FullFind is a unified AI search engine for enterprises and teams that can simultaneously retrieve internal documents, databases, collaboration tools, and external Internet information, and aggregate, summarize, and reason the results through large language models.

FullFind: Unified AI Enterprise Search Engine

Core parameters and statistics

Project	Specifications
Product Name	FullFind
Category	AI Search Engine
Delivery form	SaaS cloud/private deployment
Support Platform	Web, API
Supported languages	zh-CN, en-US, ja-JP
Target users	Enterprise employees, IT operation and maintenance, knowledge management leaders
User scale	3,200+ registered enterprises, 200+ paying customers (as of 2026-07)
Pricing model	Free + Team ($499/month) + Business ($1,999/month) + Enterprise (customized)

Interpretation of core parameters: FullFind is positioned as an enterprise-level unified AI search layer. Its core value is to eliminate information silos within the organization - employees do not need to switch between multiple systems such as Confluence, Notion, SharePoint, Google Drive, etc., and can obtain cross-source aggregated results through a single search portal. The product supports two delivery forms: SaaS and privatized, adapting to the data security and deployment preferences of enterprises of different sizes.

User and market recognition

Dimensions	Data
Number of registered companies	3,200+
Number of paying customers	200+
Covering enterprise size	500-5,000 people
Industry distribution	Technology, finance, and manufacturing are the main areas
G2 Rating	4.5/5 (leading scores in search relevance and ease of deployment)
Average daily time savings	15-30 minutes per knowledge worker (based on Gartner statistical estimates)

It is estimated that FullFind can save each knowledge worker 15-30 minutes per day in information-finding time. Calculated for a 500-person enterprise, this is equivalent to releasing about 3,125-6,250 working days per year - based on Gartner's statistics "knowledge workers spend 20% of their working time on information retrieval". The actual benefits depend on the severity of the enterprise's information islands.

Cost advantage

Cost Dimension	Description
Free version	$0, 5 users, up to 3 connectors, basic keyword search
Subscription version	Team $499/month (50 users), Business $1,999/month (200 users)
Enterprise Edition	Customized quotation, unlimited users, privatized deployment, SLA guarantee

Cost comparison of competing products:

Compare Dimensions	FullFind	Glean	Algolia
Entry price	$0 (5 users)	Approx. $40,000+/year (500 people)	Approx. $30,000+/year
Average monthly fee per person (50 people)	~$10/month	~$35/month	Billed by search volume
Number of connectors	20+	50+	10+
Deployment method	SaaS / Privatization	SaaS / Privatization	SaaS / Privatization
Search type	Enterprise internal knowledge base	Enterprise knowledge search	Site/e-commerce search
AI Summary	✅ Support	✅ Support	❌ Basics

Compared with traditional enterprise search solutions (Elastic self-built + customized development, usually $30K-100K initial + $2K-5K/monthly operation and maintenance), FullFind lowers the threshold for obtaining search capabilities from "requiring a full-time search engineer" to "registration-ready". The Team version costs about $10/month per person, which is much lower than the typical per-person license fee for an enterprise-level knowledge management system ($20-50/month). Hidden costs: Connector configuration and search result optimization require certain configuration investment; privatized deployment has additional hardware and operation and maintenance costs.

Main functions

• Unified search portal: A single search box simultaneously searches internal knowledge bases (Confluence, Notion, SharePoint, Google Drive), document systems, databases and external web pages (custom crawlers), and search results are aggregated and sorted across sources.
• AI Intelligent Summary: LLM summary of search results, extract core conclusions and mark the source. In summary mode, users do not need to click on each document one by one to get an overview of the answers, reducing browsing time by 60-80%.
• Fine-grained permission filtering: Integrated with Azure AD / Okta, search results are dynamically filtered by user permissions - users can only see documents they have permission to access, and the system does not expose unauthorized summary content in search results.
• Knowledge graph relationship recommendation: Automatically generate a knowledge context diagram for related topics, display the relationships between different concepts, documents and projects, and assist exploratory learning.
• Custom crawler connector: The open SDK supports enterprise-built connectors, which can connect to internal Legacy systems, self-built databases and private file storage.
• Real-time index update: Automatically trigger re-indexing through the CDC mechanism, with the delay controlled within 5 minutes.

Model and version evolution

Version	Date	Key Changes
v1.0	2025-09	Initial version, Web search + basic API
v2.0	2026-03	Added 10+ connectors such as Notion, Confluence, SharePoint, etc.
v2.1	2026-06	Hybrid search mode (vector + keyword joint sorting), RBAC permission filtering, knowledge graph recommendation

Version records are subject to official release documents.

Technical advantages

• Dual-stage retrieval architecture: The first stage uses BM25 + vector retrieval to recall the Top 100 candidate documents in parallel, and the second stage uses the Learning-to-Rank model to re-rank. Control the delay within 300ms while ensuring the recall rate.
• Incremental Index Engine: Based on the CDC mechanism, source-side changes are captured in real time without the need to fully rebuild the index. For an enterprise with more than 1 million documents, full reconstruction takes 2-6 hours, and the incremental indexing delay is ≤ 5 minutes.
• LLM summary pipeline: RAG mode injects search results into a large language model to generate a summary, and supports custom Prompt templates to adapt to different summary styles (precise summaries of technical documents vs. conclusion-oriented summaries of management reports).
• Multi-layer permission filtering: Index layer (dividing visibility by connector/source system), retrieval layer (filtering candidates by user attributes), result display layer (permission verification of summary content), three-layer permission verification to avoid single points of vulnerability.
• Multi-cloud deployment plan: Supports AWS, Azure, GCP and private data center deployment. The enterprise version can specify the data storage region to meet data residency compliance requirements.

How to use

Entrance	How to use	Applicable people
Web search portal	Unified search interface, cross-source aggregation + AI summary	All employees
Web management background	Configure connectors, manage permissions, view analysis panels	IT/Administrator
REST API	Integrate into internal systems or build your own portal	Developers
Slack bot	Slash command search, message card return	All employees
Private Deployment	Complete Services for Internal Server Deployment	Enterprise IT

Typical usage flow: Administrator configures data source connector → System indexes and continuously synchronizes → Employees enter queries in the search portal or Slack → System returns cross-source aggregated results + AI summaries → Employees read summaries or click on source documents.

Product Pricing

Package	Price	Core Benefits
Free version	$0	5 users, up to 3 connectors, basic keyword search
Team Edition	$499/month	50 users, all connectors, AI summary, knowledge graph
Business Edition	$1,999/month	200 users, hybrid search, RBAC permissions, full API
Enterprise version	Customized quotation	Unlimited number of users, privatized deployment, SLA guarantee

Application scenarios

• Enterprise knowledge base search: When employees search for historical project documents, technical solutions or customer information, the search time is shortened from 3-5 minutes to 10-20 seconds. Verification: Compare the average daily time spent searching by employees before and after deployment.
• Legal and Compliance Review: The legal team searches for contract terms, compliance policies, and historical cases, improving review efficiency by 40%-60%. Verification: Track the review cycle of a single contract.
• R&D Technology Stack Query: Developers search internal Wikis, code comments, and external technical documents at the same time. Verification: Monitor how long developers spend on document search.
• New Employee Onboarding: New employees can quickly find company policies, team wiki, and project history. Verification: The time when a new employee completes a task independently for the first time.
• Customer Support: After the customer service inputs the customer question, the system automatically matches the best answer in the knowledge base. Verification: Compare the first response time before and after deployment.

Applicable people

Crowd	Adaptation value	Restrictions
Corporate employees	Search multiple internal systems with one click	Basic search keyword skills are required
IT/Operations team	Connector configuration, index management, permission policies	Basic API and directory service knowledge required
Knowledge Management Leader	Understand search blind spots through the analysis panel	Connector configuration needs to be maintained regularly
Enterprise Procurement Decision Maker	Assess search ROI and data security	Need to confirm connector coverage and SLA terms

Not suitable for the boundary: Enterprises with extremely single data sources have limited value; teams that use pictures/videos as the main knowledge carrier (multimodal search capabilities have not yet been perfected); scenarios that require real-time search (second-level delay) but have a 5-minute window for index synchronization.

Comparison of competing products

Compare Dimensions	FullFind	Glean	Algolia
Core differences	Unified search + AI summary, outstanding cost performance	More connectors (50+)	Site search + e-commerce search
Price range	$0-1,999/month	$40,000+/year (500 people)	$30,000+/year
Covered scenarios	Unified search in enterprise internal knowledge base	Enterprise knowledge search	Site/e-commerce search
Number of connectors	20+	50+	10+
AI Summary	✅ LLM Summary	✅ AI Summary	❌ Basics
User evaluation	G2 4.5/5, easy to deploy	Rich connectors, high price	High search accuracy
Technical threshold	Low (SaaS works out of the box)	Medium	Medium

Summary and Outlook

FullFind's core competitiveness lies in the combined experience of "multi-source unified search + AI summary", which has found a clear positioning range in the medium-sized enterprise market.

Core Advantages: Unified search reduces cross-platform search time costs; AI summaries reduce browsing time by 60-80%; three-layer permission filtering ensures data security; SaaS model has zero deployment threshold.

Current limitations: (1) There is a gap in the number of connectors (20+) compared to Glean (50+), and low-frequency systems such as SAP and Oracle have not yet been covered; (2) The multi-modal content indexing capability is not yet perfect - teams with pictures, whiteboards, and videos as the main carriers have limited coverage; (3) The specific delivery time and feature set of the enterprise version's privatized deployment need to be confirmed with sales.

Risk Disclosure: (1) Search relevance depends on connector configuration quality and document structure, and may require a 2-4 week tuning cycle after initial deployment; (2) The accuracy of AI summaries is affected by the underlying LLM, and it is recommended to set up manual review links in key scenarios; (3) Prices and functions are subject to official real-time information, and the SLA terms of the Enterprise version need to be specified in the contract; (4) The maintenance costs of connector SDK development need to be included in the team budget - self-built connectors require ongoing API adaptation work.

Purchase Suggestion: Start with the Team package, first connect to 3-5 core data sources and run for 2-4 weeks, and then expand after evaluating the search relevance, summary quality and permission filtering effect.

Related tools: perplexity, you-com

Version Info

• Enterprise Release ：Added new hybrid search mode, supports vector + keyword joint sorting, and optimized RBAC permission filtering. （2026-06-15）
• Connector Expansion ：New connectors for Notion, Confluence, and SharePoint. （2026-03-10）