Comparison · Outmind vs. Sinequa
Both Sinequa and Outmind enable users to connect, search, and leverage corporate knowledge using AI. The main difference between them lies in their product philosophies: Sinequa offers a very broad and highly configurable Enterprise AI platform, while Outmind combines a search engine, RAG, and AI assistants into a modern experience designed for everyday use and to continuously evolve with new AI applications.
For companies whose knowledge is stored on file servers, SharePoint, in emails, archives, and document management systems, Outmind makes this content immediately accessible to teams and their current and future AI systems.
Deterministic and semantic search · AI-generated answers with sources · Access rights respected · File servers without migration.
Verified Access Rights
On which projects have we already performed underpinning work?
18 results · 4 sources
NDC_underpinning_P2.pdf
“… underpinning with micropiles, carried out in four phases …”
CCTP_South_Island_v4.docx
“… underpinning of the existing foundations …”
REX Construction Project: Lyon Office Building
“… the underpinning work stayed on schedule despite water seepage …”
Outmind Assistant
3 sources
Three projects are relevant: Pont de la Loire (2019), Lyon Commercial Expansion (2021), and Îlot Sud Renovation (2023). The calculation sheets and technical specifications are included in the project files.
SharePointCCTP_South_Island_v4.docxOutlookREX Construction Project: Lyon Office Building, 2021Response based on the research findings
Both platforms now address advanced enterprise AI and research needs. The difference lies in their scope, the product experience, and how you want to evolve your AI architecture.
Criterion
Sinequa
Outmind
Positioning
A highly comprehensive Enterprise AI platform, billed as “The Knowledge Engine for the AI-Powered Enterprise”
A modern platform for research, knowledge, and RAG
Keyword and Semantic Search
Yes, hybrid neural network research
Yes, a combination of deterministic and semantic search
AI Answers with Sources
Yes
Yes
Source Access Rights
Yes
Yes
Connector Catalog
Sinequa has announced over 200 connectors
A catalog focused on the main collaborative and documentary sources
File servers, SharePoint, Microsoft 365, iManage
Yes
Yes, with file servers as the primary use case, without prior migration
Structured Data and Business Applications
Extensive coverage
Cover art from the Outmind catalog
Selecting AI Models
Platform announced as LLM-agnostic
Recent models are available; the choice of language model depends on the offering and configuration
Agents and Orchestration
Extended Agent-Based Orchestration Offering
Agent-based operations and domain-specific assistants, focused on knowledge and retrieval
Deployment
SaaS, private cloud, and on-premises
Hosting in Europe, one dedicated instance per customer, advanced options depending on the plan
Business Model
Based on a quote
Pricing based on indexed data volume and usage, not on the number of users
Natural Fit
Large-scale enterprise AI projects, highly customized architectures
Literature review, project documentation, engineering, construction, legal affairs, and knowledge management
Sinequa capabilities listed on Sinequa’s public web pages and documentation as of September 2026: 200+ connectors, file systems, SharePoint, iManage, permission compliance, RAG, agents, multi-LLM compatibility, and SaaS, private cloud, or on-premises deployments. Scope and prerequisites are subject to change: verify them with each vendor for your specific environment.
See how Outmind would work with your sourcesDesigned for rapidly evolving AI
AI models evolve within a few months. The architecture you choose today shouldn't lock you into the model or interface of 2026. Outmind is designed as a durable knowledge layer between your data and your AI systems, allowing you to evolve your AI without having to reindex or reorganize all of the company's knowledge.
01
Outmind regularly integrates new, relevant models. Depending on the offering and the environment's configuration, the administrator can choose which language model to use, based on performance, security, and cost requirements.
Switching to a new model generation does not require reindexing, migrating, or rebuilding team workflows.
02
Outmind is priced based on the volume of indexed data and usage, not on a per-user license. You can make the search available to the entire organization without a new user automatically creating a new license.
The way AI is used may evolve along with the offerings, as models and their costs change.
03
The AI tools already in place at the company can access the knowledge indexed and governed by Outmind, rather than having to rebuild a RAG pipeline for each assistant.
A single layer for indexing, search, and permissions powers multiple AI experiences. Access rights remain in place regardless of which assistant queries the knowledge base.
04
Web search, agent-based reasoning, new models, the Assistant experience, file analysis: Outmind is advancing its AI capabilities without waiting for a new generation of platforms.
Literature Review
In a project file, a plausible answer isn’t enough. Sometimes you need to find an exact reference, the latest version of a calculation sheet, a contract clause, the email in which a decision was approved, or a specific phrase used several years ago—somewhere between SharePoint and a file server.
Deterministic search for exact words, phrases, operators, and filters. Semantic search to find a document whose vocabulary differs from the query. An open-source AI assistant to analyze and synthesize, while referencing the exact passage used to generate the response.
AI doesn't replace research—it's given a search function that's reliable enough to work with. Forengineering and design firms, years of accumulated work become reusable again instead of remaining buried in files.
See Outmind in action with your own documentsSearch Results
Verified Access Rights
4 sources on the same case
CR_MOA_Meeting_2018-11.docx
“… decision reached regarding the foundation option …”
NDC_Foundations_P4_vC.pdf
“… 1,200 mm bored piles, variant B …”
Project Charter Approval, Lot 3
“… the project owner confirms the selected option …”
Formwork_Plan_P4_scan.pdf
“… P4 support, supplemental geotechnical survey …”
Outmind Assistant
3 sources
The client approved Option B (1,200-mm bored piles) on March 14, 2023, subject to additional geotechnical investigation of support P4.
Response based on the research findings
Companies will likely not operate with just a single AI assistant. Some teams will use Outmind, while others will use general-purpose assistants or in-house agents. Outmind is designed so that the company’s curated knowledge does not have to be rebuilt separately for each of these tools.
Outmind
index + permissions
A single layer of indexing, search, and permissions can power multiple AI experiences. This architecture limits the proliferation of RAG pipelines and makes it possible to switch models or interfaces as the market evolves.
There is no one-size-fits-all solution. The right choice depends on the scope of your Enterprise AI project and how your users will actually work with the platform.
You're looking for a comprehensive Enterprise AI platform that covers a wide range of business systems and structured data.
Your project requires a high degree of customization in terms of applications, relevance, or user journeys.
You're looking for a highly comprehensive agent-based orchestration platform.
You have a team or a partner responsible for designing a highly customized architecture around the product.
Your priority is to make scattered documentary knowledge immediately usable.
Your file servers, SharePoint, email, archives, and document management systems contain a critical portion of the company's knowledge.
You want to maintain precise search results in addition to using AI.
You want the product to be used directly by the business teams, without any intermediaries.
You want to evolve AI models and interfaces without rebuilding the knowledge layer.
You want to make access available to a broad audience without a primarily per-user pricing model.
The question isn't just "which platform can do the most," but "which architecture will deliver the most value today while remaining relevant once AI has evolved further."
A corporate research project doesn't end once the connectors are plugged in. Outmind integrates adoption into the deployment process: role-specific guides, short team sessions, initial use cases developed with champions, and usage tracking.
01
Existing data where it is, including file servers and archives, without unnecessary migration.
02
First assistants and first use cases developed with the business teams, based on their real-world questions.
03
Short training sessions, followed by implementation and continuous improvement, team by team.
The goal is for Outmind to be the first thing employees turn to when they’re wondering where to find information or what past projects have to say on a particular topic. That’s also why pricing isn’t based on the number of users: the value of a search engine increases when it becomes accessible to the entire organization.
Sinequa is a long-standing French enterprise search technology provider, now owned by ChapsVision. Outmind is also a French company, with an infrastructure designed to meet the demands of large European organizations. The publisher’s country of origin is therefore not the distinguishing factor: the choice depends on the type of sources to be connected, the user experience, the target AI architecture, the pace of product development, model governance, and the business model.
A French company, hosting in Europe, a dedicated instance for each client. Your data is never used to train a model.
We do not store your documents. The index is encrypted at rest and in transit, with dedicated keys for each client. Outmind is ISO 27001 and SOC 2 Type II certified.
Outmind replicates the access rights of the source systems: each user sees only the content to which they already have access. The exact behavior depends on the connector and is validated during the project.
Outmind is used by engineering firms, design firms, consulting firms, and infrastructure providers whose document collections number in the tens of millions of files.
Thanks to Outmind’s indexing of document databases and project archives, Setec engineers and project managers can retrieve and reuse twenty years’ worth of studies instead of spending hours searching, recreating deliverables, or missing critical information about a project.
50M+
indexed documents
+70%
monthly active users
≈1 000
Connectors with permissions in production
We estimate that Outmind saves each of our project managers and engineers one month of work per year.
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Thierry Douceron
Director of Information Systems, Setec Bâtiment
Are you comparing several enterprise search solutions? Our comparison of alternatives to Sinequa reviews several vendors; our article on Sinequa pricing and plans addresses the issue of cost; and the Alternatives page brings together all of our comparisons. If you have a question about your specific environment, you can also contact us.
What is the best alternative to Sinequa?
There is no single, universally better option. The choice depends on your sources, the level of customization you’re looking for, and your AI strategy. Outmind is particularly well-suited for organizations that want to make their document-based knowledge actionable for both employees and their AI systems, by combining deterministic search, semantic search, RAG, and assistants into a modern user experience.
What is the difference between Outmind and Sinequa?
Sinequa offers a very comprehensive Enterprise AI platform, with over 200 announced connectors, extensive configuration options, RAG, agents, and an open architecture. Outmind places greater emphasis on the day-to-day AI search and assistance experience, document-based knowledge, adoption, and an architecture capable of evolving rapidly with new AI models and interfaces.
Is Outmind as technologically advanced as Sinequa?
Outmind regularly updates its AI layer and product experience. Notably, the product integrated GPT-5 and agent-based functionality in October 2025, web search into the Assistant in January 2026, and new indexing and administration options in 2026. Depending on the configuration, Outmind also allows users to control model selection and expose its knowledge layer to external AI systems.
Can you change the AI model in Outmind?
Depending on the offering and the environment's configuration, the administrator can choose from the models available in Outmind. The platform is designed to evolve this layer as new generations of models emerge, rather than permanently tying the experience to a single LLM.
Can Sinequa and Outmind search file servers?
Yes, both platforms support file systems. At Outmind, searching file servers and project archives—without the need for prior migration—is a core use case, particularly in engineering, construction, consulting, and historical document management environments.
Do Sinequa and Outmind comply with access rights?
Yes. Both solutions document the mechanisms for inheriting permissions from source systems. For any enterprise search deployment, the exact behavior must be validated on a per-connector basis, depending on the systems and the customer's configuration.
Is Outmind cheaper than Sinequa?
We can't say for sure without comparing two equivalent offerings. Outmind primarily uses a pricing model based on the volume of indexed data and usage rather than the number of users, which may be appealing to organizations that want to deploy search on a large scale. Our pricing plans and ROI calculator are publicly available.
Is there a French alternative to Sinequa?
Yes, Outmind is a French company that offers a corporate search and AI platform. Sinequa, however, is also French and is owned by ChapsVision. The choice between the two solutions therefore hinges more on the product approach, architecture, and use cases than on the publisher’s nationality.
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