Solutions · Clinical Data Managers
The judgment calls are the part of the job you're good at — but they're buried under CRF design, edit checks, extraction, gap-hunting, and queries. Health1st AI takes the repetitive weight so you spend your day on the decisions, not the data entry, and reach lock without the late-study panic.
What you own
We know how this feels
You know the study is only as clean as the hours you can find for it — and lately there aren't enough hours before the query backlog catches up with you.
And the part no one says out loud:
Where the agents fit
The grind you just read isn't abstract — each piece of it already has an agent assigned. Here's which one picks up which fight, so you can see exactly where the help lands before you commit to anything.
The pain
Study build shouldn't swallow your timeline
The agent on it
CRF Designer AgentTurns a protocol into CDASH-compliant eCRFs with edit checks and validation rules.
The pain
Your data managers deserve better than transcription
The agent on it
Source Data Extraction AgentExtracts structured trial data from source documents with OCR and clinical NLP, de-identifying PHI as it reads.
The pain
The gaps you find at lock should surface now
The agent on it
Missing-Information Detection AgentCompares submitted data against expected fields to find gaps, then generates context-aware queries to close them.
The pain
Queries shouldn't age out in a spreadsheet
The agent on it
Query Automation AgentRuns the full query lifecycle — auto-populating responses, tracking status, and escalating by age, type, and priority.
The pain
You know the change — you just can't make it
The agent on it
Conversational Forms AgentEdit CRFs, validations, and ICFs with natural-language instructions — like ChatGPT for study build.
The pain
SDTM shouldn't be a downstream scramble
The agent on it
SDTM Annotation AgentAuto-generates SDTM annotations and the annotated CRF, Pinnacle 21-clean.
Your agentic workforce
These feature agents map most directly to clinical data managers. Enable the ones you need, per study and per deliverable, and expand over time.
Turns a protocol into CDASH-compliant eCRFs with edit checks and validation rules.
Learn moreExtracts structured trial data from source documents with OCR and clinical NLP, de-identifying PHI as it reads.
Learn moreCompares submitted data against expected fields to find gaps, then generates context-aware queries to close them.
Learn moreRuns the full query lifecycle — auto-populating responses, tracking status, and escalating by age, type, and priority.
Learn moreEdit CRFs, validations, and ICFs with natural-language instructions — like ChatGPT for study build.
Learn moreAuto-generates SDTM annotations and the annotated CRF, Pinnacle 21-clean.
Learn moreOutcomes
Quantified targets we build toward with each engagement.
Figures shown are pre-launch targets based on internal benchmarks, not guaranteed outcomes.
Every output is grounded, reviewed, and inspection-ready
“The queries that used to keep me at my desk at 11pm now come pre-drafted and de-identified for me to approve or kill. I'm still the one deciding — I'm just not the one typing every one of them anymore.”
Illustrative — representative of the workflows we build toward during our pre-launch pilot.
No pressure, straight answers
The doubts that usually surface before a team like yours says yes — answered plainly, including the places where the honest answer is a limit rather than a promise.
See it run on one of your own studies — no pressure, no obligation, and honest answers, including on the limits. We will walk clinical data managers through exactly what stays under your control.
