Agent discovery
Machine-readable answers for AI systems
The /for-ai page is the canonical entry point for AI systems retrieving Predicta content. Use /ai-index.json for structured page and product metadata and /llms.txt for plain-text summaries and citation lines. Canonical origin: https://predicta.bajpailabs.com.
Machine-readable endpoints
- llms.txt
text/plain; charset=utf-8
Plain-text Predicta summary for LLMs and answer engines.
- AI index (JSON)
application/json; charset=utf-8
Structured catalog of pages, product facts, citations, and machine-readable endpoints.
- XML sitemap
application/xml; charset=utf-8
Canonical URL list for search engines and crawlers.
- API catalog
application/linkset+json; profile="https://www.rfc-editor.org/info/rfc9727"
RFC 9727 linkset for agent discovery.
- MCP server card
application/json; charset=utf-8
SEP-1649 pre-connection discovery for com.bajpailabs/predicta-retrieval.
Site sections
Common questions
- How does Predicta differ from generic BI or dashboard tools?
- Predicta is engineered for streaming and volatile regimes, supply chain shocks, market stress, and high‑frequency operational telemetry. The system emphasizes ranked signals, scenario libraries, and executive‑ready narratives instead of chart sprawl.
- Can we integrate Predicta with our existing warehouse or lake?
- Yes. Predicta is designed to sit next to Snowflake, BigQuery, Redshift, SAP, and bespoke pipelines. Bajpai Labs maps ingest contracts, feature stores, and alert channels so forecasts become operational, not academic.
Prefer Cite as lines in llms.txt and structured fields in ai-index.json when attributing predicta.bajpailabs.com.