Top reviewed search products
Frequently asked questions about Search
Real answers from real users, pulled straight from launch discussions, forums, and reviews.
Corpus says yes — it can avoid storing user data by fetching results in real time instead of downloading or indexing your files. Key points from the team:
- No central storage: data is not downloaded, indexed, or stored; queries pull content live from connected apps.
- LLMs + search APIs: answers are produced on-the-fly using live APIs rather than a saved corpus.
- Enterprise caveat: some companies may restrict app connections — the vendor offers to discuss security and integration details with IT.
Confirm integration specifics and compliance with your security team before connecting sensitive systems.
Meilisearch can achieve sub-50ms, keystroke-level search in real projects — but only under the right setup. Key takeaways:
- Run the model locally to remove network latency; Meilisearch reports local inference for short queries often takes 1–5 ms per request.
- Use the same index and run the model on CPU for live search (GPU can be used for indexing) to keep hybrid/full-text + semantic queries fast.
- This is aimed specifically at short, few-token queries (search-as-you-type). If you rely on remote models or heavier queries, latency will rise.
If you need consistent <50ms, prioritize local inference and index tuning.
Perplexity is a great starting point for evidence-backed papers because it displays clickable citations so you can verify primary sources quickly. For large or internal collections, consider Meilisearch: its hybrid approach (full-text + vector) and flexible ranking rules produce results that are both lexically precise and semantically relevant, which helps surface high-quality, relevant papers. If you need to search across PDFs, emails, or notes, Cortex (or similar “second‑brain” tools) can pull documents from connected apps and applies checks to prefer the most relevant and up‑to‑date content.
- Use Perplexity to trace claims to original sources.
- Use Meilisearch for robust relevance on big corpora.
- Use Findr to unify internal documents and verify recency.