Prompt
What should I use for a managed search API?
Latest observation
If you want a managed search API, the best choice depends on what you’re searching and how much relevance tuning you need. Here are the main options:
Good general-purpose choices
- Algolia — Best for fast, typo-tolerant, user-facing search on websites/apps. Great developer experience and relevance controls.
- Elasticsearch / OpenSearch (managed) — Best if you need full-text search, complex filtering, analytics, or custom ranking. More powerful, but more operationally and conceptually heavy.
- Typesense — Simpler than Elasticsearch, easy to use, fast, and good for product/site search.
- Meilisearch — Very easy to get started with, great for lightweight search experiences and small-to-medium datasets.
If you mean enterprise/document search
- Azure AI Search — Strong if you’re already in Microsoft/Azure, especially for document indexing and AI-powered retrieval.
- Amazon OpenSearch Service — Good if you’re on AWS and want managed Elasticsearch/OpenSearch.
- Google Vertex AI Search / Elastic on cloud — Good for hybrid search and AI-integrated experiences.
Quick recommendation
- Need the easiest, best UX for app/site search: Algolia
- Need powerful search and control: OpenSearch / Elasticsearch
- Need simple and cheaper: Typesense or Meilisearch
- Already on cloud provider: use that provider’s managed search
If you tell me:
- what you’re searching (products, documents, logs, code, etc.),
- your cloud provider,
- your scale/budget,
- whether you need semantic/vector search,
…I can recommend the best one more specifically.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.