AnySearch - Real-time structured search trusted by agents and developers

@emir_citak Thanks for your recognition. We adopt different update strategies for various vertical search areas in our self-built sources. Welcome to experience.

@emir_citak Glad you appreciated the hard benchmarks—we're tired of vague marketing fluff too! 🤝

To your question: you nailed it, the caching is absolutely domain-specific. Our Hierarchical Routing applies dynamic TTLs based on the vertical. Fast-moving data (like live finance) hits real-time feeds directly, while deep-research domains (like academic/legal) rely on specialized caching layers.

That’s exactly how we balance deep retrieval while keeping our overall latency incredibly low!

@emir_citak Thanks — really appreciate that. We also believe agent tooling is moving toward MCP, Skills, and API-first workflows, so that is where we are focusing.

And yes, freshness is domain-aware rather than one-size-fits-all. Fast-moving areas like finance or news need fresher sources and shorter refresh windows, while slower-moving but source-sensitive areas like academic, legal, patents, or documentation can use longer cache windows with more emphasis on source quality, structure, and provenance.

That helps us balance latency, cost, and reliability without treating every source the same way.

And thanks for noticing the benchmarks. We wanted to publish actual numbers because developers should be able to evaluate search infrastructure with real measurements, not just vague claims like “faster” or “smarter.”

@vaishnavi_goel Exactly, that's the part we're proud of. One bad info can suddenly break the result your agent gives. Let us know how it works for you!

@vaishnavi_goel That’s one of the core reasons we built AnySearch. Agents and AI workflows need trustworthy, structured information, not just more links. We’re working to help filter out low-quality signals before they enter the context window, so agents can reason with better inputs and hallucinate less. Would love for you to try it!

@madalina_barbu Thanks, Visit Website for more info

@lesley_liu2 Try it, I look forward to your feedback.

@lesley_liu2 Fast-changing docs are a great use case. AnySearch helps agents get real-time, accurate info instead of relying on outdated context. Hope you give it a try :)

@lesley_liu2 Absolutely. Coding docs are one of the clearest use cases.

A lot of agent mistakes come from stale examples, old APIs, or random blog posts outranking the current docs. If the agent can pull fresher, source-attributed docs and examples before acting, it has a much better chance of writing code that actually works.

@sezerdasekwcwb Great question.

AnySearch does not use one fixed “trusted source” whitelist. Trust is query-dependent.

For each query, we rank sources based on signals like relevance, source authority, freshness, content type, domain fit, and vertical context. A trusted source for financial data may be very different from one for academic papers, legal research, or developer documentation.

Developers can also constrain or bias retrieval toward specific domains, sites, verticals, or source types when those sources are already covered or publicly accessible.

For new sites, private sources, or domains that are not yet covered, tell us the use case and target source. We can evaluate the best way to support it as a custom or approved source.

So the default is query-aware source selection, while developers can still enforce their own provenance policy when needed.

@sezerdasekwcwb Just chiming in here to add—we totally get that 'black box' APIs are a nightmare for agent builders.

That's why, alongside the input controls mentioned above, we focus heavily on output transparency. AnySearch always returns strict citation metadata, giving your system full auditability. You never have to blindly guess where the data came from!

Let us know if you have specific domains in mind for your use case.

@conduit_design 
Appreciate the question! Honestly, the best way to see the difference is to try it out yourself — we built AnySearch to be as easy to use as possible. Visit the official website and register an account to obtain more free search credits. We look forward to your feedback.

@conduit_design Fair question. Parallel looks like a strong product, so I’d frame it less as “better in every case” and more as a different focus.

Parallel seems very strong around open-web search, extraction, and deep research workflows. With AnySearch, we’re focusing on being a broader retrieval layer for agents: web search, vertical sources, URL extraction, and agent-native integrations like APIs, MCP, and Skills, with source attribution and metadata that agents can carry through their workflow.

So if your use case is pure web research, I’d honestly benchmark both. If you want one pluggable search layer that fits into different agent workflows and source types, that’s where we think AnySearch becomes useful.

@conduit_design Heya, great question.

I’d frame the difference more around use case than “better or worse.” AnySearch is built as an agent-native search infrastructure layer that developers can plug into their own agents and products.

AnySearch can be called directly through MCP, Skill, and API, returns structured results, and routes across both general web and vertical sources like finance, academic, legal, business, code, health, patents, and more.

We also put a lot of emphasis on developer control, including source constraints, domain-level policies, provenance, and privacy-friendly usage.

The best way to compare is to try both with your own agent workflow and queries. We’d love for you to test AnySearch directly and see where it fits better for your use case.

@krekeltronics Good point on avoiding 'false certainty' in agent reasoning.

We currently use Entity Enrichment to separate raw facts from citations to preserve provenance. However, explicitly exposing 'freshness' and 'failure states' as first-class fields is an interesting angle to help agents reason better about the data quality.

We'll definitely consider this as we refine our API. Thanks for the feedback!

@ridhwikvinod Thanks, and totally agree with that distinction — “trusted by the tool” is not always the same as “trusted by your workflow.”

Yes, the goal is to let developers control source policy per query.

For new domains, private sources, or sources that are not yet covered, share the use case and target sources with us. We can evaluate the best way to support them as custom or approved sources.

Default ranking is useful when developers do not want to manage source selection manually, but when you already have your own trusted source list, your policy should take priority.

@ridhwikvinod Thanks so much for the congrats!

Just adding a quick thought to Nic's answer: since messy results are your main headache, the best part of pinning those 15 domains is the output format.

We handle the extraction and just hand your agent clean Markdown. No more wrestling with raw HTML or scraping those specific sites.

Let us know if you want to test it out with your list!

@sabber_ahamed The structured content AnySearch provides is in Markdown format, which can be directly used by Agents. Existing search is designed for human browsing, that's why Agents cannot browse and make decisions like humans. AnySearch is designed to address this issue.

@hazy0 Context bloat and duplication are exactly what kill agent reasoning—spot on.

To answer your question: Yes, you can absolutely scope it. We built Private Capability Isolation (currently Enterprise-only) specifically for this use case.

While the global routing is amazing for open-ended research, for a customer-facing support bot, you can pin the search strictly to your own docs or a whitelisted set of domains. We completely agree with you—having that hard boundary is non-negotiable for production safety.

@hazy0 That’s a great point, and I agree this is a key requirement for customer-facing agents. Today, AnySearch is closer to request-level source control: developers can constrain or bias retrieval for a specific query or workflow when they want the agent to search within a defined scope. Per-agent trusted-source policies, like pinning a support bot to only your own docs and a few approved domains, are a very valuable kind of operator-level control, especially as teams move from research agents to production agents. We want to think carefully about this capability rather than just add a shallow toggle. Your example is very helpful, and we’ll take it into account as we continue improving source control and provenance in AnySearch.