Move your team from Claude Science to SciSpace.

SciSpace's Chat with PDF lets a user upload or open a paper and ask plain-English questions grounded in the document, with in-document citations pointing to the source location, available in both the web app and the Copilot browser extension. Claude Science's session workspace supports an equivalent document-grounded Q&A pattern generally: reference an uploaded artifact ('@' in composer) within a session and converse about it, with the coordinating agent able to discuss, summarize, and explain the content in context. Moving this workflow into Claude Science: upload the PDF into a session/project folder and use '@' to bring it into context for questions, the same conversational pattern as Chat with PDF, but without a dedicated single-document reading UI — it is one capability of the general-purpose session rather than a standalone lightweight reading tool. For quick, low-friction single-paper Q&A (e.g. reading on a phone, or in-browser while reading a publisher page via the Copilot extension), SciSpace remains the faster tool; Claude Science is the better destination once that paper needs to feed into actual computation (e.g. digitizing a figure's data, reproducing a reported statistic) in the same session.

SciSpace's Deep Review is a higher-tier mode of the literature-review workflow that goes deeper across a larger set of high-quality papers, producing wide custom-column tables (up to ~100 columns) suited to meta-analysis-style synthesis, gated to Advanced-and-above plans. Claude Science has no analog literature-depth mode; the nearest conceptual match is its artifact-provenance-and-Reviewer system, which does the opposite kind of 'deep' work — not analyzing more papers more thoroughly, but auditing whatever computational/manuscript artifact was produced against its full execution record (code, environment, conversation) to catch unverifiable claims. If a lab's actual goal in reaching for Deep Review is rigor/auditability of a synthesis rather than paper-count breadth, Claude Science's Reviewer is the better-matched destination capability: run the literature synthesis wherever it's produced (SciSpace, Elicit, or drafted directly in a Claude Science manuscript), then use the Reviewer pass to independently check the claims, numbers, and citations in that draft against its provenance record. It does not, however, replicate Deep Review's core value of surfacing and organizing more papers — that job has no Claude Science equivalent.

SciSpace's literature review turns a research question into a comparison table over its 280M+ paper index, with custom columns pulling natural-language-defined data points across every selected paper. Claude Science has no dedicated paper-comparison-table product; its coordinating agent can approximate the workflow generally — a session/project can ingest a set of papers (uploaded or fetched via a connector/skill) and the agent can extract and tabulate fields per user instruction, drafting the comparison as an artifact rather than a purpose-built column-based UI. Moving a review workflow from SciSpace into Claude Science: expect to describe the desired columns as natural-language instructions to the coordinating agent each time rather than reusing SciSpace's persistent custom-column definitions, and expect the output to land as a generated table/notebook artifact rather than a live, filterable literature-review grid. For labs anchoring on broad literature synthesis as the primary job, SciSpace's purpose-built table remains the faster path; Claude Science is a better fit once the review needs to feed directly into code-driven analysis (e.g. extracted effect sizes piped straight into a meta-analysis script in the same session).

SciSpace's literature search is a semantic query engine over 280M+ academic papers, unlimited on paid tiers (capped around 5 searches/month on the free Basic plan). Claude Science ships no comparable general paper-search index; its 60+ connectors instead give read-only, no-auth access to named scientific databases (Ensembl, UniProt, PDB, PubChem, GEO, ClinVar, GWAS Catalog, etc.) for pulling structured records once specific identifiers or accessions are known. A lab moving off SciSpace should keep it (or another literature-search tool) as the discovery front end and use Claude Science purely for the downstream structured-data retrieval and computation once a paper points to a specific dataset/structure/gene — e.g. a SciSpace-surfaced paper cites a PDB ID or GEO accession, and that gets pulled directly into a Claude Science session via the matching connector for analysis in the sandbox. There is no reverse migration path worth recommending here: Claude Science was never meant to replace broad semantic literature search, so a researcher needing that capability inside a Claude Science project should keep using SciSpace (or Elicit) alongside it rather than trying to approximate it with connectors.

SciSpace sells a standalone free Basic tier plus Premium/Advanced/Max individual plans and a Teams plan, metered by a monthly AI-action credit system (e.g. Advanced at $70/month annual for 10,000 credits/month unlocking Deep Review and wide extraction). Claude Science, in contrast, has no standalone price or credit meter of its own — it is a capability toggle bundled into the existing Claude Pro/Max/Team/Enterprise ladder (not available on Free), with usage drawn from the same shared 5-hour/weekly limits as Claude Code and Cowork rather than a dedicated research-credit pool. A team consolidating research tooling onto Claude Science does not gain a SciSpace-style 'unlimited literature searches, unlimited PDF chats' guarantee at a given tier — it gains general Claude capacity, which may be more or less generous depending on how much Claude Code/Cowork usage already competes for that same budget. Cost comparison should be done at the plan level (what the org already pays for Claude Pro/Max/Team/Enterprise) rather than mapping SciSpace's credit costs onto any Claude Science equivalent, since none exists.