Published January 21st 2026
As frontier technologies move from lab to pilot to commercialization, the quality of research increasingly determines the quality of R&D decisions.
To evaluate how modern AI research tools perform in this context, we ran the same advanced research prompt through two widely used platforms:
Both outputs were assessed by Gemini, as an independent AI auditor, using a 100-point R&D evaluation rubric covering source quality, technical depth, IP intelligence, commercial readiness, and actionability for research teams.
The result was a clear divergence in strengths:
Cypris produced an R&D-grade intelligence report (89/100) optimized for technical due diligence and IP-aware decision-making.
Perplexity produced a strong market intelligence report (65/100) optimized for breadth, timelines, and business context.
This analysis breaks down the results and shares how R&D teams should think about choosing the right research tool depending on their objective.
Evaluation context
Both reports were generated from the same geothermal energy research prompt and evaluated using a 100-point rubric designed around what matters most to R&D teams. The assessment reflects a simulated “current state” as of January 21, 2026, with both reports referencing developments from late 2024 and 2025. All recency and accuracy judgments are made relative to that context.