The strongest current use case is exact or typed evidence: transactions, orders, incidents, policy versions, device events, and structured records. Broad questions over novels, image-heavy documents, or open-domain knowledge still need stronger semantic or multimodal retrieval.
Vector databases, SQL, keyword search, graph traversal, and metadata filters remain candidate locators. PAIL checks whether retrieved evidence belongs together and may support the answer. Poor recall upstream can still leave PAIL with nothing to verify.
The public generation path requires citations to released evidence IDs and withholds uncited prose. A model can still misread a cited record. High-risk deployments need a stronger answer verifier, domain tests, and human review.
Shared identifiers, timestamps, state transitions, and cause fields can build a useful timeline. They do not prove physical or organizational causality. PAIL should label suspected cause and missing proof, not declare certainty.
Text PDFs, DOCX, CSV, JSON, logs, and text files are supported by the private runtime when optional parsers are installed. Scanned PDFs need OCR. Complex tables, charts, handwriting, and layout may be extracted incompletely.
The Panini-inspired layer supplies canonical roles, ordered transformations, constraints, relation checks, and conflict behavior. It does not make Sanskrit grammar a replacement for multilingual semantic models. An optional normalizer may still be needed for unconstrained natural language.
Large noisy candidate sets can shrink substantially. Tiny exact answers may cost more after control headers and provenance. Exact counts depend on the selected tokenizer and should always report source tokens, packet tokens, and method.
It accepts sanitized inputs only, limits files and bytes, provides ten protected queries per account, and expires each corpus in 24 hours. This is an evaluation surface, not a production data room.
There is no independent penetration test, production SLA, multi-region recovery proof, customer UAT, or regulated-industry approval. Production adoption requires dedicated infrastructure, identity, managed keys, monitoring, backups, load tests, and a written operating model.
Symbolic or acoustic features must never overturn deterministic identity and relation evidence. Physical sound storage, crystal resonance, and broad semantic advantage are not production claims of this release.