On-Premises Deployment — On Our Roadmap
Talk to Our Team →Today VigyanLLM runs in your browser and on our hosted servers. This page describes the planned self-hosted option for institutions that need to keep genomic data inside their own network, work offline, or run on their own compute — it is on our roadmap and not yet available.
Why Labs Ask for Self-Hosting
Some institutions cannot send sequence data to servers outside their own network: they handle sensitive genomic data, clinical diagnostics, or proprietary workflows and need to control data egress and per-run costs themselves. A self-hosted bioinformatics setup keeps data, compute, and control inside your organization — that is exactly the option we are building. Until it ships, the hosted service processes data as described in our Privacy policy.
Planned: Deployment via Docker Compose
VigyanLLM is intended to ship as containers that deploy with a single command. The planned reference deployment target is Ubuntu 22.04 LTS with Docker Compose, with CUDA for GPU-accelerated modules such as structural docking. This is roadmap scope — not available today. Once the stack is up, all tools would run locally:
- Primer design using Primer3 and SantaLucia thermodynamics.
- PCR analysis and in silico PCR.
- BLAST and MSA for sequence comparison.
- Docking with AutoDock Vina and GNINA on local GPU.
Planned: Air-Gapped and Offline Operation
Air-gapped operation is a goal of the on-premises roadmap: after the initial image load, the stack is intended to run with the network disconnected — for restricted environments, isolated research networks, and institutions with strict cybersecurity policies. The hosted service you use today requires an internet connection.
Who Is the Planned On-Premises Option For?
Clinical & Diagnostics Labs
Patient-linked or regulated genomic data that must not leave the lab network.
Government Research Bodies
Institutions requiring air-gapped, self-hosted tools with auditability and local infrastructure.
Biotech & Pharma
Proprietary compound libraries and pipelines deployed on private servers.
Remote / Offline Facilities
Field laboratories or low-connectivity sites that need reliable local tools.
Planned on-premises deployments are intended to include LDAP integration for single sign-on with institutional directories, unlimited internal runs, and dedicated support — final details will be confirmed when the option ships.
Frequently Asked Questions: On-Premises Deployment
Does VigyanLLM work offline?
The hosted VigyanLLM needs a browser connection. An offline, air-gapped deployment is on our roadmap and not available yet.
Can I self-host VigyanLLM on my own server?
Not yet. Self-hosting via Docker Compose on Ubuntu 22.04 LTS is on our roadmap with no committed date. Today VigyanLLM runs in your browser and on our hosted servers.
What are the system requirements for on-premise deployment?
On-premise deployment is not available yet, so there are no final requirements. The planned reference target is Ubuntu 22.04 LTS with Docker Compose, with GPU acceleration (CUDA) recommended for docking workloads. Contact our team to discuss your environment.
How is on-premise different from the hosted version?
On-premise is not available yet — it is on our roadmap. The hosted service runs in your browser and on our servers; a future self-hosted option would run entirely on your infrastructure with unlimited local runs and no per-query cost.
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