Build an AI Research Team: Literature Review & Synthesis
Five frontier AI models working as your research assistants. Each with a specialized academic role. All trained on your field’s standards, your methodology preferences, and your citation requirements.
Literature synthesis that identifies consensus and debate. Analysis that gets smarter with every paper you review.
The literature is overwhelming
Thousands of papers publish in your field every year. Preprints move faster than peer review. By the time you finish one literature review, the landscape has shifted. Staying current is a full-time job on top of your actual research.
And reading isn’t enough. You need to identify consensus versus ongoing debate, evaluate methodology quality, trace citation networks, and spot the gaps no one has addressed. Single-AI tools give you summaries. They don’t give you synthesis.
Suprmind changes this. Five AI models work as your research team – one tracks recent publications, another grades methodology, another critiques limitations, another maps the citation landscape. The Knowledge Graph remembers every paper you’ve discussed, every methodological decision, every research question. Your 100th review has context your 1st couldn’t.
Five specialists. Comprehensive literature analysis.
Each AI brings different research expertise. Together, they synthesize what individuals can’t.
Grok
Recent Literature Scanner
Tracks recent publications, preprints, and conference proceedings in your field. Flags new findings that might affect your research. Monitors retractions and corrections. Catches what’s happening now.
Perplexity
Citation Verification
Finds and verifies sources. Traces citation networks. Identifies seminal papers and recent replications. Checks claims against original sources. Everything cited, everything verified.
Claude
Methodology Critique
Deep analysis of methodology, limitations, and potential biases. Evaluates statistical approaches. Identifies confounds and alternative explanations. The skeptical reviewer you need.
GPT
Structure & Consistency
Ensures logical consistency in arguments. Checks that conclusions follow from evidence. Validates that your synthesis accurately represents the sources. Catches gaps in reasoning before reviewers do.
Gemini
Literature Synthesis
Combines all perspectives into coherent synthesis. Identifies themes, consensus, and ongoing debates. Maps research gaps. Produces literature review sections ready for your papers and proposals.
15 minutes to build your AI research team
Configure once for your research area. Use across all your projects.
Create a Research Project
“Systematic literature review on attention mechanisms in transformer architectures. Focus: efficiency improvements, interpretability, and biological plausibility. Target venues: NeurIPS, ICML, ICLR. Citation style: NeurIPS format.”
Generate Instructions with Prompt Adjutant
Define your research standards, methodology preferences, and quality thresholds. Get structured instructions every AI will follow.
Upload Your Research Foundation
The documents that define your research context:
Methodology standards
Previous literature reviews
Your research questions
Citation style guides
Start Your Literature Review
Upload a paper. Ask for analysis. Five researchers respond in sequence – recent context, citation verification, methodology critique, consistency check, synthesis.
Paper analysis in action
YOUR PROMPT
Analyze this paper on sparse attention mechanisms. Evaluate methodology, identify how it relates to existing work, and assess whether the claims are supported. I’m considering citing this in my efficiency-focused literature review.
GROK – Recent Context
“Three related papers published since this one: Chen et al. (2024) extends sparse patterns to vision; Kumar et al. replicated with different results on longer sequences; Park et al. showed limitations in multilingual settings. Also: lead author’s follow-up preprint addresses some limitations noted here. Consider the evolved understanding.”
PERPLEXITY – Citation Network
“Paper cited 47 times since publication. Key citing works: 12 are direct extensions, 8 use as baseline comparison, 4 challenge efficiency claims. Original Sparse Transformer (Child et al., 2019) cited correctly. However: Longformer comparison may be unfair – uses different hardware baseline. Linformer claim on page 6 doesn’t match original paper’s numbers.”
CLAUDE – Methodology Critique
“STRENGTHS: Solid ablation study, reproducible setup. CONCERNS: (1) Efficiency measured only on A100 – may not generalize to other hardware, (2) Perplexity improvements are marginal and may not be significant with proper error bars, (3) Longest sequence tested is 4K – claims about ‘long-range’ need qualification. Statistical tests not reported for main comparison.”
GPT – Logical Consistency
“Abstract claims ‘2x speedup’ but Section 4.2 shows 1.7x average with high variance. Conclusion overstates implications – ‘enables new applications’ not supported by experiments shown. Figure 3 and Table 2 show different sequence lengths – direct comparison misleading. Introduction cites biological plausibility but experiments don’t address this.”
GEMINI – Synthesis
“RECOMMENDATION: Cite with qualifications. Contribution is real but overstated. For your lit review: cite as ‘one approach to sparse attention with demonstrated efficiency gains on specific hardware (though see Kumar et al. for replication concerns).’ Don’t cite the 2x speedup claim directly. Consider citing alongside Chen et al.’s extension which addresses some limitations. The methodology section is solid – good reference for experimental setup.”
Your team builds your knowledge base
The Knowledge Graph learns from every paper you review, every methodological decision, every synthesis.
What it learns
Citation relationships
Methodological patterns
Debates in your field
Your research questions
Gaps you’ve identified
How it helps over time
“This paper uses the same methodology you criticized in the Wang et al. review. Same limitations apply.”
“Three papers in your collection address this research gap – consider for related work section.”
“Author has 4 papers in your knowledge base. Track record: strong on theory, weaker on empirical validation.”
Beyond literature review
The same team structure works across the research lifecycle.
Grant Writing
Develop proposals with comprehensive literature context. Perplexity finds supporting evidence, Claude identifies potential reviewer concerns, Gemini helps structure the narrative. Multiple perspectives strengthen your case.
Paper Drafting
Write with your literature review at your fingertips. The Knowledge Graph connects your claims to sources you’ve already vetted. Related work sections that actually relate to your work.
Peer Review
Prepare thorough reviews with five analytical perspectives. Catch methodology issues, verify claims, identify missing citations. Professional-quality reviews that improve the field.
Research Gap Analysis
Map what’s been done and what hasn’t. Grok tracks recent activity, Claude identifies methodology gaps, Gemini synthesizes opportunities. Find your research niche systematically.
Build your AI research team today.
Literature synthesis that identifies consensus and debate.
Analysis that gets smarter with every paper you review.