Mergic / Platform Capabilities
From raw DICOM and FASTQ to governed clinical decisions, Mergic unifies the entire precision-medicine data lifecycle on GPU-native infrastructure. Five capability layers, one control plane.
Data Ingestion
Zero-copy streaming from scanners, sequencers, and EHRs with consent enforcement at the point of entry.
Ingest DICOM, WSI (SVS, NDPI, MRXS), FASTQ, BAM, CRAM, VCF, HL7v2, FHIR R4, PDF, and structured CSV/Parquet natively. No brittle ETL pipelines, no manual conversions. Custom parsers can be added via the plugin SDK for proprietary instrument formats.
mergic ingest --source /scanner/output --format auto --consent-policy strict
Stream data from scanners, sequencers, and EHRs as it arrives with zero-copy ingestion and automatic format detection.
Enforce patient consent policies at the point of entry. Automatically tag, route, and restrict data by governance rules before any processing begins.
50+
<5s
Supported: DICOM, WSI, FASTQ, BAM CRAM, VCF, HL7v2, FHIR R4, PDF CSV, Parquet, Custom SDK plugins
Content-hash-based deduplication prevents duplicate studies from entering the pipeline, saving storage and compute.
GPU Modeling
Scale across multi-node DGX clusters with automatic sharding, mixed precision, and real-time inference.
Scale across multi-node DGX clusters with automatic sharding, mixed precision, and checkpointing for imaging, genomics, and multimodal foundation models. Automatic kernel selection and memory optimization.
cluster: dgx-h100-8x | sharding: auto | precision: bf16
Serve models with TensorRT and Triton-backed endpoints for sub-second clinical decision support across imaging, genomics, and text modalities.
Leverage BioNeMo for GPU-accelerated molecular docking, protein folding, and de novo compound design with native SMILES and PDB support.
20x
<1h
300ms
Automatically scale GPU resources based on queue depth and priority. Burst to cloud GPUs when on-prem capacity is exceeded.
Version, compare, and deploy models from a unified registry with built-in A/B testing and canary deployment patterns.
Agentic Reasoning
Synthesize findings from imaging, genomics, and clinical notes into grounded narrative summaries.
Synthesize findings from imaging, genomics, and clinical notes into grounded narrative summaries with inline evidence citations, confidence scores, and provenance links. Every conclusion is traceable to source data.
confidence: 0.94 | evidence_links: 7 | modalities: imaging+genomics+clinical
Configurable rules route urgent findings to specialists while low-risk cases flow through automated review paths.
Embed mandatory human approval checkpoints before any AI-generated recommendation reaches a patient record.
Prioritize case queues by acuity, complexity, and available specialist bandwidth with dynamic re-ranking.
Generate HL7 and FHIR-compliant structured outputs ready for downstream EHR integration.
3x
94%
Governance
Every data access, model inference, and human decision is logged to an append-only ledger with cryptographic integrity.
Every data access, model inference, and human decision is logged to an append-only ledger with cryptographic integrity verification and tamper-evident seals. Full chain of custody from raw input to clinical output.
Built-in controls for BAA-ready deployments with encryption at rest, in transit, and in compute. SOC 2 Type II certified.
Automated PHI stripping across imaging metadata, genomic headers, and clinical text using NLP and rule-based methods.
Fine-grained RBAC with attribute-based policies for data, models, and inference endpoints.
Version, validate, promote, and retire models with full lineage tracking from training data to production.
100%
0
SOC 2 Type II, HIPAA BAA, GDPR, HITRUST, and FDA 21 CFR Part 11 aligned. Annual third-party pen testing included.
policy: consent_required = true audit: append_only = true crypto: integrity_check = sha256 retention: configurable per-org
Deployment
From cloud to air-gapped DGX, Mergic meets your data where it lives.
Full Mergic stack runs on NVIDIA DGX systems within your data center. All patient data and model weights stay inside your physical perimeter. Supports fully air-gapped installations with offline updates.
Deploy on GPU-optimized instances with managed Kubernetes orchestration and auto-scaling across regions.
Dedicated single-tenant environments with network-level isolation and customer-managed encryption keys.
Split workloads across on-prem inference and cloud training with secure data synchronization.
Fully offline operation with local container registries and no external network dependencies.
99.95%
Integrations
Native bidirectional connectors for PACS, LIS, EHR, and the full NVIDIA microservice ecosystem.
Native connectors to major PACS vendors, laboratory information systems, and EHR platforms including Epic, Cerner, and MEDITECH. Bidirectional data flow supports both ingestion and result push-back using DICOMweb, FHIR, and HL7v2 protocols.
protocols: DICOMweb | FHIR R4 | HL7v2 ADT/ORU | gRPC | REST
Clara, MONAI, Parabricks, BioNeMo, NeMo, and NIM inference microservices integrated natively.
Connect to S3, Azure Blob, GCS, MinIO, and Hadoop-compatible file systems for bulk data access.
RESTful and gRPC APIs for every platform capability with OpenAPI specs and SDK support in Python, Go, and TypeScript.
Real-time event notifications for pipeline completions, model alerts, and governance triggers.
50+
6
Workflow
NVIDIA Native
Not a wrapper. Mergic is engineered from the ground up on NVIDIA GPU frameworks for maximum throughput.
Every Mergic pipeline kernel is optimized for NVIDIA silicon. From CUDA-accelerated image preprocessing to TensorRT-compiled inference graphs, performance is native, not emulated through abstraction layers.
Medical imaging AI with pre-trained models for radiology and pathology segmentation, detection, and classification.
GPU-accelerated genomics for variant calling, alignment, and secondary analysis. 30x genomes in under 30 minutes.
Molecular generation, protein folding, and drug discovery with GPU-native generative models.
Large language model inference and fine-tuning for clinical NLP, report generation, and agentic reasoning.
Compiled inference serving with dynamic batching, model ensembles, and sub-100ms latency guarantees.
Market context
$20B+
~40%
<1h
1,000+
6
5
Why Mergic
Most platforms solve one piece of the puzzle. Mergic is the only multimodal AI platform that unifies all biomedical data types, accelerates them with NVIDIA GPUs, and governs the full lifecycle from a single control plane. No more stitching point solutions together.
Join imaging, genomics, and clinical data into shared patient embeddings. No more siloed tools for siloed modalities.
GPU-native from ingestion to inference. What took overnight runs on CPU now completes within a clinical shift.
Immutable audit trails, RBAC, de-identification, and model lifecycle controls satisfy the most demanding compliance requirements.
On-prem DGX, cloud VPC, hybrid, or air-gapped. Your data stays where your policies demand.
What teams say
"Mergic gave us the cross-modal layer we couldn't build alone. Imaging plus genomics in one governed view changed how our tumor board operates."
"We went from 18-hour variant calling to under 50 minutes. The clinical team now gets results same-shift."
"The governance layer made our compliance team comfortable with AI in production for the first time."
Integration guide
A structured onboarding path that connects your PACS, LIS, EHR, and GPU infrastructure without custom adapters or multi-month integration projects.
Day 1 — Connect your data sources using pre-built DICOM, FHIR, and genomics connectors. Day 3 — Configure governance policies and consent rules. Day 7 — Validate inference pipelines on representative samples. Day 14 — Go live with full audit trails, role-based access, and human signoff workflows.
day_1: connect | day_3: govern | day_7: validate | day_14: go_live
50+ connectors for PACS, LIS, EHR, sequencers, cloud stores, and NVIDIA microservices — no custom code required.
A solutions architect and integration engineer are assigned to your deployment from day one through go-live.
14
50+
Full API specs, SDK examples, and sandbox environments for every platform capability. Test before you deploy.
FAQ
Technical answers for engineering, clinical, and compliance teams evaluating the platform.
Mergic natively ingests DICOM, WSI (SVS, NDPI, MRXS), FASTQ, BAM, CRAM, VCF, HL7v2, FHIR R4, PDF, and structured CSV/Parquet. Custom parsers can be added via the plugin SDK for proprietary instrument formats.
Mergic supports NVIDIA A100, H100, and DGX systems for training workloads. Inference can run on T4, L4, A10G, and above. The platform automatically detects available hardware and optimizes kernel selection accordingly.
Every AI-generated finding includes a calibrated confidence score and evidence provenance links. When confidence falls below configurable thresholds, the system automatically escalates to human review rather than propagating uncertain conclusions.
Mergic maintains SOC 2 Type II certification, supports HIPAA BAA execution, and provides controls aligned with GDPR, HITRUST, and FDA 21 CFR Part 11. Annual third-party penetration testing and continuous compliance monitoring are included.
Yes. The on-prem DGX deployment option supports fully air-gapped installations with offline model updates, local container registries, and no external network dependencies for inference or governance operations.
Connectors support both read and write operations. Results and AI-generated annotations can be pushed back into PACS, EHR, and LIS systems using DICOMweb, FHIR, and HL7v2 with conflict resolution and deduplication.
Ready to see it in action?
Choose a clinical, genomic, or R&D use case. Mergic will demonstrate the full pipeline from ingestion to governed output on your data.