Integrated analysis platform for Frontier Bio

IAS──이미지, 유전체, 분자, 유세포 분석, 질량분석 통합

하나의 클라우드에서 연구 데이터를 협업하고 원격 공동 연구, 재현성, 분석 효율을 높입니다.

ResearchersPharma / Bio R&DPathology / Medical researchMaterials / Semiconductor / QC

AI for Science

AI for Science implementation support is now available

We help research teams design generative AI, RAG, local LLMs, AI agents, and research data foundations with access control, human review, and department operations in mind. The service is independent from IAS and can integrate with IAS when a multimodal data foundation is useful.

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Research data

RAG/AI foundation

AI agents

Human review

Four common breaks in research workflows

Scattered data

Files sit across instruments, analysis software, and shared folders, making evidence hard to trace.

Person-dependent analysis

Preprocessing choices and thresholds are difficult to reproduce when they live with one operator.

Slow collaboration

Results, comments, and attachments move separately, so review context is easy to lose.

Heavy reporting

Teams spend time re-collecting figures, settings, and interpretation for reports.

분석 업무의 비용과 시간을 절감

연구개발, 품질관리, 진단과 검사는 다양한 데이터 형식을 사용합니다. IAS는 분야별 전용 형식을 지원하고 중앙에서 관리해 전체 워크플로를 연결합니다.

The IAS workflow

IAS does not replace modality-specific tools. It connects data by experiment so analysis, review, and reporting stay in the same context.

Connect
Organize experiment data
Link images, NGS, flow, mass-spec, molecular structure, and metadata.
Analyze
Share methods and results
Handle preprocessing, analysis steps, and visualization in one workspace.
Review
Inspect evidence together
Keep comments, comparisons, and decisions connected to the data.
Report
Prepare report outputs
Organize analysis history and figures for reports and manuscript drafts.

A dashboard view of research data

멀티모달 통합: 이미지, 유전체, 단백질, 분자, 유세포 데이터를 가로질러 분석
클라우드 협업: 기관과 거점을 넘어 안전하게 공동 연구
재현성과 효율: 표준화된 파이프라인으로 수작업 감소
신뢰와 실적: 제약사와 연구기관에서 지속적인 도입 및 검증

01Experiment

02Image / NGS / Flow

03Analysis history

04Review notes

05Report draft

Use cases by customer segment

Academic labs

Challenge: Data and analysis settings are scattered by experiment, making handover and reproducibility hard.
Use: Manage data, analysis, comments, and reports by project.

Discuss collaboration

Pharma / Bio R&D

Challenge: Teams need cross-modal evidence from images, omics, flow, and mass spectrometry.
Use: Bring candidate comparison, toxicity review, and decision evidence into one workspace.

Request a demo

Pathology / Medical research

Challenge: Images, related data, and review records need to stay aligned by case or experiment.
Use: Connect image analysis and review history for inspectable outputs.

Ask about analysis

Materials / Semiconductor / QC

Challenge: Inspection images, measurements, quality decisions, and reports are managed separately.
Use: Support cross-process analysis and report creation in one workflow.

Materials or quote