Prompt

I'm building a company intranet and want search to cover docs, chat, tickets, and CRM notes. What should I use?

Technology / Search & Discovery Tools1 observationLast seen Oct 13, 2026

Latest observation

Oct 13, 2026OpenAI APIWeb search: off

For an internal intranet search that needs to cover docs, chat, tickets, and CRM notes, you’ll usually want a single enterprise search / semantic search layer rather than trying to search each system separately.

Best fit in practice

1) Enterprise search platform

Good when you want fast rollout and connectors.

  • Examples: Elastic, OpenSearch, Algolia, Coveo, Glean
  • Pros:
    • Connectors for many SaaS tools
    • Full-text search, filters, permissions
    • Can blend sources into one result set
  • Cons:
    • Semantic relevance varies
    • Some platforms are expensive or SaaS-only

2) OpenSearch or Elasticsearch + ingestion pipeline

Good when you want control and can build it.

  • Index content from:
    • Docs: Google Drive, SharePoint, Confluence, Notion
    • Chat: Slack, Microsoft Teams
    • Tickets: Jira, Zendesk, ServiceNow
    • CRM notes: Salesforce, HubSpot, etc.
  • Add:
    • Metadata filtering
    • Access control trimming
    • Hybrid search = keyword + vector
    • Optional LLM reranking / answer generation
  • Pros:
    • Flexible, customizable
    • Can keep data on your own infrastructure
  • Cons:
    • More engineering effort

What I’d recommend

If you want the best balance for an intranet:

  • Search engine: OpenSearch or Elasticsearch
  • Vector search: built in or via a vector DB like pgvector / Pinecone / Weaviate if needed
  • Ingestion/connectors: custom jobs or a connector framework
  • Relevance: hybrid search + reranker
  • Security: document-level permissions from source systems

If you want minimal engineering:

  • Look at Glean or Coveo if budget allows

If you want open-source/self-hosted:

  • OpenSearch is a strong default
  • Pair it with a connector framework and hybrid ranking

Key requirements to plan for

No matter what you choose, make sure it supports:

  • Unified indexing across sources
  • Permission-aware search
  • Near real-time sync
  • Metadata filters like team, source, author, date, ticket status
  • Hybrid ranking
  • Auditability for enterprise use

Simple recommendation

  • Small/medium company, want quick deployment: Glean / Coveo
  • Want control and self-hosting: OpenSearch + connectors + hybrid search
  • Already on AWS: OpenSearch Service is a practical path

If you tell me:

  1. your stack (Google/Microsoft/Slack/Jira/Salesforce/etc.),
  2. number of users,
  3. whether you need self-hosting,
  4. and your budget range,

…I can suggest a more exact architecture and product shortlist.

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.

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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.

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