Systematic review automation

Your entire review,
automated.

From abstract screening to data extraction, Systronix walks you through every stage of the systematic review process — powered by AI, controlled by you.

Every step of the process,
handled.

Scroll through each stage of a systematic review and see exactly how Systronix accelerates your workflow.

STEP 01

Define Your Criteria

Start with what matters

Set your inclusion and exclusion criteria — population, intervention, comparator, outcomes, study design. Upload your protocol or guidelines as reference documents so the AI understands exactly what you're looking for.

Inclusion Criteria
Adults undergoing THA or TKA
Reports EQ-5D outcomes
RCT or prospective cohort
Exclusion Criteria
Case reports or reviews
Pediatric population
STEP 02

Import Studies

From Covidence or any reference manager

Drop in a Covidence export, RIS, BibTeX, EndNote XML, or CSV — hundreds of studies with titles, authors, and abstracts are loaded in seconds. No manual data entry, no copy-paste.

covidence-export.ris
Imported
1
Smith et al. 2024
2
Chen & Park 2023
3
Williams et al. 2024
4
Kumar et al. 2023
247 studies imported
STEP 03

AI Abstract Screening

Every abstract, evaluated

Each abstract is read against your criteria using a two-stage AI pipeline: fast regex pre-filtering, then deep language model analysis. The AI classifies each study as Include, Exclude, or Maybe — with a written reason for every decision.

Abstract Screening78%
42
Include
156
Exclude
12
Maybe
AI Reasoning
“Excluded: study population is pediatric (age <18), does not meet adult THA/TKA criterion.”
STEP 04

Full-Text Review

Go deeper on included studies

Studies that pass abstract screening move to full-text review. The AI reads the complete PDF and evaluates it against your detailed criteria, flagging potential exclusions with specific reasons.

Smith et al. 2024
Full text under review
Reviewing
Population: Adults, THA
Outcome: EQ-5D at 12mo
Design: Prospective cohort
All criteria met — Include
STEP 05

Data Extraction

Structured data from PDFs

Define your extraction columns — sample size, outcomes, follow-up period, effect sizes — and the AI pulls structured data directly from each paper into your review table. No more flipping between PDFs and spreadsheets.

Extracted Data
StudyNEQ-5D PreEQ-5D Post
Smith 20241420.520.81
Chen 2023890.480.77
Williams 20242030.550.84
45 columns extracted per study
STEP 06

Review & Override

You stay in control

Every AI decision is transparent and overridable. See the reasoning, override with one click, and maintain a full audit trail. The AI assists — you decide.

Jones & Park 2023
ExcludeInclude
Relevant subgroup analysis in appendix
Kumar et al. 2023
MaybeExclude
Conference abstract only, no full text
Full audit trail preserved
STEP 07

Export & Publish

Clean data, ready to go

Export your screening decisions and extracted data to PRISMA diagrams, Google Sheets, CSV, or DOCX. Your PRISMA flow numbers are calculated automatically. Go from search to synthesis faster than ever.

247
Studies Screened
42
Included
38
Data Extracted
~40hrs
Time Saved
Download PRISMA diagram
Download CSV
Sync to Google Sheets

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