-hours voice agent
Turns missed calls into appointment requests and routes anyone showing urgency signals to emergency services, on a rule that runs ahead of the conversational model.
DESIGNED
Natural-language search over your own data
Turns a plain-language question into filters from a closed schema the model can't add to, running the ranking you already have with no new datastore.
DESIGNED
Drafting grounded in your records
Generates text only from facts already confirmed in the record, halts when a required field is missing, and leaves a named person as the only one who can publish.
DESIGNED
Discoverability in AI assistants
A read-only MCP server that lets ChatGPT, Claude and Perplexity query your directory while your data and your booking transaction stay on your own domain.
IN PRODUCTION
AI agent integration
The API layer a third-party voice or chat agent calls to do real work in your systems, built so you can swap the agent vendor without rebuilding underneath.
Guardrails for Clinical AI
Patient-facing AI carries clinical risk. We define strict boundaries for what an AI model can touch and where human oversight is required. These controls are built into a shared foundational layer, ensuring safe and predictable integrations.
Hardcoded safety checks
Emergency screenings and server-side answer verifications run as fixed code, meaning patient safety never relies on the model "behaving".
Clinician sign-off
Any emergency escalation path must pass a clinician-approved test set before it handles a real patient call.
Output based on facts
Search filters are restricted to a closed schema, and text drafts rely only on confirmed records. Generation automatically halts if required information is missing.
Strict data compliance
Patient symptoms are treated as special-category data under GDPR Article 9, which strictly governs what gets logged, retention times, and approved vendors.
Shared foundational layer
Model access, spending caps, logging rules, and WCAG 2.1 AA accessibility live in a single shared layer, so every new feature automatically inherits them instead of reinventing them.
Healthcare Projects We've Delivered
Delivering a Modern Self-Scheduling Platform for At-Home Care
Challenge:
DispatchHealth needed a digital self-scheduling and onboarding platform that would allow patients and caregivers to request urgent medical care without relying on call-center operators.
Solution:
Designed end-to-end digital scheduling flows that collect patient demographics, medical information, and insurance details with high accuracy.
Built address verification, service-area eligibility, and preferred time-window selection into a seamless onboarding experience.
Integrated all collected data directly into the backend to support triage, dispatch, and operational workflows.
Provided ongoing engineering support to evolve the platform with new scheduling, insurance, and clinical features.
Result:
Enabled a shift from phone-based scheduling to digital self-service, reducing call-center load while improving data completeness, patient satisfaction, and operational efficiency.
Building the Care-Request API Behind an AI Voice Intake Agent
Challenge:
An at-home urgent care provider moved to a voice-AI intake agent and needed the care-request layer beneath it to serve a new vendor without a rebuild.
Solution:
Built one endpoint per step of the call, from demographics through scheduling.
Served risk protocols from complaint keywords while the call was still open.
Gated the API with Auth0 credentials and an allowlist of the caller's addresses.
Kept the intake layer vendor-agnostic, so a second IVR vendor plugged into the same API.
Result:
Patients are empowered to create a visit without a dispatcher, a second vendor onboarded onto the same contract, completed in six weeks with two back-end engineers.
Implementing a Location-Aware Patient Landing Experience with Brightspot CMS
Challenge:
DispatchHealth needed a flexible, CMS-driven patient landing site that could serve as the primary entry point for care requests.
Solution:
Implemented Brightspot CMS as the foundation for the patient landing experience.
Built a custom Brightspot widget to integrate CMS-managed content with real-time platform logic.
Enabled location-aware content and service availability without custom frontend deployments.
Ensured workflow-accurate routing based on patient and requester context.
Result:
Delivered a unified, CMS-driven entry point that adapts by location, routes patients into the correct care flows, and empowers internal teams to manage content independently.
Automating End-to-End Delivery and Quality Workflows in a Healthcare Platform
Challenge:
DispatchHealth needed to reduce manual operational work, improve software quality, and safely increase release frequency across patient-facing and internal systems.
Solution:
Implemented fully automated continuous deployment pipelines to replace manual weekly releases.
Introduced end-to-end test automation with Cypress to validate complete user workflows.
Improved logging and observability to detect issues earlier and simplify production debugging.
Streamlined engineering operations to support sustainable on-call rotations..
Result:
Enabled daily automated deployments, reduced critical production incidents, and improved platform reliability.
Standardizing Serverless Front-End Delivery for Healthcare Platform
Challenge:
DispatchHealth needed a consistent, secure, and scalable way to deliver front-end applications across its growing digital ecosystem.
Solution:
Designed a standardized serverless front-end delivery pattern using CloudFront, S3, and AWS Lambda.
Centralized edge-level security controls, including CSP enforcement and request handling.
Enabled global content delivery through CloudFront caching for high performance and reliability.
Rolled out the shared infrastructure model across multiple production applications.
Result:
Established a reusable, security-first front-end delivery standard adopted across applications, improving maintainability, global performance, and operational efficiency with no added hosting or deployment costs.
Modernizing a Healthcare Platform by Migrating a Monolith to Microservices
Challenge:
DispatchHealth needed to break down its growing Ruby on Rails monolith, which powered mission-critical patient onboarding, insurance logic, and clinical workflows.
Solution:
Designed a long-term migration roadmap and identified high-load features to extract first.
Developed 17 Golang microservices covering patient data, insurance payers, risk stratification, partner-specific rules, and operational logic.
Introduced gRPC for fast, reliable service-to-service communication across clinical workflows.
Implemented a dedicated authorization service and improved system maintainability through clearer service ownership.
Result:
Significantly reduced dependency on the monolith, improved performance across key patient flows, enabled faster inter-service communication, and increased long-term scalability and maintainability for mission-critical healthcare operations.
Creating a Cross-Platform App for Biometric Data Collection
Challenge:
A Canadian smart textile company required a cross-platform app to complement its smart attires that collect users’ body data and analyze it.
Solution:
Developed a cross-platform app to support smart garments.
Added seamless BLE connectivity between the app and garments.
Implemented complex health indicators analysis.
Developed an algorithm for processing and structuring data into insights.
Result:
Created a feature-rich cross-platform app that analyzes health data gathered by smart garments and provides users with useful insights.
Designing a Free AI Reputation Report
Challenge:
Clinicians could not see their own online presence, and the platform had nothing to offer a prospect before a sales conversation started.
Solution:
Reads what AI assistants say about a doctor, not only where they rank
Scores five separate dimensions, then ranks what to fix first
Proceeds on public data alone when the identity match is unclear
Caps what each free report may spend on outside services
Result:
5 scored dimensions, 3 degradation paths with defined behavior, and a spend ceiling on every free report.
Designing an AI Receptionist With Emergency Escalation
Challenge:
A private practice closes at six and the phone keeps ringing. Every unanswered call is a patient handed to whoever picks up first.
Solution:
Specified emergency escalation as a release gate that has to clear a clinician-signed test set
Scoped a bought voice engine and a built platform integration, in that order
Designed a completed call to land as an appointment request in the dashboard staff already use
Specified a route to a human or voicemail behind every failure
Result:
0 dead ends, 1 clinical sign-off gate, 3 defined call outcomes.
AI Bio Writer Grounded in Confirmed Facts
Challenge:
Most clinicians leave their profile bio blank, and the writing was landing on the platform's own team instead.
Solution:
Specified grounding in facts the clinician confirms first, with a missing field halting generation
Specified sanitization of open-web research before it reaches the model
Removed every path that publishes without the clinician doing it
Specified what happens when the research, the model or the flow itself fails
Result:
0 automatic publishing paths, 4-question intake, 1 adoption bar.
Designing an MCP Server for AI Assistant Discovery
Challenge:
A global healthcare review platform needed AI assistants to query its verified specialist directory, without handing over the review corpus.
Solution:
Specified a stateless read service on the platform's existing read layer, with no new datastore
Specified nine read-only tools as a contract, with no language model inside the server
Fixed the data-exposure line in code, enforced by property-tested response mappers
Specified an internal-first rollout behind a named security gate with five signed exit criteria
Result:
One AI layer for every product, layered security before public exposure, the review corpus as an owned asset.
Implementing Enterprise SSO Integration for a Healthcare Platform
Challenge:
A healthcare platform needed to implement enterprise-grade single sign-on to meet a major client's security requirements and enable seamless user authentication.
Solution:
Implemented SAML 2.0 authentication with OneLogin integration.
Built Just-In-Time Provisioning for automatic user account creation.
Developed security-first session management to prevent hijacking.
Created environment-agnostic testing tools for QA without live data.
Result:
Delivered in under 1 month, multi-tenant architecture enabling new SSO clients in hours, and enterprise security compliance.
Developing Mobile Apps for Patients and Healthcare Providers
Challenge:
A healthcare review platform needed mobile apps to make it easier for patients to submit reviews and for doctors to manage their online presence.
Solution:
Built a React Native patient review app with push notifications and kiosk mode
Developed an Expo-based provider app with dashboard access and file sharing
Implemented automated deployment pipelines for faster releases
Continuously integrated new web platform features into both apps
Result:
Increased provider engagement, streamlined on-site review collection, and unified mobile experience across iOS and Android.
Modernizing Cloud Infrastructure for a Global Healthcare Platform
Challenge:
A healthcare platform needed robust cloud infrastructure to support global expansion and enable faster, more reliable deployments.
Solution:
Migrated monolithic application to microservices across AWS and GCP
Implemented GitLab CI/CD for fully automated deployments
Codified all infrastructure using Terraform for consistency and compliance
Established AWS Organizations for improved security boundaries
Result:
92% reduction in deployment time (4 hours to 20 minutes), global infrastructure supporting 6 countries, and complete infrastructure as code coverage for improved compliance.
Building a Global Healthcare Search Platform with Intelligent Specialist Matching
Challenge:
A healthcare review platform needed to transform from a single-country website into a scalable global solution supporting multiple markets.
Solution:
Refactored legacy platform into microservices architecture
Built intelligent search algorithms for specialist matching
Developed cloud infrastructure for multi-country operations
Enabled verified patient review collection across regions
Result:
150% increase in user base, 30% improvement in patient satisfaction rate, 80% fewer fraudulent reviews achieved, expanded to 6 countries, and reduced new market onboarding to one day.
Conducting a Compliance Discovery for a MedTech Company
Challenge:
A medtech company needed to prove that its platform could securely store and process sensitive patient data. Before scaling, they required a full HIPAA/GDPR readiness assessment.
Solution:
Reviewed AWS infrastructure, IAM roles, VPC setup, encryption, backups, and access policies.
Documented risks and delivered a remediation plan and compliance roadmap.
Connected the client with certified HIPAA/GDPR auditors and training partners.
Advised on privacy policies, data access, audit requirements, and PHI-handling best practices.
Result:
Delivered a complete compliance readiness roadmap, identified key AWS vulnerabilities, and aligned the client with certified auditors to accelerate HIPAA/GDPR certification.
Building a Diabetic Retinopathy Care Platform with Mobile App and Provider Portal
Challenge:
A health-tech company needed to bring its clinically validated retinopathy risk algorithm to patients on mobile and to clinicians on the web, with a single team supporting both surfaces.
Solution:
Built a Flutter patient app for iOS and Android with risk visualizations and screening reminders.
Developed a web provider portal for clinicians to manage patient records and risk scores.
Implemented a shared serverless backend on AWS Lambda, RDS, S3, and Cognito.
Set up three isolated environments (dev, staging, production) on the Serverless Framework.
Result:
A single Flutter codebase shipped to both app stores, one shared backend powering both patient and provider surfaces, and three isolated AWS environments managed by a one-person backend team.
Designing a Self-Hosted Patient Chatbot With Server-Enforced Safety
Challenge:
A healthcare platform had a third-party chat window on its homepage that patients were typing health information into, with no emergency handling.
Solution:
Specified a deterministic emergency gate over the rolling conversation window, ahead of any model call
Specified server-side validation of every answer, inside a two-second first-token budget
Reused the shared tool layer and the enquiry and booking flows already in production
Wrote down every store a conversation touches, so an erasure request completes
Result:
Guardrails owned by the client, patient health data held in-house, a calculable worst-case bill.
Designing a Hallucination-Resistant Search Mode for a Healthcare Platform
Challenge:
A healthcare marketplace wanted patients to search in their own words, using the search and infrastructure it already ran.
Solution:
Specified one model call, isolated from the patient-facing application, over the unchanged search path
Constrained the model to a closed schema, with the fields it must not set never shown to it
Gated translation accuracy in continuous integration against a versioned labeled set
Specified an experiment whose decision rule, guardrails and kill switch were written first
Result:
A search upgrade without new infrastructure, health data at the Article 9 standard, a decision, not a feature.
Testimonials
"Their level of engagement and collaboration on each project are impressive. The engagement has reduced call center costs and increased overall consumer growth"
Name withheld under NDA
Product Manager, DispatchHealth
"They managed the project well. DBB Software managed the entire project seamlessly and worked efficiently without sacrificing any quality of their outputs."
Name withheld under NDA
Scrum Master, Textile Computing Solutions Company
"The team exhibited excellent ownership and judgment. Delivered fast, accurate work, and made good judgment calls when there was ambiguity."
Name withheld under NDA
Executive, Enchart Inc.
“DBB Software delivered the first version in record time. The team continues to work on the website with a sense of ownership and pride in their work.”
Alex Shyba
CTO, Uniform
"Impressive what they have managed to make in such a small time, also suggesting new ways to implement, or new technologies we should be aware of.”
Peder Søholt
CTO & Co-Founder, Plaace
How We Deliver
DBB pairs senior healthcare engineers with AI agents and milestone-based delivery, so scope, progress and ownership stay clear from the first call to production.
Understand the Outcome
We map your business goal, your patients and clinicians, the clinical workflow at the centre of the product, the systems it has to talk to, and your compliance obligations, then recommend the path that fits them.
Define the Right Engagement
Depending on your needs, we propose a focused MVP that validates a clinical or patient product with real users, integration of a new application with the EHR and clinical systems you already run, or a dedicated long-term team embedded in your engineering organization. You receive a clear delivery plan with scope, milestones, responsibilities, timeline, and budget.
Design the Solution
Our senior engineers define the architecture, PHI data flows, HL7, FHIR, and DICOM integrations, encryption, access controls, audit logging, HIPAA and GDPR requirements, and the deployment approach. Where AI is involved, we also define model strategy, clinical evaluation, human oversight, and fallback logic.
Build in Milestones
We deliver working functionality in short, visible milestones, with compliance built into each release. Our engineers use specialized AI agents across planning, development, testing, and documentation, while remaining accountable for architecture, patient data protection, security, and final decisions.
Validate, Launch, and Evolve
We test functionality, interoperability with clinical systems, performance, security, and HIPAA controls before release. After launch, we support deployment, data migration, user training, monitoring, and further product development.
Have a patient app, a clinical platform, or an EHR integration to build?
Tell us what you are trying to achieve. We will help you determine the right technical and delivery approach.
Mina Morkos
Business Development Manager
Discuss Your Project
Why Choose Us for Healthcare Software Development
100+
Skilled
Professionals
We deliver premier healthcare software development services and build the AI that delivers results. Our team follows best practices, and you own the code from the first commit.
Long-Term Partnerships & Support
With 80% of clients staying 7+ years and our team collaborating for over 5 years, we ensure dedicated long-term support.
ISO 27001 Certified
ISO/IEC 27001 certified, with CMMI and ISO standards in the delivery process.
Milestone-Driven Delivery
Scope, milestones, timeline and budget agreed before we start, with working functionality at each checkpoint.
FAQ
Let's Talk About Your Healthcare Project
"Tell us about your current situation: what you're building, which clinical systems you work with, and what's not working.
Whether you need a telemedicine app, an EHR integration, or a biotech research platform, we'll get back to you within one business day with an honest assessment and, if it's a good fit, an initial cost estimate."
Mina Morkos
Business Development Manager