Syno provides an AI research platform that runs inside a client’s own environment, ensuring that sensitive health data never leaves the organization’s firewall. Users can pose complex research questions in natural language and receive reproducible, auditable results, eliminating the need for time‑consuming data wrangling and compliance workarounds.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers handling sensitive health data must navigate strict consent frameworks, privacy regulations, and security requirements, which prevent the use of most external AI tools. Consequently, they spend extensive time on data wrangling, IRB approvals, and manual analysis instead of focusing on scientific discovery.
Solution
Syno delivers an AI research platform that is installed as containerized micro‑services inside the customer’s own infrastructure—on‑premises, private cloud, or managed GDPR‑compliant endpoints. The platform ingests the organization’s data dictionaries, SOPs, and prior analyses, enabling it to understand domain‑specific terminology. Researchers interact via a chat interface, posing complex analytical questions in natural language. Syno automatically decomposes each query, generates executable Python code, runs the analysis securely, and returns verified results together with a full audit trail. For advanced users, isolated JupyterLab workspaces provide direct access to the reproducible analysis environment. The solution ensures that no sensitive data leaves the firewall while providing reproducible, auditable outputs that satisfy regulatory and governance constraints.
Target Audience
Primary customers are research teams at pharmaceutical, med‑tech, and academic institutions that need to analyze protected health data while complying with strict governance and privacy regulations.
Features
- Containerized deployment that runs inside the client’s environment (on‑prem, private cloud, or managed GDPR‑compliant service)
- Natural‑language query interface that translates questions into executable Python analysis code
- Automatic generation of reproducible, auditable code and execution logs for each result
- Integrated JupyterLab workspaces offering isolated, secure notebooks for power users
- Multi‑agent workflow (Data Explorer, Analysis Designer, Code Generator, Literature Agent, Report Builder) that collaborates to produce research‑grade outputs
- Built‑in compliance with GDPR, HIPAA, and EU AI Act requirements, with no data sent to external servers
- Full audit trail and versioned code ensuring traceability and reproducibility of analyses