Sinequa AI is a powerful enterprise search and generative AI platform designed to help large organizations extract meaningful insights from complex, unstructured, and structured data. The platform combines intelligent search, natural language processing (NLP), and large language models (LLMs) to deliver context-aware search experiences across enterprise content.
Used by knowledge-intensive industries such as life sciences, financial services, and manufacturing, Sinequa transforms the way organizations discover, access, and use information. It enables employees to make faster, better-informed decisions by surfacing relevant knowledge hidden across emails, documents, databases, and legacy systems.
Features
Sinequa offers an AI-powered search platform capable of indexing and understanding billions of documents across multiple languages.
It uses advanced NLP to interpret the meaning behind queries and content, delivering more relevant and contextual results.
The platform includes a neural search engine that combines semantic understanding with keyword precision to enhance retrieval accuracy.
Generative AI capabilities are integrated into the search experience, allowing users to ask complex questions and receive summarized answers grounded in enterprise data.
Sinequa supports content analytics, enabling organizations to derive trends and patterns from enterprise information.
It includes connectors for over 200 data sources including SharePoint, Salesforce, SAP, and Microsoft 365, ensuring seamless data integration.
Security and access controls are built-in, with full compliance to enterprise-grade standards like SOC 2, GDPR, and HIPAA.
Customizable interfaces and APIs allow businesses to tailor the search experience for specific roles, departments, or workflows.
Real-time indexing and multilingual capabilities make it suitable for global enterprises with large and diverse content ecosystems.
How It Works
Sinequa works by crawling and indexing content from various enterprise data sources. This content is enriched through NLP techniques such as entity recognition, sentiment analysis, summarization, and classification.
The search engine applies both keyword and neural search models to provide highly accurate and context-relevant results. When integrated with generative AI, users can ask natural language questions and receive AI-generated summaries that are based strictly on indexed enterprise data—reducing hallucination risks.
The platform’s intelligent search interface allows users to refine results with filters, preview documents, and drill down into specific insights. APIs and SDKs enable integration into enterprise apps like intranets, digital workplaces, and support portals.
Sinequa’s architecture is cloud-native and scalable, supporting both on-premises and hybrid deployments, which makes it adaptable to different IT environments.
Use Cases
Pharmaceutical and life sciences companies use Sinequa to accelerate R&D by giving scientists fast access to research papers, clinical trial results, and lab data.
In financial services, analysts and advisors use it to retrieve regulatory documents, client records, and market intelligence from fragmented systems.
Manufacturers rely on Sinequa to improve product development and maintenance by making technical manuals, design documents, and field reports searchable.
Customer support teams use the platform to reduce response time by finding answers from knowledge bases and historical tickets.
Legal departments benefit by locating case files, contracts, and compliance documents quickly and securely.
Knowledge management professionals use Sinequa to improve enterprise knowledge sharing and retention, especially in large, distributed teams.
Pricing
Sinequa does not publish pricing on its official website. As an enterprise solution, pricing is customized based on the size of the organization, volume of data, deployment type, and feature requirements.
Typically, Sinequa works with large organizations and Fortune 500 companies, so pricing reflects the complexity and scale of deployments. Interested businesses are encouraged to request a demo or contact the sales team to receive a tailored quote and implementation plan.
The platform offers deployment options in the cloud, on-premises, or hybrid models, with enterprise-level support included in service agreements.
Strengths
Purpose-built for large enterprises and knowledge-intensive industries.
Combines neural search, NLP, and generative AI to deliver high-relevance results.
Strong support for multilingual content, making it ideal for global organizations.
Over 200 data connectors simplify integration across business applications.
Customizable UX and developer tools enable tailored user experiences.
Proven deployments across life sciences, finance, and manufacturing sectors.
Enterprise-grade security and compliance standards are embedded.
Cloud-native and scalable architecture supports growth and flexibility.
Drawbacks
Pricing and implementation may be out of reach for small to mid-sized businesses.
Requires time and IT resources to deploy and customize at the enterprise level.
Due to its complexity, onboarding and training may be needed for full adoption.
Not suitable for individuals or teams looking for out-of-the-box search tools.
Generative AI features are focused on grounded enterprise data, not open-ended generation, limiting creative use cases.
Comparison with Other Tools
Compared to Microsoft Search or Google Cloud Search, Sinequa offers deeper semantic capabilities and more control over enterprise-specific content.
Unlike generic search tools, Sinequa is tailored for regulated and data-rich industries, offering precise compliance and governance features.
Against open-source enterprise search tools like Apache Solr or Elasticsearch, Sinequa includes pre-built AI and NLP capabilities, significantly reducing the development burden.
Compared to AI chatbots like ChatGPT, Sinequa’s generative AI is grounded in enterprise data, ensuring factual responses tied to internal documents.
Tools like Coveo or Lucidworks may offer similar functionality, but Sinequa stands out in its ability to scale across billions of documents and support multilingual, secure enterprise environments with precision.
Customer Reviews and Testimonials
Sinequa is trusted by some of the world’s largest enterprises, including AstraZeneca, Siemens, and NASA. Testimonials emphasize its ability to improve productivity, reduce time spent searching for information, and support strategic decision-making.
Enterprise customers report that Sinequa significantly enhances internal knowledge discovery, accelerates R&D, and supports compliance by providing consistent access to reliable data.
Technology analysts from Gartner and Forrester recognize Sinequa as a leader in enterprise search and cognitive search platforms.
Use cases across industries show a strong return on investment through better use of organizational knowledge and streamlined operations.
Conclusion
Sinequa AI delivers a robust and scalable enterprise search platform designed to unlock the full potential of organizational data. By combining neural search, NLP, and generative AI into a single solution, it empowers large organizations to find, understand, and use their content more effectively.
Whether in life sciences, financial services, manufacturing, or legal fields, Sinequa helps businesses enhance productivity, support innovation, and maintain compliance. While it may not be suitable for smaller organizations, it offers unmatched capabilities for enterprises looking to transform information into actionable knowledge.
