Make evidence authority explicit
Give applications a stable contract for verified evidence, contradictions, missing proof, provenance, and generation permission.
Independent laboratory
Build AI that knows when not to answer.
Confidence is not evidence.
Modern models can explain almost anything. Business systems need a separate mechanism to decide what they are permitted to explain.
Models remain replaceable
Retrieval engines and LLMs may improve or change. The evidence relationship, audit record, and refusal boundary should remain inspectable.
Panini-inspired, engineering-first
The project borrows the principle of reducing many surface expressions into canonical roles and applying explicit ordered rules. Public claims are based on implemented software and measured tests, not cultural branding alone.
Operating principles
What the laboratory refuses to fake.
The fastest way to lose trust is to present a synthetic result as customer proof or a research module as production capability.
Label simulations
Public demos state whether private core, customer data, or an LLM was used.
Attach boundaries
Every benchmark states fixture, method, scale, and remaining uncertainty.
Fail closed
Missing proof and unresolved conflicts do not become confident prose.
Protect the core
Public contracts are inspectable; proprietary rule implementations and private evidence remain server-side.
Current maturity
A serious prototype seeking serious evaluation.
PAIL is ready for public demonstration and controlled design-partner testing. It is not represented as a certified enterprise platform.
Public-safe evidence lab
Test deterministic conflict, refusal, token, and trace-isolation contracts with synthetic or sanitized records.
Open the lab →Private local runtime evaluation
Install a local node or connect a protected runtime for bounded file ingestion and guarded queries. Data terms are agreed before confidential use.
Discuss an evaluation →Evaluate the claim
Bring a workflow where the wrong record would damage trust.
Start with sanitized data and a known-answer test set. We will measure releases, refusals, conflicts, latency, and context size.