Clinical trials, monitored differently.
Sensai knows your protocol and reads every record in your study as it comes in. It flags what needs attention, attaches the evidence, and sends it to the right person. When you want to dig in, you just ask.
- A safety signal building in one treatment arm13/241 vs 3/238 · safety workerCritical
- Adverse events at one site missing onset datesSite 21 · 10 events · 5 subjectsHigh
- Dosing errors clustering at a single siteSite 8 · 46 of 337 error-coded recordsHigh
- Lab values that need source verification21 extreme LDH and platelet resultsMedium
- Enrollment stalled at three sites since last monthSites 4, 12, 17 · enrollment workerMedium
The data already knows. The team finds out later.
Monitoring keeps getting bigger, and slower with it.
Something sits in the data for weeks.
Not because anyone missed it. Nobody was scheduled to look until the next review.
Your best people spend the week fetching data instead of judging it.
Pulling listings, chasing extracts, rebuilding a report someone already built last month.
Every time the study grows, the team watching it has to grow too.
And on the studies you've outsourced, you hear about problems when the CRO decides to tell you.
The later you find it, the more it costs.
Catch it in week three and it's a phone call to the site. Leave it until month four and you're writing a protocol amendment.
Every trial gets a team of AI workers.
They watch. Your team decides.
Your study
- Protocol and study material
- Clinical data imports
- Labs and safety data
- Site and enrollment records
AI workers
Every data import is checked the day it lands, against this study's protocol. Not a general-purpose model pointed at a database.
Your team
- CRAQuery site 21 for missing AE onset dates
- MEDICAL MONITORReview thromboembolic events by arm
- DATA MANAGERReconcile dosing records at site 8
They don't wait for the next review.
Every data import gets looked at immediately, so issues surface in days rather than at the next scheduled pass.
They know this trial specifically.
From the protocol through the clinical data and everything in between. Your study material, understood in detail.
Findings go to whoever should handle them.
With the evidence attached, so nobody has to reconstruct how it was found.
What your team opens in the morning.
Ranked, with the evidence attached, and nobody had to go looking for any of it.
Insights
Review and manage study insights
Review the excess of serious treatment-emergent blood-clot events in the active arm and confirm that the two critical pulmonary embolism cases were fully reported and adjudicated. Events occurred in 13/241 active vs 3/238 placebo subjects. This is a safety signal, not a causal conclusion.
Query site 21 to enter or verify onset dates for 10 treatment-emergent adverse events in five subjects. Without onset dates, event timing can't be checked against treatment exposure.
Reconcile recorded study-drug administration errors, starting with site 8: 46 of 337 error-coded dose records sit in 20 subjects there.
Verify the flagged laboratory source records and units before any correction. Twenty-one extreme results need reconciliation.
- On treatment, the active-arm mean sits at or near the 12 g/dL threshold; placebo is generally below it.
- I used the treatment-arm field in the hematology records and all available hemoglobin observations.
Mean hemoglobin over time by treatment arm
The day starts with a short list.
Findings from every worker, sorted by urgency, each with its reasoning and the records behind it.
- Source and reasoning on every finding
- Routed to the CRA, medical monitor or data manager who should act
- Resolved findings stay on record for the whole team
When you need to dig in, just ask.
Ask in plain language and get the chart, the numbers and how it got there. No tickets, no programming queue, no waiting until Thursday.
- Answers built from your study's own records
- How it got there is explained in the answer
- Suggested follow-ups to keep digging
Same team. Different week.
The work doesn't disappear. It changes hands.
Your study. Your controls. Your call.
Your study runs in its own environment.
Nothing is shared with other sponsors. The AI runs inside that environment, and nothing is used to train models.
Built to the standards regulated trials expect.
Designed around HIPAA, GDPR and 21 CFR Part 11: data encrypted in transit and at rest, access controlled per person and logged, and an audit trail on every change, running on cloud services approved for healthcare workloads.
Who did what, and when.
Logins, access changes, imports, exports, unblinding, and every change to a finding or task are recorded.
The AI proposes. Your team decides.
It reads your data and can never write to it. Findings and tasks are for your people to act on; nothing in the study changes without a person.
Your people make the decisions. Every judgement, every call.
Sensai surfaces what needs attention and shows its reasoning.Built by the people who did the analysis.
Sensai was founded by people who spent years inside sponsor clinical trial teams, working alongside every function from operations to clinical monitoring and turning study data into the answers those teams needed. We built the tool we wanted then.
Is this just a chatbot on top of our database?
No. It knows your study end to end: protocol, study material, data and SAP. AI workers check every import, build on each other's findings and work with your team to resolve what they find, and surface insights specific to your study. And it opens up the study data, so anyone on the team can get any analysis on the fly.
Where does our data go?
It stays in your own environment. The AI runs there too, and nothing is used to train models. Access, imports, exports and unblinding are all recorded.
Who makes the decisions?
Your team, always. Sensai surfaces what needs attention, explains why, and hands it to the right person. The judgement, and the decision, stay with your people.
We run the study through a CRO.
That works. Nothing changes for your sites, and you stop waiting for the CRO's report to know what's going on.
How long before we're using it?
Once we've set up your study, your team uses it the same day. There's nothing technical to learn: you ask in plain language, and the insights, tasks and dashboards explain themselves. Our team is around whenever you need us.
Pick one study you're running now.
Any phase, any indication, any size, in-house or through a CRO. We'll run Sensai on your data and you'll see what it finds, with the reasoning behind every finding. Whatever we turn up is yours to keep.
- Tell us about the studyA short call on the indication, phase and where the data lives.
- We set up your tenantYour protocol and data, in an environment only your team can see.
- You see real findingsOn your own data, straight away, each with its evidence.