AI for preclinical CROs, built around the work your scientists sign.
A preclinical CRO runs on quotes, study plans, reports and SOPs, and on the trust of its sponsors. We build AI for the operational side of that work: quotes and proposals drafted from your past statements of work, study reports drafted for scientists to check and sign, and SOP and quality questions answered with citations. We also put in place the AI policy, sponsor data controls and Microsoft 365 Copilot readiness your sponsors now ask about, for sites in the US and Europe.
Where CRO teams lose time, and where AI adds risk.
Quotes wait on senior scientists
Every request for a quote means finding the right assays, past pricing and a study design. The people who know the catalog best are also the busiest people in the lab.
Reports take longer to write than to run
Results come off the instruments quickly, then wait while someone assembles methods, tables and interpretation into the sponsor's format.
Sponsors write AI into contracts
Sponsor agreements have started to say how AI may touch their compound data, whether it can be used for training, and what you must disclose. Answering those terms takes evidence, not a policy draft.
Copilot is already switched on
Copilot Chat comes with Microsoft 365 and public AI tools are a browser tab away. Without labels, permissions and a written GxP boundary, sponsor data and GxP records are exposed to tools nobody approved.
AI for the operational side of a CRO.
Quote and proposal drafting
Reads an incoming request, finds the matching assays and past statements of work, and drafts the quote and study outline for your scientist to price and approve.
Open →Study report drafting
Assembles methods, results tables and figures into your sponsor template from approved data, with every value traced to its source. A scientist reviews, edits and signs.
SOP and quality search
Answers questions from your SOPs, methods and quality documents with the exact passage cited, limited to what each person is allowed to open.
Sponsor AI questionnaires
Standard answers for sponsor AI clauses and questionnaires, backed by your AI tool register and the controls in your tenant.
AI governance for GxP sites
One AI policy for the US and Europe, a written GxP boundary, an approval route for new AI tools and AI literacy training.
Open →Microsoft 365 Copilot readiness
Labels, data loss prevention and permission cleanup, so Copilot does not surface sponsor data or GxP records to the wrong people.
Open →AI drafts. People decide, sign and record.
In a CRO the study director and the scientist own the result. Our workflows draft, search and check, and a named person approves anything that leaves the building or enters a record. AI is never the source of GxP data, and nothing we build creates or changes a GLP or GMP record unless that path has been validated under your quality system.
Drawing that line is what lets a CRO use AI on proposals and reports without reopening validation for every system. It is also the line sponsors and auditors expect to see written down. Our page on GxP validation for AI workflows explains how we handle the cases that do cross it.
Good first workflows for a preclinical CRO.
Each one runs on your own documents in your own tenant, and each has one finished item you can count and check.
| Workflow | Who it helps | One finished item |
|---|---|---|
| Quote and study outline drafting | Business development and study directors | A draft quote a scientist approves without rework |
| Study report drafting | Study directors and report writers | A report draft with every value traced to approved data |
| SOP and method questions | Lab and quality staff | An answer with the SOP passage it came from |
| Sponsor AI questionnaires | Client services | A questionnaire answer backed by evidence |
Operational AI and governance, alongside your lab systems.
We focus on the work around the lab: quotes, reports, documents, sponsor terms and the governance that lets staff use AI safely. Our workflows read from LIMS and ELN systems through their APIs or approved exports. Instrument pipelines and LIMS or ELN rollouts are lab informatics work, and we work alongside a specialist when a project needs one.
Our regulated-AI experience comes from pharma review and compliance. For a European pharmaceutical regulator we built an AI review of medicine and health product advertising, where review that took two to three hours per asset now takes about two minutes, with every finding cited. For 12 years we have also been the technology partner to Arcondis, a life-science compliance consultancy, on work for large pharma.
A fixed price, paid when it works.
We scope one workflow with you, agree the acceptance tests before we start, and build it in your own Microsoft 365, Azure or AWS tenant in two weeks. You pay $10,000 only after every test passes, and sponsor data stays in your environment.
For AI governance and Copilot readiness we start with a short discovery of your tenant, contracts and sites, then give you a fixed price for the rest. We work from Plano, Texas and Munich, in English and German.
What sponsors and auditors will ask you to show.
A register of AI tools
Every AI tool and AI feature in use, with an owner, a risk level and the data it may touch.
A written GxP boundary
Where AI may draft, where a person must decide, and which systems AI never touches.
Sponsor data separation
Sponsor content limited to the project team and kept out of company-wide AI search.
No training on sponsor data
Approved tools only, under terms that exclude training on your inputs.
An audit trail
Who used AI, on what, and who approved the result.
AI literacy records
Training completion for staff who use AI, which the EU AI Act asks of your European sites.
From workflow to working tool in two weeks.
Scope and sign
We define the workflow, the deliverables, and the acceptance criteria, and sign an agreement on them before anything starts.
Build
We build the tool in your environment, with Claude Code and automated evaluation against your own data.
Pay when it works
$10,000, due only after every criterion in the signed agreement is met. Nothing before that.
Each workflow is built in two weeks in your tenant and paid only after it passes the acceptance tests you signed. Governance and Copilot readiness work is quoted at a fixed price after a short discovery.
What AI costs, including after the build →
Tell us the workflow →Questions buyers ask.
What can AI do for a preclinical CRO today?
The quickest wins are in operations: drafting quotes and study outlines from past statements of work, drafting study reports for scientist review, answering SOP and quality questions with citations, and answering sponsor AI questionnaires. Each runs on your own documents, and a person approves the output.
Can AI be used in GLP or GMP work?
Yes, with care. AI can draft and search, but it should never be the source of GxP data, results or conclusions. Any AI step that creates or changes a GxP record has to be validated under your quality system first, so most CROs start with work outside that boundary.
How should a CRO answer AI clauses in sponsor contracts?
Map each type of clause to a control you can show: an AI tool register, approved tools whose terms exclude training, labels that keep sponsor data with the project team, and an incident procedure. Most clauses are then answered by the same evidence rather than a new rule for each sponsor.
Is Microsoft 365 Copilot safe to use with sponsor data?
Copilot shows each person only what they can already open, so the main risk is oversharing inside your own tenant. Fix permissions, label sponsor content and keep sponsor and GxP sites out of Copilot search before you widen access.
Do you integrate with LIMS and ELN systems?
Our workflows read from LIMS and ELN systems through their APIs or approved exports. For instrument integration or a LIMS rollout, a lab informatics specialist is the right lead, and we work alongside one when a project needs it.
How much does AI cost for a CRO?
At QueryNow one workflow is $10,000, built in two weeks and paid only after it passes your acceptance tests. Governance and Copilot readiness work is quoted at a fixed price after a short discovery. Model usage and hosting run on your own cloud bill.
Ready to ship AI that actually works?
Send us the workflow. We return a fixed scope, price, and acceptance criteria in 48 hours. You pay $10,000 only after it works.
Tell us the workflow →Compliance-grade RAG: Retrieval systems a regulator can audit
How to build retrieval that a regulated reviewer can trust and audit.
Read it free →