Puraite
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AI Systematic Review SoftwareSystematic reviews in days, every decision auditable.

Explainable AI for the life sciences, with the reasoning and audit trail behind each include and exclude.

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Projects/Title & Abstract ScreeningDashboardMy QueueAI ScreeningResults

55 included · 2,271 excluded · 8 unclear

Screening Details

Supervised exercise versus usual care in chronic low back pain: a randomised trial

Demo Journal of Musculoskeletal Research · 2023 · DOI 10.0000/demo.2023.1284

AI AnalysisAI DecisionIncludedAI Confidence94%

Overall Summary

A randomised trial of supervised exercise against usual care in adults with chronic low back pain. Pain intensity at 12 weeks is the primary outcome. All inclusion criteria are met and no exclusion criterion applies.

Key Evidence

  • “randomly assigned to a supervised exercise programme or usual care”
  • “non-specific low back pain lasting 12 weeks or longer”

AI Reasoning 8 Satisfied0 Violated0 Unclear

  • Adults with chronic non-specific low back pain Population

    Participants are adults whose pain has lasted 12 weeks or longer.

  • Supervised exercise therapy Intervention

    The programme is delivered in supervised sessions.

  • Usual care, no treatment or another active treatment Comparator

    The comparison group receives usual care.

  • Pain intensity or disability reported Outcome

    Pain intensity at 12 weeks is the primary outcome.

  • Randomised controlled trial Study design

    Participants were randomly assigned to the two groups.

  • Acute or post-surgical back pain Population

    Pain is chronic and no surgery is reported.

  • Participants under 18 years Population

    All participants are adults.

  • Protocol or conference abstract without results Publication type

    Results are reported in full.

Audit TrailAI Screening SystemScreened as Include12 Nov 2026, 14:32

<1 month

Draft systematic review with Puraite

16 months

Industry standard

Puraite delivers a draft systematic review in roughly <1 month instead of the industry-standard 16 months. The AI works as a second screener next to your reviewers, not in place of them.

Supported by Europe's leading AI and life science organisations

eXISTRWTH InnovationHigh Tech NRW AcceleratorFounders FoundationGerman Acceleratorgarage33QuhrPaderborn Universitylife science factoryUniversity Hospital CologneGHA - German Health Alliance

Why Puraite

Four capabilities that set Puraite apart from generic AI tools and legacy SLR platforms.

Explainability

Every decision, traced to source.

Every AI screening decision links directly to the sentence that drove it, with a calibrated confidence score. No black box. No trust-us outputs. Auditable at every step.

Regulatory-grade

Built for submission, not just discovery.

PRISMA flow diagrams, GRADE certainty ratings and RoB assessments are generated automatically with complete decision logs, ready for HTA, MDR CER or FDA dossier.

Human control

You decide. AI recommends.

Approve, override, comment or escalate any AI action at any stage. Puraite augments your team's judgment; it never replaces it. All overrides are logged and exportable.

End-to-end

One digital workspace. Zero media breaks.

Protocol to PRISMA report, every step lives inside one auditable environment. No switching tools, no copy-paste. Activate AI at any step or work entirely manually.

Title & Abstract Screening/Audit TrailAppend-only

Supervised exercise versus usual care in chronic low back pain: a randomised trial

  1. AI Screening SystemIncluded, confidence 94%Decision with rationale and source quotes stored
  2. R. Okafor · Reviewer 1IncludedAdopted the AI decision after reading the abstract
  3. L. Brandt · Reviewer 2ExcludedReason given: comparator is another exercise programme
  4. SystemConflict openedTwo human decisions differ, record leaves the queue
  5. M. Sato · Project ManagerConflict resolved: IncludedComparator criterion I3 allows another active treatment
  6. SystemSent to full-text retrievalPRISMA count updated

No Training on Your Data

Your data is never used to train AI models. Our AI providers keep inputs only for a limited time for abuse monitoring. All data can be deleted on demand.

Security and data handling

From Protocol to Evidence in Six Phases

The complete systematic review workflow, powered by explainable AI.

Planning & Protocol

The most critical phase of any systematic review. If the protocol leaves room for interpretation, downstream AI and human decisions will be inconsistent. Puraite provides a guided wizard that walks you step by step through protocol creation – simply fill in the fields without having to set up the protocol manually. It flags ambiguous criteria in real time so every inclusion rule is precise before screening begins.

  1. Define Research Question (PICO)
  2. Conduct Scoping Search
  3. Write the Protocol
  4. Register Protocol (optional)

See the whole product

Three Ways to Run Your Review

Puraite runs systematic reviews your way: manual, hybrid or AI-assisted, with team workflows built in.

01

AI-Driven

For teams that want speed. Use AI to draft searches, screen studies, extract data, flag conflicts and prepare outputs. Human reviewers stay in control with approve, override and audit trails.

02

Hybrid

For CROs and HEOR teams. Assign reviewers, split workloads, use AI where it helps, and keep manual checks for high-stakes decisions. Built-in conflict resolution keeps the team moving.

03

Fully Manual

For Cochrane-style or conservative workflows. Run the entire SLR manually: reviewer assignment, dual screening, extraction, comments, conflicts, audit trail and project oversight, with AI turned off or used only when approved.

Built For Review Teams

Roles, assignments, audit trail. Your team migrates cleanly into Puraite.

Project Manager
Configure protocol, assign reviewers, monitor progress, resolve bottlenecks.
Reviewer
Screen, extract, comment and resolve conflicts in assigned workspaces.
Viewer / Stakeholder
Follow progress and inspect outputs without changing study decisions.
Audit Trail
Decisions, overrides, comments and AI-assisted actions are attributable by user.

Who Puraite Is Made For

Regulated industries where the speed, auditability, and reproducibility of evidence synthesis directly determine commercial and regulatory outcomes.

Pharmaceuticals

Regulatory AffairsMarket Access & HEOR

Medical Devices

Regulatory AffairsClinical & Market Access

CRO & Market Access Consultancies

Evidence Synthesis TeamsClinical Operations

Insurance & Payers

Coverage DecisionsHealth Economics

Chemistry

Regulatory SafetyProduct Compliance

Food & Nutrition

Regulatory SafetyProduct Compliance

Cosmetics

Safety AssessmentClaims & Dossiers

Academic Network

Research groups working with Puraite

Universities and public research institutes run their systematic reviews on Puraite. Academic access is free, with no time limit.

  • All India Institute of Speech and Hearing, MysuruIndia
  • Harvard UniversityUnited States
  • National Research and Innovation Agency (BRIN)Indonesia
  • Universidad de AntioquiaColombia
  • Università degli Studi della Campania Luigi VanvitelliItaly
  • University of AberdeenUnited Kingdom
  • University of OxfordUnited Kingdom
  • Wayne State UniversityUnited States

See the Academic Network

Puraite's end-to-end systematic review platform has allowed us to maintain a high level of research momentum without compromising human control. It has streamlined our evidence synthesis workflow, allowing our team to process and manage over 10,000 records in an auditable, highly efficient workspace.

Where Do You Stand on SLR Automation?

See how AI-powered evidence synthesis compares to your current workflow.

Current Annual Cost
€825,000
With Puraite
€123,750 to €247,500
Annual Savings
€577,500 to €701,250
Time Saved
70 months

Industry benchmark: a standard systematic review with 5 co-authors over 16 months costs approximately €165,000 in researcher time. Costs scale proportionally with team size and project duration.

Engineering Rigor

How we build, validate and deploy AI for regulated evidence synthesis.

Methodology and explainability

How we test screening

We test the AI screening against the decisions of published Cochrane reviews. Joint evaluations with independent academic research groups are under way; we will link the publications when they appear.

Selecting the right model for each task

We benchmark leading foundation models across every pipeline stage: retrieval, screening, extraction and synthesis. Model selection is task-specific. A model that excels at eligibility classification may underperform at data extraction. We fine-tune and specialize models for domain-specific tasks such as HEOR dossier preparation, clinical data extraction and regulatory evidence appraisal. This allows us to deploy the most capable model for each step at the lowest cost and energy consumption.

Confidence and rationale, not black-box predictions

Every screening decision comes with a confidence score and a rationale linked to the source text, so your reviewers can see why the AI decided and choose which decisions to check.

Integrates with Your Research Stack

Connect to major biomedical databases and export to the formats your team already uses.

PubMedOpenAlexSemantic ScholarClinicalTrials.govmedRxivbioRxivEurope PMCDOAJFDA FAERSFDA MAUDEHTA DatabasesEFSA.RIS Import.CSV ImportPRISMA ExportDOCX Export

Additional databases coming soon.

Frequently Asked Questions

Not sure where to start?

Answer a few short questions about your next review. You get a setup for your team and can request a pilot on the same page.

What is Puraite?

Puraite is an AI-powered platform for systematic literature reviews that combines scientific rigor with explainable AI (XAI) to deliver transparent, reproducible and regulatory-compliant results.

What is a systematic literature review?

A systematic literature review (SLR) is a structured research methodology for identifying, appraising and synthesizing all relevant evidence on a specific research question. It follows predefined protocols to minimize bias and ensure comprehensiveness.

Who is Puraite for?

Puraite serves pharmaceutical companies, contract research organizations (CROs), health technology assessment (HTA) bodies, academic researchers and anyone conducting evidence synthesis in regulated environments.

What makes Puraite different?

Puraite's AI is built to support dual screening, not to replace it. Every AI decision shows its reasoning and can be overridden by a reviewer. The platform is PRISMA compliant and covers the review from protocol to report in one auditable workspace.

Is Puraite scientifically validated?

We evaluate Puraite's AI screening against the decisions of published Cochrane reviews. Joint evaluations with academic research groups are under way; we will link the publications when they appear.

How does human-AI collaboration work?

AI augments human reviewers by automating screening, extraction and synthesis tasks. Every AI decision is reviewable and overridable. Human experts maintain full control with approve, override, comment and second review capabilities.

What review types are supported?

Systematic reviews, scoping reviews, rapid reviews, living reviews, umbrella reviews, targeted reviews and meta-analyses. The platform adapts its workflow to each review type's specific methodology requirements.

How secure is your data?

Puraite is fully GDPR compliant with EU-based servers. All data is encrypted in transit and at rest. We implement strict access controls and regular security audits. We are currently pursuing ISO 27001 and SOC 2 certifications to meet the highest enterprise security standards.

What export formats are available?

Word (DOCX), CSV, PDF, RIS, XML, JSON and PRISMA-compliant reports. Export formats are compatible with major reference managers and regulatory submission requirements.

How long does it take to complete a review with Puraite?

Depending on the scope and complexity, Puraite can reduce a typical 6-24 month systematic review to days or weeks. The exact timeline depends on the number of records, review type and level of human oversight required.

What databases does Puraite search?

As of now, Puraite integrates with PubMed and OpenAlex. Embase, Medline and other major bibliographic databases are coming soon. Depending on the field, we also plan to support specialized niche databases for targeted evidence synthesis.

Can multiple reviewers collaborate on the same project?

Yes. Puraite supports multi-reviewer projects with PM/reviewer roles, task assignment, conflict resolution, audit trails and real-time collaboration features. Advanced workspace analytics and richer consensus tooling are on the roadmap.

How does Puraite handle full-text PDF retrieval?

Puraite can automatically retrieve full-text PDFs from linked institutional subscriptions and open-access repositories. For paywalled content, the platform integrates with your institution's library access.

Is training required to use Puraite?

Puraite is designed to be intuitive for researchers familiar with systematic review methodology. We provide onboarding sessions, video tutorials and dedicated customer success support for all enterprise accounts.

Can Puraite handle non-English language publications?

The vast majority of biomedical evidence is published in English, which Puraite handles natively. Multi-language screening and extraction capabilities for major European and Asian languages are on our development roadmap and will be available in a future release.

Ready to Accelerate Your Evidence Workflow?

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Funded by the German Federal Ministry for Economic Affairs and Energy and the European Union through the European Social Fund Plus (ESF Plus). Implemented by Projektträger Jülich as part of the EXIST programme.