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askFinz
Use case · For clinicians

AI for clinical research, with the trial record intact.

Turn a trial search into a documented pass. Pull registered studies by condition, intervention or population into a notebook, read them beside the papers written about them, and keep every detail — sponsor, phase, status — tied to its source.

ResearchHealthcare
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In access today
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Moves
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Workflows
Working note · clinicianscited

Pull the registered trial record[1]

Read it beside the literature[2]

Search across everything you've collected[3]

File the review with sources attached[3]

[1] Research[2] Search[3] Storage

What you can do

Four moves, one workspace.

The concrete work behind "ai for clinical research" — not a feature list.

01

Pull the registered trial record

Search registered studies by condition, intervention or population and bring the record — sponsor, phase, status — into a notebook, not just a summary.

02

Read it beside the literature

Pull the papers written about a trial into the same notebook, so its registered design and its published results sit next to each other.

03

Search across everything you've collected

Semantic search over trial records, papers and your own notes — find the detail without re-opening every record.

04

File the review with sources attached

Export the summary to versioned storage alongside the underlying records, so the next review starts from the same file.

What it reads against

Healthcare work is only as good as its sources.

The reference collections this job draws on. Each is a page you can open and read before you trust a single answer.

  1. Clinical knowledge, and the trials behind it

    Registered studies kept as registry records — with phase, sponsor and recruiting status intact — beside the literature.

  2. Papers, preprints and the data behind them

    Open-access research read in full — with the datasets a finding rests on kept alongside the write-up.

  3. Reference knowledge, read from the wikis that maintain it

    The settled account of a subject, read from the maintained entry rather than a copy of it.

Collections are libraries the workspaces read from, kept as what they are rather than flattened into one pile. See the full collection breakdown.

Example workflows

What it looks like end to end.

01Worked example

Trial landscape scan

For a condition or intervention, pull every relevant registered trial into one notebook, sort by phase and status, and see the literature behind each one — a landscape read in an afternoon instead of a week of registry searches.

02

Protocol comparison

Line up two or three trials on the same question side by side — population, endpoints, phase — and note where the designs actually differ, each detail tied to its record.

Questions

Frequently asked.

Can askFinz search clinical trial registries?
Yes. The index holds registered studies with their sponsor, phase and status attached, searchable by condition, intervention or population rather than by trial name alone.
Does it read trials alongside the published literature?
Yes. Trial records sit beside the academic corpus in the same index, so a study's registered design and the papers written about it turn up together and can be pulled into one notebook.
Is this a clinical decision-support tool?
No. askFinz surfaces the registered trial record and the literature around it with citations attached — it doesn't diagnose, recommend treatment or replace a clinician's judgement.

For clinicians

Put it to work.

Request private access and we will walk through the workspaces this job runs on.

workspaces in access
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workspaces in access
worked examples
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worked examples
reference collections
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reference collections

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