Validation Maturity Levels
Every evidence pack in BrewBio is assigned a maturity level that reflects how thoroughly its outputs have been evaluated. These levels are progressive: each builds on the requirements of the previous.
Concept
Level 1The pack has been designed and its evidence architecture defined, but outputs have not yet been systematically tested. Source integrations may be provisional. Suitable for internal exploration and design iteration only.
What this entails
- Evidence source architecture documented
- Prompt chains and output schema drafted
- Initial source integration configured
- No systematic output evaluation completed
Internally Validated
Level 2The pack has undergone internal evaluation against a test matrix of representative inputs. Outputs have been reviewed for factual accuracy, citation integrity, and structural completeness by the BrewBio development team. Known edge cases are documented.
What this entails
- Evaluated against 10+ representative input scenarios
- Citation accuracy verified for all evidence sources
- Output structure and completeness reviewed
- Edge cases and failure modes documented
- Confidence calibration assessed on test set
SME Reviewed
Level 3One or more subject matter experts with relevant domain credentials have reviewed pack outputs for scientific accuracy, regulatory plausibility, and practical utility. SME feedback has been incorporated and documented.
What this entails
- Reviewed by 1-3 credentialed domain experts
- Scientific accuracy validated against expert knowledge
- Regulatory claims checked for plausibility and currency
- SME feedback incorporated into prompt engineering
- Review documentation and reviewer credentials on file
Production Approved
Level 4The pack meets all internal quality gates for production use. It has passed internal validation, SME review, and has been evaluated for consistency, reproducibility, and appropriate confidence calibration across diverse inputs. Version-locked for stability.
What this entails
- All Internally Validated and SME Reviewed criteria met
- Reproducibility tested across 50+ diverse inputs
- Confidence scores calibrated and validated
- Output consistency verified across repeated runs
- Version locked with semantic versioning
- Change control process established for updates
Evidence Integrity
The foundation of BrewBio is the principle that every factual claim in an output must be traceable to a specific piece of evidence. Here is how that works in practice.
Every Claim Links to Evidence
BrewBio outputs include inline citations that trace each factual claim back to a specific evidence source. Sources include peer-reviewed publications, regulatory guidance documents, clinical trial registries, and structured databases. No claim is presented without an associated evidence reference.
Transparent Source Quality
Each evidence source is annotated with its type (regulatory, literature, registry, database), refresh frequency, and the date it was last accessed. Users can evaluate whether the evidence supporting any given claim meets their own quality thresholds.
Immutable Evidence Snapshots
When a pack execution occurs, the evidence context used to generate the output is snapshotted. Even if underlying sources are updated later, the provenance record for that execution remains intact, preserving the exact evidence basis for audit purposes.
Provenance Tracking
BrewBio maintains a complete chain of custody from raw evidence source to final output. This provenance chain is designed to support audit requirements and regulatory inspection readiness.
Source Ingestion
Evidence is retrieved from authoritative sources (FDA, PubMed, ClinicalTrials.gov, etc.) with access timestamps and content hashes.
Context Assembly
Relevant evidence fragments are selected, ranked, and assembled into a structured context window for the AI model.
Output Generation
The model produces structured output with inline citations. Each citation maps to a specific evidence fragment from Step 2.
Provenance Record
A complete provenance record is created linking the output, model version, evidence snapshot, and execution parameters.
Confidence Scoring
BrewBio assigns confidence scores at two levels: per-evidence and per-section. These scores are not arbitrary: they reflect measurable properties of the underlying evidence and generation process.
Per-Evidence Confidence
Each evidence fragment used in output generation receives an individual confidence score based on:
- Source authority — Regulatory guidance scores higher than unreviewed preprints
- Recency — More recent evidence is weighted appropriately for domains where guidance evolves
- Specificity — Evidence that directly addresses the query context scores higher than tangential matches
- Corroboration — Claims supported by multiple independent sources receive a boost
Per-Section Confidence
Each section of the output report receives an aggregate confidence score derived from:
- Evidence density — Sections with more supporting evidence fragments receive higher base scores
- Citation coverage — The proportion of factual claims with direct citations affects the section score
- Weighted average — Individual evidence confidence scores are aggregated with source-authority weighting
- Gap penalty — Sections where the model generates content without strong evidence support receive a confidence penalty
Important:Confidence scores represent the system's assessment of evidence quality and coverage. They do not guarantee factual accuracy. A high-confidence score means the output is well-supported by its evidence sources, not that it is necessarily correct in all contexts. Human review remains essential.
Human Review Model
AI-generated intelligence is a starting point, not an endpoint. BrewBio integrates structured human review at multiple stages to ensure outputs meet scientific and regulatory standards.
Pack Development Review
During pack creation, domain experts review evidence source selection, prompt design, and output structure to ensure the pack is designed to produce scientifically sound results.
SME Output Validation
Subject matter experts with relevant credentials review representative outputs for accuracy, regulatory plausibility, and practical utility. Reviewers are documented and their credentials recorded.
User-Level Review
Every output is presented with confidence scores, evidence citations, and provenance data so that end users can exercise their own professional judgment before acting on any recommendation.
Export Traceability
When outputs are exported as PDF, DOCX, or other formats, the audit trail travels with the document. Exported reports are designed to be inspection-ready.
Embedded Metadata
Export files include embedded metadata: execution ID, pack version, generation timestamp, model identifier, and evidence snapshot hash.
Citation Appendix
Every exported document includes a citation appendix listing all evidence sources referenced, with access dates and source URIs where available.
Confidence Summary
Exported reports include a confidence summary table showing per-section confidence scores and overall output confidence.
Provenance Footer
Each page of exported PDFs includes a provenance footer with the execution ID and generation timestamp for traceability.
Version Control
Both evidence packs and their outputs are version-controlled to support reproducibility and change management.
Pack Versioning
- Packs use semantic versioning (MAJOR.MINOR.PATCH)
- Major versions indicate changes to evidence sources or output schema
- Minor versions reflect prompt refinements or additional source integration
- Patch versions address formatting, typo, or minor quality fixes
- Deprecated versions remain accessible for historical reference
Output Versioning
- Every execution creates a uniquely identified output version
- Re-running a pack with the same inputs creates a new version, not an overwrite
- Output versions record the pack version used at generation time
- Users can compare outputs across versions to see how results evolve
- Outputs are immutable once generated: annotations and reviews are additive
Limitations & Disclaimers
Transparency about limitations is central to BrewBio's approach. Users should understand what this platform is and what it is not.
What BrewBio Is
- An evidence aggregation and intelligence platform that synthesizes publicly available regulatory, scientific, and clinical data
- A tool designed to accelerate research and analysis by qualified professionals
- A system designed for SOC 2 readiness with audit trail capabilities
- A starting point for professional analysis that requires human review and judgment
What BrewBio Is NOT
- Not a medical device. BrewBio is not FDA-cleared, CE-marked, or approved as a medical device. It does not provide clinical diagnoses, treatment recommendations, or patient-level decision support.
- Not legal or regulatory advice. Outputs should not be treated as legal opinions or as a substitute for qualified regulatory counsel. Regulatory landscapes change, and local requirements may differ.
- Not a replacement for professional judgment. All outputs are intended to inform, not replace, the professional judgment of qualified scientists, clinicians, and regulatory professionals.
- Not guaranteed to be error-free. AI-generated content may contain inaccuracies, hallucinations, or outdated information despite confidence scoring and validation processes. Critical decisions should always be independently verified.
- Not SOC 2 certified. The platform is designed with SOC 2 readiness in mind but has not completed third-party SOC 2 certification at this time.
By using BrewBio, you acknowledge that outputs are generated by AI systems and require professional review before use in any regulatory submission, clinical decision, or business action. BrewBio and its operators accept no liability for decisions made based on platform outputs without appropriate professional review and independent verification.
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