Research Paper Figures and Claims Extractor
Extract key claims, figure evidence, methodology limits, citations, and practical implications from technical research papers.
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Extract key claims, figure evidence, methodology limits, citations, and practical implications from technical research papers.
Run a structured AI safety red-team workshop to identify abuse cases, assess safeguards, define monitoring, and prepare launch-readiness decisions.
Check market sizing assumptions against cited sources, identify definition mismatches, and produce a cautious strategy or investment brief with confidence limits.
Synthesize customer interviews, win-loss evidence, objections, and verified proof points into a traceable strategic narrative, messaging spine, objection matrix, and validation plan.
Convert quarterly results, OKRs, KPIs, wins, misses, and constraints into an executive operating review with root causes, decisions, owners, risks, and a 30-60-90 day execution plan.
Guide Codex through evidence-based legacy module inspection, behavior mapping, regression-risk analysis, and characterization test design before a risky refactor.
Create a practical SOP for responsible team AI use, covering allowed use cases, restricted data, review rules, approval roles, escalation paths, and update cadence.
Draft a governance-ready review pack for AI policy exceptions, risk decisions, residual risks, controls, mitigation commitments, and approval questions.
Design human review gates for AI-assisted workflows with quality criteria, escalation rules, reviewer rubrics, audit evidence, and risk-based approval paths.
Synthesize conflicting expert sources into a balanced decision memo with claim comparison, evidence quality, uncertainty, source bias, and decision implications.
Use Codex to produce an evidence-based safety review of proposed Laravel schema and data migrations, including engine-specific lock analysis, rolling-release compatibility, backfill controls, recovery planning, and measurable deployment acceptance criteria.
Use Perplexity to build a citation-backed procurement dossier that tests AI, SaaS, software, agency, or service-provider claims, grades evidence, records unresolved risks, and prepares precise vendor questions without representing research as approval or completed due diligence.