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Dashworks

What it is

An AI-powered search and knowledge management platform designed for teams to find information across all their internal apps.

What problem it solves

Eliminates information silos by providing a unified interface to search through Slack, Google Drive, Jira, Confluence, and other enterprise tools.

Where it fits in the stack

Category: Enterprise AI / Knowledge Management

Typical use cases

  • Internal Knowledge Retrieval: Finding specific documents, messages, or tickets across multiple platforms.
  • Onboarding: Helping new employees find relevant information and answers to common questions.
  • Executive Summarization: Getting a quick overview of project statuses or meeting notes from various sources.

Getting started

Dashworks is a SaaS platform. Integration typically involves connecting your enterprise apps via their web dashboard. For developers, the Dashworks API allows for programmatically querying the knowledge base and managing users.

Technical Examples

Querying the Knowledge Base (cURL)

You can use the Dashworks Search API to retrieve answers across all connected sources.

curl -X POST https://api.dashworks.ai/v1/search \
  -H "Authorization: Bearer $DASHWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What is our policy on remote work?",
    "stream": false,
    "filters": {
      "sources": ["slack", "confluence"]
    }
  }'

Python SDK Example

Using the requests library to interface with Dashworks:

import requests
import os

DASHWORKS_API_KEY = os.getenv("DASHWORKS_API_KEY")

def ask_dashworks(question: str):
    url = "https://api.dashworks.ai/v1/search"
    headers = {
        "Authorization": f"Bearer {DASHWORKS_API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "query": question,
        "max_results": 5
    }

    response = requests.post(url, json=payload, headers=headers)
    response.raise_for_status()
    return response.json()

# Example usage
answer = ask_dashworks("Who is the project lead for Alpha?")
print(answer['summary'])

Strengths

  • Wide Integration Support: Connects to 100+ popular enterprise applications.
  • Personalized Results: Learns from user behavior and permissions to provide relevant answers.
  • Privacy-First: Built with enterprise security and data privacy in mind.

Limitations

  • Subscription Cost: Enterprise pricing model.
  • Setup Complexity: Requires administrative access to multiple third-party systems for full effect.

When to use it

  • When your team spends too much time searching for information across different apps.
  • When you need a "single source of truth" for internal knowledge.

When not to use it

  • For small teams with very few documents or apps.
  • If you prefer a completely local, self-hosted search solution.

Licensing and cost

  • Open Source: No
  • Cost: Paid (SaaS)
  • Self-hostable: No
  • Glean — primary competitor in enterprise search.
  • Guru — knowledge management with verification focus.
  • Coveo — enterprise-grade search and recommendations.
  • Notion AI — AI search within Notion workspaces.
  • Elastic — underlying search technology for many enterprise tools.
  • Langfuse — observability for AI queries.
  • Knowledge Management — core concept and patterns.

Sources / references

Contribution Metadata

  • Last reviewed: 2026-05-23
  • Confidence: high