Legal counsel
Daubert Framework: FRE 702 + 707 Admissibility
Why JIL is admissible under Federal Rules of Evidence 702 and exempt from proposed FRE 707: deterministic rule engine, 332-check foundation library, documented error rates.
Daubert Framework
The 7 admissibility hurdles
JIL CREB must clear seven distinct legal hurdles to be admissible in court. This section outlines each hurdle and the current status of JIL's compliance.
| Hurdle | Federal Rule | What it tests | CREB status today | Engineering work to close |
|---|---|---|---|---|
| 1. Authentication | FRE 901-902 | The document is what it purports to be | Solved via 902(13)/(14) plus CourtChain | None for federal; some state variations |
| 2. Hearsay | FRE 801-807 | If statements by others are inside, an exception applies | Mostly solved via FRE 803(6) business records | Custodian certification template |
| 3. Best Evidence | FRE 1001-1008 | Original or admissible duplicate | Solved via hash-validated copies (FRE 1003) | None |
| 4. Relevance | FRE 401-403 | Probative value greater than prejudice | Case-specific | Per-finding relevance memo template |
| 5. Expert Testimony / Daubert | FRE 702 plus Proposed 707 | The methodology is scientifically valid | Partial: methodology documented but not yet packaged for Daubert hearing | Full Daubert foundation per check |
| 6. Predicate Facts | Statutory elements | Identification, amounts, dates, statutory elements | Partial: in CREB but not venue-formatted | Per-statute element-mapping templates |
| 7. Damages | Statutory damages formula | How the loss was computed | Mentioned in current CREB, not rigorously specified | Damages calculation engine with statute-specific formulas |
JIL is currently addressing each hurdle with targeted engineering work to ensure full compliance.
Deterministic Defense
Why deterministic is not machine learning
JIL's architecture is a deterministic rule engine, not machine learning. This distinction is critical for admissibility under evolving Federal Rules of Evidence.
JIL is not machine learning because it does not use any of the following:
- Model trained on historical fraud cases
- Neural network
- Gradient descent
- Statistical pattern recognition derived from training data
Instead, JIL uses structured data inputs, declarative checks, cross-source corroboration, and reproducible outputs.
Reliability Factors
FRE 702 reliability factors
JIL's methodology meets the reliability factors outlined in Federal Rule of Evidence 702.
The factors include:
- Whether the theory or technique has been tested
- Whether the theory or technique has been subjected to peer review and publication
- The known or potential error rate
- The existence and maintenance of standards controlling the technique's operation
- Whether the theory or technique has attracted widespread acceptance within a relevant scientific community
JIL's 332-check foundation library and documented error rates ensure it meets these reliability factors.
Commercial-Software Exemption
FRE 707 commercial-software exemption
JIL qualifies for the proposed FRE 707 exemption for routinely relied-upon commercial software.
The proposed rule exempts "the output of basic scientific instruments or routinely relied upon commercial software." JIL's deterministic rule engine and documented methodology align with this exemption.
Daubert Foundation
The 332-check Daubert foundation library
JIL's 332-check foundation library provides a robust Daubert foundation for each attestation check.
Each check is a formal rule expressed in declarative logic, with documented schema and verifiable sources.
Expert Witness
Expert witness bench
JIL maintains a bench of expert witnesses prepared to testify on the admissibility and reliability of CREB output.
These experts are equipped to address Daubert challenges and provide comprehensive testimony on JIL's deterministic architecture and compliance with Federal Rules of Evidence.