
Hospitals generate massive volumes of unstructured data — clinical notes, lab results, prescriptions, and compliance reports.
MediSumm’s key challenges included:
Manual documentation leading to delays and human errors
Compliance reporting inefficiencies across departments
High administrative overhead for medical staff
Limited visibility into quality-of-care metrics
They sought a solution to automate clinical documentation, ensure compliance consistency, and empower doctors with AI-generated, data-grounded summaries.
Manexa AI Labs designed MediSumm AI, a secure, multi-agent ecosystem that transforms raw medical data into structured, compliant documentation — leveraging RAG pipelines and enterprise-grade AI orchestration.
Clinical Data Extraction Agent
Parses EHR (Electronic Health Record) inputs, identifying diagnoses, treatments, and test results.
Built with LlamaIndex and LangChain for contextual retrieval.
Medical Summary Agent
Uses OpenAI GPT and Anthropic Claude models to generate concise, human-readable medical summaries — ensuring clarity without losing medical precision.
Compliance Verification Agent
Validates generated content against hospital-specific protocols and healthcare regulations (HIPAA, NABH).
Reporting & Analytics Engine
Provides administrators real-time insights into document completion rates, compliance accuracy, and departmental workloads.
LangGraph for multi-agent workflow orchestration
LlamaIndex for retrieval from EHR and lab databases
OpenAI GPT-4 for natural language generation and summary construction
Anthropic Claude for safe, transparent validation
Multi-tenant Cloud Infrastructure for enterprise-scale deployment
Role-based access control (RBAC) for secure collaboration
Discovery & Workflow Mapping — Understanding MediSumm’s documentation lifecycle and compliance structure.
Custom AI Architecture Design — Developing agents for each stage of the medical reporting process.
Integration with EHR Systems — Real-time API integration with hospital data.
Deployment & Training — Pilot rollout across three departments (cardiology, internal medicine, and pathology).
Continuous Optimization — Ongoing fine-tuning of RAG prompts and compliance rules.
Results & Outcomes
| KPI | Before AI Deployment | After MediSumm AI |
|---|---|---|
| Report preparation time | 25–30 mins | Under 6 mins |
| Compliance accuracy | 82% | 99.1% |
| Documentation backlog | 3–4 days | Same-day completion |
| Staff workload | High manual entry | Reduced by 55% |
Operational Impact
Reduced administrative burden for doctors and nurses.
Standardized reporting formats across multiple branches.
Real-time compliance alerts and version-controlled document trails.
Improved audit readiness and patient data governance.
This project demonstrates Manexa AI Labs’ enterprise AI capabilities in healthcare — merging multi-agent orchestration, data governance, and AI compliance validation.
Agentic Collaboration: Multiple AI agents coordinate tasks like extraction, summarization, and verification.
Grounded Intelligence: RAG ensures outputs are based on real hospital data — not generic responses.
Scalable Architecture: Designed for deployment across multiple hospital branches with multi-tenant support.
Human-AI Partnership: Doctors stay in control — reviewing AI suggestions before finalizing records.
Through MediSumm AI, Manexa AI Labs showcased how Agentic AI systems can transform traditional healthcare operations — making clinical reporting faster, safer, and smarter.
This solution set a benchmark for how AI can augment medical professionals, ensuring compliance while freeing up time for patient care.
“From documentation to decision-making — Manexa AI Labs is redefining how healthcare institutions harness AI for operational excellence.”