Frequently Asked Questions

Dashamlav AI Labs develops AI-powered workflow automation tools specifically for oncology practices. Our platform—designed by practicing oncologists—uses advanced algorithms, real-world data (RWD), and patient-reported outcome measures (PROMs) to generate real-world evidence (RWE) that supports clinical decisions, automates documentation, and enables research.

We’re built by oncologists who lived these problems. Our founders are practicing radiation oncologists with 70+ combined years of clinical experience who designed every feature to address real workflow pain points. We focus on oncology-specific solutions—not generic healthcare AI—with deep integration of clinical guidelines, TNM staging automation, and research-grade data capture.

Integration is straightforward. Our team provides comprehensive onboarding support including data migration assistance, staff training, and workflow customization. We work with your existing EMR systems and can be operational within weeks. Whether you’re optimizing workflows, automating documentation, or enabling research capabilities, we tailor the implementation to your specific needs.

Our platform is used by oncologists, radiation oncology departments, cancer centers, and healthcare institutions across India, ASEAN, and MENA regions. Individual oncologists use it for daily efficiency gains, while research-focused practitioners leverage it for real-world evidence generation and clinical studies.

OncFlow: AI based oncology workflow platform with automated TNM staging, case summaries, and clinical decision support that understands complete patient context and suggests evidence-based treatment plans.

PulseDash: Patient-facing mobile app for radiation therapy symptom reporting and care team communication.

MedCompass: Team coordination tool for real-time status updates and workflow synchronization.

OncoFlow R+: AI enabled research along with comprehensive oncology workflow platform

We leverage generative AI and natural language processing (NLP) to comprehend clinical documents, extract insights from evidence-based outcomes, and interpret published guidelines. Our proprietary RULES pipeline grounds every AI recommendation in peer-reviewed literature and clinical evidence—not generic training data. We employ rigorous red teaming methodologies to validate AI-generated recommendations against established oncology standards, ensuring clinical accuracy before deployment. Unlike generic AI tools that provide general suggestions, our models are specifically trained on oncology workflows, staging systems, and treatment protocols to deliver patient-specific, evidence-backed clinical decision support.

Yes. We understand every healthcare environment has unique workflows and requirements. Our platform is highly configurable for hospitals, clinics, research institutions, and telemedicine providers. We customize staging templates, reporting formats, clinical guideline references, and workflow automations to match your specific practice patterns.

ChatGPT provides generic answers like “What treats lung cancer?” OncFlow answers patient-specific questions like “What’s the evidence-based plan for this patient with Stage IIIB EGFR+ adenocarcinoma, given their comorbidities, prior treatments, and current performance status?” The difference is complete patient context combined with clinical evidence grounding through our RULES pipeline.

Yes. We follow HIPAA guidelines to protect Personal Health Information (PHI). Our platform implements required administrative, physical, and technical safeguards including access controls, audit logging, encryption in transit and at rest, and secure authentication. We sign Business Associate Agreements (BAAs) with all healthcare clients and conduct regular compliance audits.

Patient data security is our highest priority. We employ:

• Encryption: AES-256 encryption for data at rest, TLS 1.3 for data in transit
• Access Controls: Role-based access control (RBAC) with multi-factor authentication
• Audit Trails: Comprehensive logging of all data access and modifications
• Network Security: Firewalls, intrusion detection, and DDoS protection
• Infrastructure: CloudHD hosted on enterprise-grade cloud infrastructure with SOC 2 compliance

CloudHD is our secure cloud infrastructure platform that meets global standards for data protection, privacy, business continuity, and disaster recovery. It provides enterprise-grade security with 99.9% uptime SLA, automated backups, geographic redundancy, and compliance with international data protection regulations including GDPR and local healthcare data laws.

Only authorized healthcare personnel within your organization have access to patient data, controlled through role-based permissions you configure. Dashamlav engineers do not have access to patient data in production environments. Any access for support purposes requires explicit authorization and is fully logged. We never use patient data for AI model training without explicit de-identification and consent.

We are actively pursuing CDSCO (Central Drugs Standard Control Organisation) approval in India as Software as a Medical Device (SaMD). Our platform design follows ISO 13485:2016 quality management standards. We maintain compliance with applicable healthcare data regulations in all markets we serve. Contact us for current certification status and roadmap.

We maintain a comprehensive incident response plan that includes immediate containment, forensic investigation, affected party notification within required timeframes, and remediation. All potential security incidents are logged and investigated. We conduct regular security assessments and penetration testing to identify and address vulnerabilities before they can be exploited.

Typical implementation ranges from 2-6 weeks depending on practice size and customization requirements. This includes data migration, system configuration, staff training, and workflow optimization. We provide dedicated implementation support and can accelerate timelines for urgent deployments.

We offer comprehensive ongoing support including technical troubleshooting, software updates, user training, workflow optimization consulting, and feature enhancement requests. Support is available via email, phone, and chat with priority response times for critical issues. We also provide regular training sessions for new staff and feature releases.

Yes. We provide comprehensive training during implementation and ongoing training as needed. Training is tailored by role—oncologists receive clinical workflow training while administrative staff learn documentation and reporting features. We offer both on-site and remote training options with recorded sessions for reference.

Contact us through our website or email to schedule an initial consultation. We’ll discuss your specific needs, demonstrate relevant features, and develop a customized implementation plan. Most practices start with a pilot program in one department before organization-wide deployment.

By automating time-consuming documentation tasks, we free oncologists to spend more time on clinical decision-making and patient care. Our AI-powered clinical decision support reduces oversights, ensures guideline adherence, and enables earlier intervention for treatment complications through PulseDash symptom monitoring. Research capabilities help practices continuously improve protocols based on their own outcomes data.

Users report significant time savings: automated TNM staging reduces case preparation from 30 minutes to under 5 minutes, AI-generated summaries eliminate hours of documentation weekly, and real-time team coordination through MedCompass reduces treatment delays. One oncologist reported reviewing 12 cases per hour (up from 5) after OncFlow automated staging and guideline retrieval.

Absolutely. Our platform captures oncology data at research-grade granularity, enabling retrospective studies, real-world evidence generation, and outcomes analysis without additional data entry. PulseDash contributes patient-reported outcomes data, and OncAnalytics provides query tools for complex research questions. Many users publish studies using data captured through routine clinical workflows.