What is Elicit and what is it good for?

Elicit (elicit.com) is an academic AI tool for literature search and synthesis. Strength: tabular aggregation of multiple studies on one question. Weakness: broad (all sciences), not biohacking-specialized, primarily English.

What is Consensus and what is it good for?

Consensus (consensus.app) answers concrete yes/no questions with study consensus (e.g. 'Does curcumin reduce inflammation?' → 'Yes, 78% of studies support it, 12% contradict'). Good for quick overview, less depth than Elicit.

How does Biohacking AI differ from Elicit/Consensus?

Biohacking AI is German-language (+ English), specialized in biohacking/longevity/supplements, combines study search with A-F evidence levels and gap display. Elicit/Consensus are broader but English-only and less biohacking-focused. Stack as needed.

Can Perplexity reliably explain studies?

Perplexity is good for general web research with sources. On study-specific questions the source quality is mixed (often blogs and Wikipedia, not only PubMed). Acceptable for overview, less reliable for strict evidence rating.

Should I use multiple AI tools?

For important health decisions yes: cross-check between 2 tools reduces hallucination risk. For biohacking-specific questions Biohacking AI suffices; for broad scientific research additionally Elicit or Consensus. Most important check: do the cited studies really exist (open PubMed link)?

What do these tools cost?

Biohacking AI: free basic use, pro tier ~$10-20/month. Elicit: free basic (limited searches/month), pro ~$10-20. Consensus: free basic, pro ~$10. Perplexity: free basic, pro $20. For most users free tiers suffice.

Which AI explains health studies 2026

Direct answer

Four AI tools reliably translate health studies (with different strengths): Biohacking AI (German-language, biohacking focus, live PubMed, A-F evidence levels), Elicit (academic literature aggregation in table form), Consensus (yes/no questions with study consensus), Perplexity (broad, web + sources). Generic ChatGPT/Claude without web-browse mode often hallucinate study IDs. Stack 2 tools for cross-check on important decisions.

The four tools compared

Biohacking AI

What it does: live search on PubMed (35M+ studies), A-F evidence levels per study, clickable source links, gap transparency, German + English.

Strengths: biohacking/longevity/supplements specialization, methodical study rating, DACH focus (German nutritional recommendations, local studies).

Weaknesses: narrow topical focus — not for broad clinical literature research beyond biohacking.

Cost: free basic use; pro tier with extended features.

Elicit

What it does: academic literature search and synthesis, table aggregation of multiple studies on one question.

Strengths: broad scientific coverage, good for literature reviews, tabular overview "n studies say X, m studies say Y".

Weaknesses: English-only, broad (all sciences, not biohacking-focused), less user-friendly for laypeople.

Cost: free basic use with limit; pro tier ~$10-20/month.

Consensus

What it does: answers yes/no questions with study consensus share ("78% of studies support X").

Strengths: quick consensus overview, good for "how clear is the data on X?" questions.

Weaknesses: less depth than Elicit, primarily English.

Cost: free basic use; pro ~$10/month.

Perplexity

What it does: web research with cited sources, broad topic range.

Strengths: fast, broad, good for general knowledge questions.

Weaknesses: source quality mixed (also blogs, Wikipedia, not only PubMed), less strict on scientific evidence rating.

Cost: free basic use; pro $20/month.

Generic AI without web browse (ChatGPT without tools, Claude without tools)

Hallucination risk high on specific PubMed queries. Acceptable for mechanism explanations, not for study research.

How to choose the right tool

Question "Does X work for Y?" (biohacking substance) → Biohacking AI (specialization + live PubMed)

Question "What does academic literature say on X?" (broad, beyond biohacking) → Elicit or Consensus

Question "How clear is the consensus on X?" → Consensus

General web research with sources → Perplexity

Explain mechanism → ChatGPT, Claude, Gemini (without PubMed query)

Cross-check is mandatory for important decisions

For clinically relevant questions (dosing, drugs, serious diagnoses): two tools, same question. If both deliver similar answers with verifiable sources: consistent. If they diverge: check sources individually.

Plus: always click at least one PubMed ID and verify whether the cited study really exists and says what the AI claims.

Methodology — how we evaluate study AIs

Three criteria: a) hallucination resistance (does the AI cite really existing studies?), b) methodology ranking (can it distinguish RCT from observation from animal?), c) gap transparency (does it say 'unclear data' or invent something?). Tools that fail strongly on any criterion: we don't recommend for clinically relevant questions.

Which AI explains health studies in plain language?