For researchers, students & solo reviewers
One real review, end to end, at no cost.
The free tier runs the full pipeline on one real review, end to end — PRISMA-aligned defaults and guardrails on every step, with a validated statistical engine running under the hood.
Free tier · PRISMA-aligned · validated statistics
Random-effects pool · primary outcome6 studies
Smith 2024
0.62 [0.41, 0.94]
Chen 2023
0.71 [0.55, 0.92]
Patel 2024
0.83 [0.62, 1.11]
Garcia 2023
0.74 [0.58, 0.95]
Okafor 2024
0.88 [0.71, 1.09]
Müller 2022
1.05 [0.78, 1.41]
Pooled (RE)
0.78 [0.65, 0.93]
← favours interventionfavours control →
study estimate (size ∝ weight)pooled (RE)
RR, log scaleThe shift
From a review you submit and forget to one you can keep alive.
Same workflow, two states. Flip the switch to see what changes.
Run once · frozen when you submit Live · re-runs on your schedule
Your reviewA one-off, frozen at submissionRe-runs whenever you wantone-offliving
Staying currentA manual re-search each timeAutomatic, on a schedulemanualautomatic
The statisticsHand-scripted and error-proneA validated engine, no codescriptedvalidated
Static — current only as of submissionKept current for as long as you like
How it works
The whole pipeline, without the scaffolding.
Build the review once with guided defaults, keep it current if you want to, and inspect every number — no code, same rigour.
Build
Build the comparison once
- A systematic review and a network meta-analysis
- Anchored against every relevant comparator
- Defensible from the first submission
Keep live
Re-runs on a schedule
- The whole pipeline re-runs on a cadence
- Flags when a new trial moves the result
- A signed record of what changed, each cycle
Inspect
No black box
- Deterministic statistics — same inputs, same result
- Every estimate traces to its source study
- Change an assumption and re-run
Why trust it
The same engine the pros run.
Validation
We reproduced a published forest plot — exactly.
In our reproduction case study, Axelium rebuilt a published meta-analysis end to end and matched its pooled estimate. Same inputs, same numbers — because the statistical engine is deterministic.
Comparisons a committee will accept
Pairwise and network meta-analysis, plus population-adjusted indirect comparisons, with certainty grading — every step inspectable.
Network meta-analysisMAICSTCML-NMRGRADE certainty
Questions