Industries · Life sciences

A sponsor should not be able to tell your regions apart.

Sponsors and CROs issue RFIs and RFPs for nearly every trial, and each arrives in a different format asking the same underlying things: which assays, what validation, what logistics, what data deliverables, what compliance posture. The knowledge to answer exists — in past proposals, project files, and the heads of scientific directors. It is not available at the moment the answer is due.

Built for proposals and business development, scientific operations, and quality.

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Respond answering a sponsor RFP — the validation package cited on each answer

Where the sponsor answer actually stalls.

Not for want of science. The work has been validated and the answer written before. It is sitting in a past proposal or in a scientific director's head while the RFP clock runs.

  • 01

    The proposals floor

    Every RFP rebuild starts from old proposals and staff memory. First-pass answers to repeat questions — assay menus, turnaround, kit composition, data integration — consume senior scientific time.

    That time should be going to the fraction of each bid that actually differentiates. Instead it goes to answers that already exist somewhere.

    Scarce scientist time spent on the questions that recur.

  • 02

    Scientific knowledge across regions

    Assay and study knowledge is deep and scarce. When a tenured project manager or lab director is unavailable, sponsor answers stall.

    Specimen stability, kit shelf life, a regional testing difference — three regions give three versions of one answer, and on standardised global testing the sponsor can see the difference.

    The variance is visible to the person deciding.

  • 03

    Quality, compliance and data

    Security, regulatory and data-handling questionnaires arrive in a new wrapper from every sponsor and CRO, consuming senior QA time on repeat answers.

    Blinded data management, chain of custody, accreditation posture, customs and distribution rules — the required language exists but is not reliably delivered in every response.

    For a business whose currency is trial integrity, a stale answer is a study risk.

What Tribble does about it.

One place the approved answer lives, with the source attached and an owner’s name on it — and every response you finish makes the next one cheaper.

  1. 1

    Load it

    Your approved sources come in with their permissions and versions intact, so every answer can be traced back from day one.

  2. 2

    Answer from it

    Answers are worked out before anyone asks. Each one shows the document it came from, who owns that document and when it was last changed.

  3. 3

    Keep what you learn

    Every edit a reviewer makes becomes the approved answer next time. Your experts see the 10–20% that is genuinely new, not all of it. The tenth submission is faster than the first.

Diagram: the answer loop 2100 × 800 · shared asset, same on every industry page

Sources in, cited answer out, reviewer edits folded back. One drawing, reused across all nine industry pages.

The documents a clinical services provider actually files.

All of them run the same way. Follow any one through to see it.

What we would measure.

Agreed against a baseline captured before anything starts, so the result is judged on your numbers.

Time to approved answerOn RFPs, RFIs and sponsor security questionnaires
First-pass qualityShare of outputs citing a governed source at acceptable quality
Scientific review burdenExpert time against the 10–20% exception-only target
Regional consistencyWhether two regions give one answer to the same technical question
Service-line attachCross-service conversations started from approved language
Prep and rampPre-call prep time, and time-to-proficiency for new proposal staff

Proof, and where it comes from.

We have not published a life sciences deployment yet. The numbers below come from document-response workflows of the same shape — hundreds of technical questions, several functional owners, one deadline set by the buyer. We would rather say that than put a stranger's logo next to your problem.

200 questions, under an hourClari, on a single RFPRead the story →
93% first passSalesforce, on a 973-question RFP
$864K in year oneUiPath, with 5 FTE of productivity returned

The first engagement: one workflow, four to six weeks.

Narrow scope is what makes that real rather than aspirational. One team, one motion, one baseline captured before anything starts.

  1. 1

    Connect · week 0

    Scope and owners named. Sources ingested from past proposals, assay menus and validation summaries, QA and regulatory language. Baseline captured from how the work runs today.

  2. 2

    Build · weeks 1–2

    The answer set assembled from your own records, scoped to the questions that actually recur. Your experts review and approve it.

  3. 3

    Pilot · weeks 3–4

    Live with a defined cohort on real work. Our team works alongside yours, tuning against what reviewers actually change.

  4. 4

    Prove · weeks 5–6

    Measured against the baseline, with a clear read on where value landed and a go or no-go on expanding.

Questions worth asking

Including a few worth putting to your own team before you talk to us.

How does this handle questions that genuinely need a scientist?

It routes them. First-pass answers are drawn from approved sources with the citation attached; anything new, sensitive or below the confidence threshold goes to the accountable expert before it ships. The target is that experts see the 10–20% that needs judgement rather than reviewing every answer, which is what makes the review sustainable rather than heroic.

Can it keep answers consistent across regions?

That is the main reason to do it. Every region draws on the same approved source, so the answer does not depend on which office received the question. When a stability figure, an accreditation or a data-handling rule changes, you change it once and it applies on the next response everywhere.

What about blinded and sponsor-sensitive material?

Sources are permissioned on intake, so access follows the permissions you already set rather than becoming a second, looser copy of them. That is also the argument against staff pasting sponsor context into consumer AI tools, which is the confidentiality exposure most quality teams are actually worried about.

How is this different from keeping a proposal library?

A library stores answers. It does not know which are stale, which contradict a current validation package, or which were edited after review last time. Tribble drafts from approved sources with the source, owner and version visible, and folds reviewer edits back in, so the next sponsor's RFP starts ahead rather than from zero.

What do we need before starting?

Past proposals, assay menus and validation summaries, QA and regulatory language, project records — in whatever form they exist. There is no migration. What matters more is naming who signs off on a scientific claim, a data commitment and a compliance statement.

Bring one sponsor RFP.

We will map what already exists across past proposals and project records, run the questionnaire together, and leave you with a first draft your scientists can review.

Book a demo