Q-omics · For Enterprise & Pharma
For pharma and biotech teams that want Q-omics's multi-omics MetaDB and Bio-LDM engine running inside their own discovery pipeline, not just in a browser tab. Every engagement starts small and de-risked, then scales toward the integration and deployment model that fits how your team already works.
Enterprise engagements are modular. Take the pieces that fit your pipeline, and leave the ones that don't.
Seamlessly integrate the Bio-LDM engine into your internal AI-driven drug discovery pipelines. Bio-LDM doesn't analyze raw omics data directly — it first structures gene, drug, and phenotype relationships into a knowledge graph validated across our 30B+ data-point MetaDB, then learns from that graph. That's what lets it surface relationships a standard analysis would miss, not just confirm the ones already known — the same engine already runs live inside Q-omics 3's AI interpretation today.
See the two integration paths →Run Q-omics fully inside your own VPC or on-premises environment, packaged as a Docker image and isolated behind your firewall. Your data, your queries, and your results stay inside your network — Q-omics's infrastructure never sees any of it.
See the full security model →Tailored analysis workflows and interface customization, built around how your team already works.
Collaborate with our experts to fuse your proprietary data with our 30B+ data-point MetaDB for instant, de-risked target validation.
See what's in the MetaDB →Your systems call the Q-omics API over an encrypted connection — your queries and the results they return travel to Q-omics's infrastructure. Fast to start, and no infrastructure for your team to run.
A Q-omics instance runs on your own infrastructure, packaged as a Docker image. Your data, your queries, and the results they produce all stay inside your network — nothing crosses out.
Every partnership starts the same way — a low-commitment first look, then a proof of concept. What happens after that is shaped around your program, not a fixed queue.
See Q-omics work against published cohorts before you share anything of your own.
Skip straight to your own targets under NDA, if confidentiality matters from day one.
A deeper, contracted proof of concept scoped to your program, fully confidential.
Then, together — in whatever order fits your program
Our team and yours work the data together toward a specific discovery goal.
Wire Q-omics into your own pipeline through the same API and MCP connector every developer uses — provisioned as part of your engagement, not the public rollout queue.
Land on whichever model fits how your team runs production — hosted, or inside your firewall.
Enterprise engagements run on the same API, MCP connector, and query guarantees documented for every Q-omics developer, not a separate, unproven system.
A starting point covering both integration paths — the MCP connector and the REST API.
The complete request and response contract, authentication model, and query guard limits.
Every data type, valid combination, and lineage the platform supports, down to the exact parameter tokens.
You choose where Q-omics runs, and that choice decides what leaves your network. Deploy on-premises and your data, your queries, and your results stay inside your own environment — nothing crosses out. Encrypted transit and de-identified sourcing from Q-omics's own MetaDB apply regardless of which model you pick. Query-level limits such as row caps and timeouts are tuned to each deployment's own infrastructure — see the full Security Overview for the defaults.
Every engagement starts with a conversation, not a contract. Tell us what you're building, and we'll help you find the entry point that fits.
Talk to our team →