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Sinequa is a long-standing player in the enterprise search market. Used by major industrial groups, the platform allows for the indexing of vast volumes of documents and the rapid retrieval of information scattered across different systems.
For many years, this type of solution has been the gold standard for accessing corporate knowledge.
However, with the advent of generative AI, user expectations have shifted. Employees no longer just want to find a document; they expect precise, contextualized, and immediately actionable answers.
Like other market players, Sinequa has enhanced its platform with AI assistants, RAG capabilities, and, more recently, AI agents. Nevertheless, some companies are looking for an alternative that better meets their specific needs, whether in terms of deployment simplicity, user experience, cost, flexibility, or features tailored to their use cases.
Sinequa's strengths
Sinequa is recognized for its ability to index and explore large volumes of information distributed across various enterprise systems.
The platform notably enables you to:
- centralize access to information;
- connect to over 200 applications, databases, and business tools;
- support more than 300 document and data formats;
- quickly search for relevant content;
- facilitate knowledge discovery within large document corpora;
- integrate with various Large Language Models (LLMs) according to the company's needs.
For organizations looking to improve access to their document assets while relying on an open and scalable platform, Sinequa is a well-established solution in the enterprise search and AI-driven knowledge management market.
Sinequa's limitations in the generative AI era
Finding a document is not the same as answering a question
Sinequa's primary strength is document search. The user enters a query and receives a list of relevant results.
But in many industrial contexts, finding a document is only the first step. Employees must then analyze the results, identify the right information, cross-reference multiple sources, and construct the answer themselves.
However, users today expect assistants capable of providing a direct, contextualized answer rather than just a list of documents.
Limited use of field knowledge
A large portion of industrial knowledge is not found in documents. It resides in the experience of technicians, engineers, and experts who resolve complex situations on a daily basis.
Like most enterprise search engines, Sinequa primarily leverages documented content. Tacit knowledge, feedback, and best practices shared through informal exchanges remain more difficult to capitalize on.
Limited reasoning capabilities
Industrial questions are often complex. They involve technical jargon, multiple information sources, and sometimes several steps of reasoning.
Document search helps identify relevant information, but it does not replace the analysis performed by an expert. Users must still interpret the results to reach an actionable conclusion.
A limited role for subject matter experts
Experts play a central role in the quality of the knowledge used by the company.
However, in many document search solutions, their contribution remains primarily indirect through the production of documents. There are few mechanisms that allow for easily capturing their answers and expertise over time.
Why choose Ask for the moon?
While Sinequa facilitates access to information, Ask for the moon stands out for its ability to create a continuous loop between explicit knowledge and the tacit expertise of specialists.
The platform is not limited to querying existing documents: it also allows for capturing, structuring, and leveraging field expertise, which is often scattered across teams and rarely formalized.
Designed for industrial environments, Ask for the moon addresses challenges related to reliability, subject matter expertise, and knowledge transfer by transforming available information and expert experience into directly actionable answers.
An AI that answers questions, not just searches
Ask for the moon stands out not just for its ability to generate answers, but for the quality of its reasoning on complex business challenges.
The platform cross-references information from various sources, considers the context of the request, and leverages the most relevant knowledge to produce accurate, reliable, and actionable answers.
This approach limits guesswork, reduces time spent verifying information, and helps teams make decisions faster, even in demanding industrial environments.
An AI that knows how to say "I don't know"
In the industrial sector, an imprecise answer can have significant consequences.
With Ask for the moon, only subject matter experts choose, validate, and maintain the knowledge sources used by the AI. The generated answers are based exclusively on company-approved content, ensuring a higher level of reliability and trust.
Ask for the moon puts humans at the heart of the decision-making process. AI recommendations can be reviewed, validated, or enriched by business teams before being used.
Capitalizing on expert knowledge
In many industrial companies, a significant portion of critical knowledge is not found in documents.
With retirements and recruitment challenges in certain trades, the transfer of this knowledge has become a strategic issue.
Ask for the moon allows you to capture and gradually capitalize on this business knowledge. When an expert answers a question, their response can be validated and then integrated into the knowledge base to be reused for future requests.
The company thus gradually transforms the tacit knowledge of its experts into a lasting knowledge asset.
A sovereign approach
Companies retain control over their data, access, and AI governance.
Ask adopts a flexible architecture capable of integrating into the technical environment chosen by the company, in order to meet the security, compliance, and sovereignty requirements of industrial organizations.
Comparison table: Sinequa vs. Ask for the moon
Would you like to compare Sinequa with an AI designed for your industrial challenges?
Check out our AI benchmark comprehensive, to compare the various approaches on the market.
We also offer a 4-week AI benchmark to evaluate automation opportunities, compare existing solutions, and identify the use cases with the highest return on investment.
Request a demo to discover how Ask for the moon can integrate into your environment.
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