On-Premise Bioinformatics Platform

Deploy VigyanLLM on your own hardware: Docker Compose on Ubuntu 22.04 LTS, air-gapped and offline capable, zero data egress, LDAP authentication, and unlimited local runs.

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VigyanLLM can run entirely on your own infrastructure with no external API calls. Choose on-premise deployment when you need to keep genomic and clinical data inside your controlled network, work offline, or eliminate per-query cloud costs.

Why Self-Host Bioinformatics?

Cloud-based bioinformatics tools send your sequence data to third-party servers, bill per query, and disconnect you during outages. A self-hosted bioinformatics or on-premise AI setup keeps data, compute, and control inside your organization. For labs handling sensitive genomic data, clinical diagnostics, or proprietary workflows, on-premise deployment removes the two biggest concerns: data egress and per-run metering.

Deployment via Docker Compose

VigyanLLM ships as containers that deploy with a single command. The reference deployment target is Ubuntu 22.04 LTS with Docker Compose, and CUDA is supported for GPU-accelerated modules such as structural docking. Once the stack is up, all tools 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.

Air-Gapped and Offline Operation

VigyanLLM is air-gapped capable: after the initial image load, it can run with the network disconnected. This is essential for classified or restricted environments, isolated research networks, and institutions with strict cybersecurity policies. Because there are no external API calls, the platform continues to function fully offline — no cloud dependency, no internet required.

Who Should Use On-Premise?

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.

On-premise deployments include LDAP integration for single sign-on with institutional directories, unlimited internal runs with no per-query costs, and dedicated support with SLA-backed SLAs.

Frequently Asked Questions: On-Premise Bioinformatics

Does VigyanLLM work offline?

Yes. In on-premise deployment, VigyanLLM is air-gapped capable and runs with no internet connection. All tools execute locally after the container images are loaded, so it continues to work autonomously offline.

Can I self-host VigyanLLM on my own server?

Yes. VigyanLLM deploys via Docker Compose on Ubuntu 22.04 LTS (Linux). Your institution can run the full suite of sequence, primer, and docking tools on your own hardware with no data egress.

What are the system requirements for on-premise deployment?

The reference platform is Ubuntu 22.04 LTS with Docker Compose. GPU acceleration (CUDA) is optional and recommended for docking workloads. Contact our team for a sizing guide tailored to your workflows.

How is on-premise different from the cloud version?

On-premise runs entirely on your infrastructure with zero external API calls, unlimited local runs, and no per-query cost. It is ideal for sensitive or offline workloads, whereas the hosted version trades convenience for managed infrastructure.