Refine (refine.ink)¶
external · status: active · focus: review · discipline: general · started: 2026
Project page: https://www.refine.ink/
Source: projects/landscape/refine-ink.yml
Positioning¶
A commercial AI peer-review service that produces reviewer-grade feedback on academic papers within ~20–40 minutes by running multi-hour parallel compute jobs (~2+ hours per review). Targets four error classes: accuracy (statistical / methodological), mathematical reasoning (proof gaps, edge cases), internal consistency (text↔tables↔citations), and general rigor. Sits in the referee-simulation stage of the RISE pipeline.
Distinctive contribution¶
Positions itself as enterprise-grade with explicit security and privacy commitments (SOC 2 + ISO 27001 in progress, zero-retention contracts, papers never used for training). Markets adoption by Oxford / Stanford / Yale / MIT / Caltech / Cambridge / Brown / OpenAI researchers. Closed-source commercial offering; first document free.
Evaluation scores¶
| Dimension | Score (0–3) | Note |
|---|---|---|
| Lifecycle coverage | 0 | Single stage (referee simulation). |
| Autonomy level | 2 | Supervised: user uploads, system returns a structured review. |
| Architectural transparency | 1 | Marketing-level descriptions only; internals not publicly documented. |
| Inputs supported | 1 | PDF inputs; no integration of literature corpora or co-author context. |
| Outputs / reproducibility | 1 | Reports persisted to user account; not designed for byte-level reproducibility. |
| Internal evaluation | 1 | Marketing claims of reviewer-grade quality; no publicly verifiable benchmark. |
| Openness | 0 | Closed-source commercial product. |
| Maturity / traction | 2 | Active commercial offering with named institutional adoption signals; user-base size not disclosed. |
| Cross-family policy | 0 | Closed; single internal stack. |
| Runtime assurance | 1 | ~2-hour parallel compute per review implies multiple internal passes; mechanism not public. |
| Cross-platform portability | 0 | Closed commercial product; single web surface. |
Scored on 2026-05-18. See the evaluation rubric.
Tags¶
Pipeline stages: referee-simulation
Architectural features: multi-agent tool-use
Inputs: submitted-paper-pdf
Outputs: referee-report issue-list
Limitations¶
- Closed-source; cannot be audited, extended, or self-hosted.
- Per-review compute cost passed to user via subscription; pricing not transparent on landing page.
- Marketing-driven adoption claims; no published systematic comparison against alternatives.
- Targets the same review niche as coarse.ink and reviewer3.com; differentiation is per-review compute intensity.
Related projects in this catalog¶
Related references (literature catalog)¶
- Gartenberg, C. et al. (2026). More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review
gartenberg2026morebetter - Naddaf, M. (2025). AI Is Transforming Peer Review — and Many Scientists Are Worried
naddaf2025aipeer