Long-form clinical discussions
Hours of working clinicians walking through real dosing logic — half-life math, cycling rationale, titration paths, and the protocol nuance you only get from people who treat patients daily.
The Knowledge Spine
10,000+ Hours of Practitioner Expertise — Behind Every DoseCraft Answer
DoseCraft’s AI doesn’t hallucinate compound mechanics because it isn’t guessing. It’s grounded in a proprietary corpus we spent years assembling — long-form clinical discussions, bloodwork case reviews, mechanism deep-dives, and Q&A archives from seven anchor practitioners with 150+ years of combined clinical experience. Cross-referenced. Tagged across 90+ compounds. Wired into five specialized AI agents.
Not a PubMed roll-up. Not a ChatGPT wrapper. Not Reddit consensus. A real knowledge spine, curated by hand.
10,000+
Hours of practitioner expertise
90+
Compounds covered, three evidence lanes each
7
Anchor practitioners cross-referenced
150+
Years combined clinical experience
5
Specialized AI agents grounded in corpus
What’s Inside
Four Layers of Clinical Reasoning
The corpus isn’t flat text. It’s structured across four content types so the AI can pull the right kind of reasoning for the question.
Bloodwork & case reviews
Anonymized lab interpretation, side-effect troubleshooting, and protocol adjustment reasoning. The exact clinical judgment that separates a 'safe' protocol from an 'effective' one.
Compound deep-dives & mechanism reviews
Pharmacology breakdowns from practitioners who've prescribed the compound for years — mechanism of action, evidence tier, contraindications, real-world drug interactions.
Practitioner Q&A archives
The questions other researchers actually ask — and the answers experienced clinicians actually give. The dosing edge cases that aren't in any textbook or PubMed abstract.
Why It Beats The Alternatives
What Makes This Structurally Different
Every other peptide AI is grounded in something else. Here is what they pull from — and why it falls short for protocol-level questions.
| Dimension | PubMed | ChatGPT | DoseCraft | |
|---|---|---|---|---|
| Source authority | Mostly preclinical animal studies | General training data, no peptide focus | Anecdotal, no clinical curation | Working clinicians who treat patients |
| Compound dosing nuance | Rarely covers human protocols | Hallucinates dosing + half-life regularly | Conflicting bro-science | Clinician-validated, cross-referenced |
| Cycling & stacking logic | Almost never | Generic, not peptide-specific | Wildly inconsistent | Real-world protocol patterns |
| Bloodwork interpretation | Reference ranges only | Generic medical training | Unqualified speculation | Clinician case-review reasoning |
| Side-effect resolution | Lists, not solutions | Boilerplate disclaimers | Try-this-supplement spam | Clinical troubleshooting playbooks |
How It Powers Everything
Five AI Agents, One Knowledge Spine
Every DoseCraft AI agent pulls from the same corpus, with role-specific retrieval. Different question, same grounded source.
Stack Builder
Designs multi-compound protocols grounded in interaction-overlap logic from the corpus.
Protocol Auditor
Reviews user protocols against clinician-validated cycling, dosing, and titration patterns.
Safety Checker
Flags contraindications, interactions, and dose-frequency mismatches before they ship.
Protocol Advisor
Surfaces clinician reasoning for compound selection given a researcher's stated goal.
Bloodwork Interpreter
Reads lab panels through the lens of practitioners who've reviewed thousands of them.
The agents do not invent compound mechanics, half-lives, or interaction rules. They retrieve from the corpus, cite the reasoning, and let the researcher decide. That is what makes DoseCraft answers checkable — and reproducible.
Curation Discipline
Five Steps Between A Practitioner’s Reasoning And Your AI Answer
01
Anchor practitioner selection
Seven anchor practitioners chosen on clinical track record, peer reputation, and depth of long-form teaching output. We do not aggregate from anyone whose work we have not reviewed end-to-end.
02
Cross-reference before acceptance
No single source becomes corpus truth. A claim has to appear in multiple practitioners' reasoning — or be explicitly debated — before it lands in the AI grounding layer. Outliers get flagged, not promoted.
03
Tagging by compound + concept
Every passage is tagged across the 90+ compound matrix and a concept ontology (PK, mechanism, cycling, contraindications, interactions, dosing forms). This is what makes the AI agents queryable instead of generic.
04
Outdated guidance retirement
Clinical thinking evolves. When the field updates a standard (e.g., GLP-1 titration timelines, BPC-157 vendor cautions), older corpus passages get retired or annotated. The AI never quotes deprecated logic.
05
Ongoing expansion
The corpus is not a one-time build. It expands monthly as anchor practitioners publish new long-form material. DoseCraft Pro subscribers ride the same growth curve.
Editorial Standards
What We’re Not Doing
We Do
- Cite the practitioner reasoning behind every protocol claim
- Cross-reference between multiple anchors before promotion
- Retire deprecated guidance as the field evolves
- Frame everything as research-only, not therapeutic advice
We Don’t
- Synthesize protocols from a single anonymous source
- Treat PubMed abstracts as protocol authority
- Surface Reddit consensus as clinical guidance
- Hand the AI generic ChatGPT training and call it expertise
Ask The Corpus Anything
The five AI agents are wired into DoseCraft Pro. Every protocol you build, every interaction you check, every bloodwork panel you read — grounded in the same 10,000+ hour spine.
For research use only. DoseCraft is a research-only platform. Information surfaced by the corpus is not therapeutic advice and has not been evaluated by the FDA to diagnose, treat, cure, or prevent any disease. Compound information is for in-vitro investigation only. Practitioners cited in our corpus have not endorsed individual user protocols and DoseCraft does not represent itself as a clinical service.