You're navigating one of the hardest things a person faces. You deserve real answers, not noise.
VERA is an AI research analyst that evaluates complementary cancer therapies using a rigorous evidence hierarchy — so you can walk into your next appointment informed.
VERA doesn't work for a hospital, a supplement company, or anyone with a stake in what you decide. She works for you — and her only job is to help you ask the right questions.
A scripted recreation of an actual session — a Stage IV pancreatic patient asks about high-dose IV vitamin C during FOLFIRINOX. Watch the scoping interview, the live source-by-source research, and the final report card. No buttons to press — it runs itself.
VERA isn't a chatbot wrapping a search engine. She runs a five-stage research protocol — every stage with named, file-enforced rules and an artifact written to disk. Skip any stage and the next one refuses to start.
One question per turn, VERA establishes the four scoping fields: cancer type and stage, current treatment, what you're trying to evaluate, and your contraindication context (medications, allergies, biomarkers, weight). Urgency does not skip scoping. "Just tell me — does it work?" gets the same calm "I need one more thing first." The scoping summary is the contract for everything downstream.
A 6-source fallback chain runs in order — Europe PMC, PubMed, ClinicalTrials.gov, Semantic Scholar, Unpaywall, WebSearch — and a parallel community scan covers Reddit, patient forums, and podcast transcripts so VERA knows what claims you're hearing online, not just what's published. Both sides of the literature are in the evidence ledger before any synthesis begins.
A 6-tier hierarchy tags every source before it can be cited: T1 systematic reviews and meta-analyses, T2 randomized controlled trials, T3 observational studies, T4 case reports, T5 grey literature, T6 anecdotal. A source without a tier doesn't enter the ledger. Tier drives weight; weight drives the verdict.
Every Tier 1 and 2 source is checked for industry funding, author conflicts, and structural bias (geographic capture, ideological capture, publication bias). Then a second AI sub-agent runs the audit-brief protocol against the finished ledger — looking for missed searches, weak sources cited as strong, hand-waved gaps. Phase 3 cannot start until the audit clears.
A 6-page report. Page 1 hits the patient first: verdict in two sentences, a two-question dashboard ("will it help / could it hurt"), and the counts that drove the answer. Pages 2–4 are patient-facing at sixth-grade reading level — findings, gaps, and the specific questions to ask your oncologist. Pages 5–6 are the technical brief for the doctor: tier-tagged evidence, COI flags, hyperlinked references. Print it. Walk in informed.
She evaluates the published literature on complementary therapies with consistent, rigorous criteria — the same standard for everything she reviews.
VERA is a research tool, not a clinician. She surfaces evidence; she does not interpret it for your specific medical situation.
No "you should take this." VERA presents what the evidence says and where it's strong, weak, or absent — full stop.
No pharma relationships. No institutional bias. No agenda. VERA's only objective is to help you ask better questions.