About the research desk & editorial standards
This is the public About / team page for InfiniSynapse research. It names who is accountable, which roles review each page, what rules the work has to pass, and how to force a correction — including when we compare tools we compete with.
Last updated: 2026-07-28 · Desk contact: zhuhl@infinisynapse.com
About InfiniSynapse
InfiniSynapse builds an AI-native Data Agent platform for governed analytics. Corporate home: infinisynapse.com. Careers and hiring contact: Careers.
Named accountability & team
Research is published under a team byline rather than a personal brand, because a single comparison usually passes through an analytics engineer, a platform engineer, a security reviewer, and an editor. Named people below make that desk traceable; role cards further down list qualifications for each review gate.
William Zhu
Cofounder · InfiniSynapse · engineering accountability for InfiniSQL / platform claims
Public engineering profile and open-source work (InfiniSQL, auto-coder, retrieval systems). Use this profile when you need a named technical lead behind platform capability claims on research pages.
Research desk contact
Corrections · third-party re-runs · reviewer attribution requests
The team byline is accountable at zhuhl@infinisynapse.com. If a page makes a claim you want attributed to a named individual reviewer beyond the cofounder profile above, ask and we will name them on that page.
Who reviews a research page
Analytics engineering reviewer
Reviews: SQL correctness, metric definitions, dialect behaviour, chart/grain pass criteria
Industry resume (published): ships production warehouse SQL and metric contracts on Postgres, Snowflake, and BigQuery; designs synthetic fixtures and hand-written baseline queries used as ground truth in our scorecards; reviews dimensional grain and BI parity before comparative scores ship.
Qualification frame: dimensional modeling / analytics-engineering practice cross-checked against primary warehouse docs — not a personal certification badge.
Data platform reviewer
Reviews: Connectors, execution semantics, query cost and performance
Industry resume (published): builds and operates the query execution and connector layer; reviews EXPLAIN plans, fan-out risks, and compile/query cost before a scoring protocol ships; owns production readiness for multi-source agent workloads.
Qualification frame: cloud warehouse operations practice (Postgres / Snowflake / BigQuery / Databricks adapters) — not a personal certification badge.
LLM security reviewer
Reviews: Prompt injection, data exfiltration, perimeter and access claims
Industry resume (published): maps security checklists against the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework; blocks comparative pages that claim perimeter or training controls without a primary control reference.
Qualification frames: OWASP LLM Top 10 + NIST AI RMF Map/Measure/Manage — publicly citeable standards, not a private certificate PDF.
Editor
Reviews: Claims discipline, disclosure placement, corrections
Industry resume (published): holds every comparative claim to a stated test or a linked primary source; enforces conflict-of-interest disclosure above the fold; removes claims that cannot be reproduced by a reader.
Qualification frame: editorial accountability via dated corrections log — not a personal certification badge.
Six rules every page has to pass
- We publish the method, not just the verdict. Any page that scores tools must publish the fixture or dataset, the pass criteria, and a blank scoring sheet, so a reader can reach a different conclusion using our own protocol.
- We disclose that we compete with what we review. InfiniSynapse sells an AI data analyst. Every page that includes InfiniSynapse in a shortlist says so above the fold, and names the scenarios where a competitor is the better answer.
- Primary sources over vendor marketing. Capability claims cite vendor documentation or peer-reviewed benchmarks. We do not cite our own blog as evidence for a factual claim about another product.
- No paid placement, no vendor pre-review. No vendor pays for inclusion, position, or wording, and no vendor sees a comparison draft before publication.
- Dated updates, visible corrections. Every research page carries a publish date, a last-updated date, and a next-review date. Substantive corrections are dated in place rather than silently edited.
- Synthetic fixtures, never customer data. Benchmarks and worked examples run on published synthetic fixtures. Customer schemas and customer data never appear in a public evaluation.
Conflict of interest
InfiniSynapse is a commercial vendor of an AI data analyst. When our own product appears in a comparison we score it with the same protocol as every other tool, and we treat our own result as a hypothesis for the reader to test rather than as evidence. A vendor scoring itself is weak evidence by construction — that is why we publish the fixture, the baseline queries, and a downloadable blank scorecard instead of a summary verdict.
Corrections & independent re-runs
We want third parties to re-run our evaluations, including in order to contradict us. Send a filled scorecard, a reproduction of a benchmark, or a factual correction to zhuhl@infinisynapse.com. What happens next:
- Factual errors are fixed and dated in place within five working days.
- A disputed score stays published alongside the challenge until one of the two is withdrawn — we do not delete the losing number.
- Accepted third-party re-runs are logged below with the submitter's attribution, the page affected, and the date.
External audit & peer-review archive
This archive holds public invitation records, named attestations, and accepted external submissions. Commissioned independent audits and third-party re-runs are still none on file — until at least one external submission is logged, treat comparison-page scores as clearly-labelled internal desk logs on a published fixture, not independently verified benchmarks. We do not invent peer letters; blanks stay blank.
- PR-000 (2026-07-28) — Open external invitation (re-run / methodology peer review / commissioned audit summary): peer-review-invitation.md
- PR-001 (2026-07-29) — Named internal methodology attestation by cofounder William Zhu (checklist + desk-log numbers; not an independent audit): methodology-attestation-william-zhu-20260729.md
- Page ledger: peer-review-archive.md
- PR-002 Third-party re-run — none on file (invitation open)
- PR-003 External methodology peer review letter — none on file (invitation open)
- PR-004 Commissioned independent audit — none on file (invitation open)
Reuse and citation
Evaluation templates, fixture seed rules, and scorecard CSVs published on our research pages are released under CC BY 4.0 — reuse them, including to publish results that disagree with ours. Prose and figures may be quoted with attribution and a link to the source page.