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Sinequa

  • What it is:Sinequa is a GenAI-powered enterprise search and analytics platform that unifies structured and unstructured data for contextual, multilingual search and AI assistants.
  • Best for:Large enterprises (1000+ employees), Organizations with heterogeneous data sources, Global teams requiring multi-language support
  • Pricing:Starting from $79/month
  • Rating:85/100Very Good
  • Expert's conclusion:Sinequa is best suited for large-enterprise organizations that need a robust, secure and scalable AI powered search solution for large, diverse data sets.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Sinequa and What Does It Do?

Sinequa develops an enterprise search platform powered by AI, so large global companies and government agencies can find the right information and insight from their own enterprise systems based on how they use natural language processing and machine learning. Since being founded in 2002 as a private research laboratory in France, the company has expanded to service over 50 Fortune 500 companies including Pfizer, AstraZeneca and NASA. The company was recently acquired by ChapsVision, which currently has headquarters in Paris and offices around the world.

Active
📍Paris, France
📅Founded 2002
🏢Subsidiary
TARGET SEGMENTS
Fortune 500 EnterprisesGovernment AgenciesLife SciencesEnergyAerospace

What Are Sinequa's Key Business Metrics?

📊
$28.2M
Total Funding
📊
$23M
Most Recent Funding
📊
3
Funding Rounds
💵
$26M
Revenue
👥
Fortune 500 clients including Pfizer, NASA
Customers
📊
Paris, New York, San Francisco, Huntsville, London, Frankfurt
Offices

How Credible and Trustworthy Is Sinequa?

85/100
Excellent

Sinequa’s has established a successful 20+ year history of developing AI search technologies with many top Fortune 500 and government clients, and it has been further stabilized through the recent acquisition which has brought financial stability.

BREAKDOWN
Product Maturity95/100
Company Stability85/100
Security & Compliance80/100
User Reviews75/100
Transparency70/100
Support Quality80/100
TRUST SIGNALS
20+ years AI experienceFortune 500 customers (Pfizer, AstraZeneca, Airbus, NASA)Gartner and Forrester recognitionRecently acquired with significant financing

What is the history of Sinequa and its key milestones?

2002

Company Founded

Sinequa was established as a private research laboratory in France with the goal of helping computers become smarter with human language.

2010s

First Semantic Search Engine

First version of Sinequa’s semantic search engine technology launched.

2024

Acquired by ChapsVision

Sinequa acquired by ChapsVision, Europe’s largest developer of AI software, supported through an €85 million third funding round.

Who Are the Key Executives Behind Sinequa?

Olivier Dellenbach— CEO of ChapsVision (Parent Company)
Founder of ChapsVision (2019), serial entrepreneur, prior founder of eFront which was sold for $1.5 billion and had completed 27+ strategic acquisitions including Sinequa.
Jean Ferré— CEO of Sinequa
Former CEO comments on ChapsVision acquisition as perfect next step for Sinequa’s continued growth and expansion into new customers.
Xavier de Labaume— VP Corporate Development
Led Sinequa’s expansion into the U.S. market. 20+ years of experience in enterprise software sales at IBM and other organizations.
Alexandre Bilger— Chief Architect Officer
Co-founder and former CTO of eFront. 20+ years of experience in enterprise software development with a focus on AI, ML and NLP.
Jeff Carr— VP Customer Solutions
20+ years of experience in data analytics consulting and professional services. Graduated from MIT with a Master of Engineering degree.

What Are the Key Features of Sinequa?

✨
AI-Powered Enterprise Search
Finds relevant information from all of your enterprise systems using advanced search combined with natural language processing.
💬
Multilingual Support
Provides insights across complex enterprise data environments in any language.
✨
Retrieval Augmented Generation (RAG)
Allows GenAI implementations to occur for enterprises with complex IT architectures and large amounts of data.
✨
Semantic Search Engine
Is able to derive the most relevant results from unstructured enterprise content based upon the meaning and context of that content.
✨
Machine Learning Personalization
Is able to learn user behaviors to provide search results and insights that are relevant to a user’s current context.

What Technology Stack and Infrastructure Does Sinequa Use?

Infrastructure

Global operations with offices in Paris, US, UK, Germany

Technologies

Natural Language ProcessingMachine LearningSemantic SearchAI Algorithms

Integrations

Enterprise Content SourcesComplex IT ArchitecturesLarge Data Sets

AI/ML Capabilities

Advanced NLP and ML algorithms powering semantic search and RAG capabilities for enterprise knowledge management

Inferred from product positioning as AI-powered enterprise search; specific tech stack details not publicly detailed

What Are the Best Use Cases for Sinequa?

Fortune 500 Enterprises
Allows users to derive insight from disparate enterprise data sources (both structured and unstructured) across complex IT environments that support clients such as Pfizer, AstraZeneca and TotalEnergies.
Government Agencies
Customers who have mission-critical knowledge discovery requirements (such as those from NASA and Government agencies) utilize the product for discovering knowledge across multiple languages and structured/unstructured data.
Life Sciences R&D Teams
Companies in the pharmaceutical space such as Pfizer use the product for accelerating their research by utilizing the intelligent semantic search technology to search technical documents.
Aerospace Engineering Teams
Airbus uses this product to manage engineering knowledge across its vast collection of technical documentation and multi-language data sources.
NOT FORSmall Businesses
Due to the complexity of the environment which it is designed for, Sinequa may be an expensive solution for small-scale simple search applications.
NOT FORConsumer Applications
The product is focused primarily on providing search capabilities within large enterprises and therefore has not been optimized for providing search experiences to the general public.

How Much Does Sinequa Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Standard$79/monthTiered structure entry levelSirius Open Source comparison
ProContact for pricingMid-tier featuresSirius Open Source comparison
EnterpriseCustom quote, volume-basedBased on documents/records ingested, minimum 3-year subscription, starts around $50,000/yearLuigi's Box , Sirius Open Source
Standard$79/month
Tiered structure entry level
Sirius Open Source comparison
ProContact for pricing
Mid-tier features
Sirius Open Source comparison
EnterpriseCustom quote, volume-based
Based on documents/records ingested, minimum 3-year subscription, starts around $50,000/year
Luigi's Box , Sirius Open Source

How Does Sinequa Compare to Competitors?

FeatureSinequaINDICA Enterprise SearchGoogle Cloud SearchElastic Workplace SearchAlgolia
Core functionalityAI-powered neural searchPatented data indexing & rankingUnified search across Google WorkspaceMulti-source searchPay-per-use search
Pricing (starting price)Custom/volume-basedNo info availablePay-as-you-go, free tier$16/month$1 per 1,000 requests
Free tier availabilityNoFree version/trialYesNoYes
Enterprise features (SSO, audit logs)Yes (security & compliance)Yes (filtering, access control)YesPartialEnterprise plans
API availabilityYesYesYesYesYes
Integration countComprehensive (Box, Dropbox, MS Teams, Salesforce)Multiple sourcesGoogle ecosystemSalesforce, Google Workspace, etc.Bundled services
Support optionsPhone, documentation, 24/7 livePhone, 24/7 live, onlineGoogle supportStandardEmail, calls, help center
Security certificationsCompliance focusedPrivacy suite availableGoogle security
Core functionality
SinequaAI-powered neural search
INDICA Enterprise SearchPatented data indexing & ranking
Google Cloud SearchUnified search across Google Workspace
Elastic Workplace SearchMulti-source search
AlgoliaPay-per-use search
Pricing (starting price)
SinequaCustom/volume-based
INDICA Enterprise SearchNo info available
Google Cloud SearchPay-as-you-go, free tier
Elastic Workplace Search$16/month
Algolia$1 per 1,000 requests
Free tier availability
SinequaNo
INDICA Enterprise SearchFree version/trial
Google Cloud SearchYes
Elastic Workplace SearchNo
AlgoliaYes
Enterprise features (SSO, audit logs)
SinequaYes (security & compliance)
INDICA Enterprise SearchYes (filtering, access control)
Google Cloud SearchYes
Elastic Workplace SearchPartial
AlgoliaEnterprise plans
API availability
SinequaYes
INDICA Enterprise SearchYes
Google Cloud SearchYes
Elastic Workplace SearchYes
AlgoliaYes
Integration count
SinequaComprehensive (Box, Dropbox, MS Teams, Salesforce)
INDICA Enterprise SearchMultiple sources
Google Cloud SearchGoogle ecosystem
Elastic Workplace SearchSalesforce, Google Workspace, etc.
AlgoliaBundled services
Support options
SinequaPhone, documentation, 24/7 live
INDICA Enterprise SearchPhone, 24/7 live, online
Google Cloud SearchGoogle support
Elastic Workplace SearchStandard
AlgoliaEmail, calls, help center
Security certifications
SinequaCompliance focused
INDICA Enterprise SearchPrivacy suite available
Google Cloud SearchGoogle security
Elastic Workplace Search—
Algolia—

How Does Sinequa Compare to Competitors?

vs INDICA Enterprise Search

Sinequa provides a neural AI search solution for large enterprises with complex environments, while INDICA provides a solution for quickly discovering data across both structured and unstructured data using its patented indexing methodology. While INDICA provides a free trial/version, Sinequa provides more advanced AI/ML capabilities, however, due to custom volume-based pricing, it is positioned as a premium solution.

Use Sinequa for AI-driven Enterprise Knowledge Management; INDICA for Fast Relevance Ranked Searches in Mid-Market.

vs Google Cloud Search

Sinequa has the ability to handle heterogeneous enterprise data and includes security features whereas Google Cloud Search has the strength of being able to integrate into the Google Workspace and also allows for pay-as-you-go pricing. However, Sinequa would be a better choice for organizations outside of the Google ecosystem; however, it does not offer a free tier.

Choose Sinequa for Cross-Platform Enterprise Search; Google for Workspace-Centric Teams.

vs Elastic Workplace Search

Sinequa provides sophisticated agentic AI and compliance capabilities for searching large-scale unstructured data while Elastic provides a simpler multi-source search capability at a lower price point per-user (starting at $16-30/month). Sinequa has a wider range of integrations than Elastic, however, it has a much higher entry cost.

Use Sinequa for Advanced Analytics in Regulated Enterprises; Elastic for Cost-Effective Basic Search.

vs Algolia

Sinequa is an enterprise-focused solution with subscription licensing for organizations with large amounts of data, while Algolia is a usage-based solution with a pricing model that starts at $1/1k requests, making it a better fit for organizations with smaller scale data. Sinequa has the lead in terms of AI insights, while Algolia has the advantage in terms of flexibility and entry costs.

Choose Sinequa for Comprehensive Enterprise Platforms; Algolia for Scalable Pay-Per-Use Search.

What are the strengths and limitations of Sinequa?

Pros

  • Provides Exceptionally Rapid Performance—Completes Searches in Milliseconds for Large Datasets.
  • Provides Extremely High Scalability—Handles Vast Heterogeneous Data Volumes.
  • Provides Very Strong AI/ML Capabilities—Neural Search and Advanced Analytics.
  • Integrates Comprehensively—Box, Dropbox, MS Teams, Salesforce, ServiceNow.
  • Provides Robust Security—Compliance in Complex Environments.
  • Supports Multiple Languages—Effective for Global Enterprises.
  • Offers Flexible Deployment Options—Cloud, On-Premise, Hybrid.

Cons

  • Provides Opaque Pricing—Custom Quotes Only; Difficult for Small Businesses to Assess.
  • Costs Very Expensive for Enterprises—Volume-Based; Starts at Approximately $50K Per Year; Minimum Term 3 Years.
  • Does Not Provide a Public Free Tier—Requires Sales Contact Even for Demos.
  • Can Be Complex for Small-Scale Users—Pricing Intervals Generous But Geared to Large Data Volumes.
  • Has a Long Return-On-Investment (ROI) Timeline—Average 20 Months Reported.
  • Is a Sales-Driven Process—No Self-Service Signup or Transparent Tiers.
  • Lacks Pricing Transparency—Difficult to Compare Without Quote.

Who Is Sinequa Best For?

Best For

  • Large enterprises (1000+ employees) — Handles Massive Unstructured Data Volumes Using AI Search and Compliance Needs.
  • Organizations with heterogeneous data sources — Unifies Siloed Information Using Comprehensive Connectors and Neural Search.
  • Global teams requiring multi-language support — Has Strong Multilingual Capabilities and Scalability for International Operations.
  • Regulated industries needing security — Provides Enterprise-Grade Compliance and Secure Handling of Sensitive Data.
  • Knowledge-intensive businesses — Accelerates Data Discovery and Insights Using an Agentic AI Platform.

Not Suitable For

  • Small businesses or startups — Has High Minimum Costs and Volume-Based Pricing Not Economical—Consider Algolia or Elastic Instead.
  • Teams needing quick self-service setup — Requires Sales Quotes and Longer Implementation—Try Google Cloud Search for Instant Start
  • Budget-conscious mid-market companies — The cost of custom enterprise pricing is higher than the cost of a simple tool such as Elastic at $16/user/month
  • Simple search needs without AI — Overkill for the basics of indexing; choose free-tier options such as Algolia

Are There Usage Limits or Geographic Restrictions for Sinequa?

Pricing Model
Volume-based on documents/records ingested, 3-year minimum subscription
Deployment Options
Cloud, on-premise, hybrid
User Limits
Unlimited users, servers, cores, queries
Data Volume
Pricing scales with ingested records; generous intervals
Contract Term
Minimum 3 years, up to 5 years
Free Trial
Not publicly available; demo via sales
Geographic Availability
Global enterprise focus, no specific restrictions noted
Compliance
Enterprise security & compliance supported

Is Sinequa Secure and Compliant?

Enterprise SecurityHandles security and compliance in complex environments with vast heterogeneous data
Data ProtectionSecures unstructured data discovery while maintaining regulatory compliance
Access ControlRole-based permissions and integration with enterprise identity systems
Deployment SecurityFlexible cloud, on-premise, hybrid options ensure control over sensitive data
Neural Search SecurityAI-powered search maintains data privacy and context-aware insights
Integration SecuritySecure connectors for Box, Dropbox, Microsoft Teams, Salesforce, ServiceNow

What Customer Support Options Does Sinequa Offer?

Channels
Available through contact form on sinequa.comBusiness hours via regional offices24/7 submission, response during business hours
Hours
Business hours (regional offices in Europe and US)
Response Time
Typically within 24-48 business hours per user reviews
Satisfaction
Not publicly available; enterprise-focused with dedicated support implied
Specialized
Dedicated support for enterprise customers with custom implementations
Business Tier
Priority support for large deployments with SLAs

What APIs and Integrations Does Sinequa Support?

API Type
REST API with support for custom integrations
Authentication
OAuth, API keys, SSO integration
Webhooks
Supported for indexing triggers and events
SDKs
Not publicly listed; custom SDKs available for partners
Documentation
Available in developer portal for partners and customers
Sandbox
Testing environments for enterprise deployments on Azure
SLA
99.9% uptime for cloud deployments, enterprise-grade scalability
Rate Limits
Configurable based on deployment size and tier
Use Cases
Data ingestion via 200+ connectors, custom AI agents, RAG workflows

What Are Common Questions About Sinequa?

Sinequa is a highly advanced AI powered enterprise search platform that brings together all forms of structured and unstructured data from 200 + different sources. This enables users to perform semantic searches, RAG (Red Amber Green) copilots and to find knowledge using multiple languages for secure knowledge discovery.

Sinequa utilizes intelligent indexing for text, images, video and audio by automatically identifying entities and concepts. It supports both complete and incremental indexing modes utilizing full-text, structured and semantic indexes.

Unlike many other tools that utilize only keyword searching Sinequa utilizes statistical, neural and semantic search for contextual relevance. Additionally, it integrates with tools such as Teams and Salesforce and provides AI agents that are grounded in enterprise data.

Yes, Sinequa provides enterprise grade security through fine grained governance, SSO, encryption and access control. In addition, Sinequa complies with applicable regulatory requirements and provides multi-layered security for both its cloud and on-premises deployments.

Yes, Sinequa has been optimized for Azure with native integration for Teams and can leverage the scalability of Azure services for deployments. Additionally, Sinequa can be easily integrated into the Microsoft ecosystem.

Sinequa provides enterprise focused professional services for deploying and customizing the product. All enterprise customers will have access to dedicated support for their specific integration needs and setting up AI copilots.

Demos and proofs-of-concepts are available via a sales contact. Enterprise trials are also available but they are customizable to fit your data sources and use case.

Pricing for Sinequa is enterprise focused and therefore is not publicly disclosed; you need to obtain a sales quote. Due to the complexity of deployment, Sinequa is best suited for large organizations.

Is Sinequa Worth It?

The strength of Sinequa lies in its ability to accurately and securely handle multiple data formats while providing AI-powered knowledge management capabilities for organizations. Its enterprise nature also makes Sinequa expensive and complex enough to be too much for most small teams to handle.

Recommended For

  • Organizations with large amounts of unstructured data that are siloed
  • Multi-national corporations that require multi-language searching capabilities
  • Teams that operate within highly-regulated industries (e.g. Healthcare, Finance) that require governance over their searches.
  • Teams using Microsoft Azure ecosystems as their primary infrastructure for cloud services.

!
Use With Caution

  • Mid-size organizations that do not have the budget or IT staff to dedicate to an enterprise-grade solution.
  • Teams looking for low-cost solutions that can quickly set up and deploy an enterprise search solution.
  • Organizations that use simple keyword search capabilities.

Not Recommended For

  • Small businesses due to the high cost and complexity of the product.
  • Teams that want the ease of use of consumer-grade products.
  • Teams that prefer open source alternatives but still want enterprise-level support.
Expert's Conclusion

Sinequa is best suited for large-enterprise organizations that need a robust, secure and scalable AI powered search solution for large, diverse data sets.

Best For
Organizations with large amounts of unstructured data that are siloedMulti-national corporations that require multi-language searching capabilitiesTeams that operate within highly-regulated industries (e.g. Healthcare, Finance) that require governance over their searches.

What do expert reviews and research say about Sinequa?

Key Findings

Sinequa provides a powerful, scalable enterprise grade AI search solution with over 200 different connector options for connecting to your organization's data sources, semantic indexing and RAG (Red-Amber-Green) copilot functionality. Additionally, Sinequa supports multi-lingual search. It is also optimized for Microsoft Azure and includes strong security features and integration with Microsoft Teams. Sinequa has been used by numerous large-enterprises around the world, including Alstom, for the purpose of mastering unstructured data.

Data Quality

Good - detailed technical info from official site and blogs; limited public data on pricing, support specifics, and customer reviews.

Risk Factors

!
Pricing is only available for the enterprise version of Sinequa; therefore you will need to reach out to Sinequa to get pricing information.
!
There is limited publicly available review and rating information regarding Sinequa.
!
If you plan to deploy Sinequa in a non-Azure environment, then you should expect deployment complexity issues.
!
The recent acquisition of Sinequa by ChapsVision could negatively affect Sinequa's future product development roadmap.
Last updated: February 2026

What Additional Information Is Available for Sinequa?

Partnerships

Sinequa is specifically designed for Microsoft Azure, and offers the deepest possible level of integration with all of the various Azure service offerings. Sinequa is used by many leading enterprises such as Alstom for the purposes of analyzing technical documentation.

Case Studies

Alstom utilizes Sinequa to obtain insight into the unstructured data contained in complex technical documentation which improves the time-to-insight for the data scientist team.

Technology Focus

Sinequa specializes exclusively in the areas of enterprise search and AI agent technology, and is now part of the ChapsVision family of products, following the company's acquisition of Sinequa.

Deployment Options

Sinequa is a cloud-native solution on Azure, with on-premises support and dynamic resource scaling that allows customers to reduce their costs.

Awards & Recognition

82. Trained by major companies around the world; cited as a leading company in enterprise search by analyst firms.

What Are the Best Alternatives to Sinequa?

  • •
    Elastic Enterprise Search: A free, open source search engine that has powerful analytics and is very secure. Much more adaptable for your own development and build, however, it does require more from your DevOps team; great for teams that are very technical and experienced with the programming. (elastic.co)
  • •
    Coveo: An artificial intelligence driven enterprise search solution that offers usage statistics and allows for personalization of results. Has a similar level of focus on enterprise needs as Coveo Enterprise Search, but focuses more heavily on commerce; ideal for customer facing search solutions. (coveo.com)
  • •
    Lucidworks Fusion: Uses artificial intelligence/machine learning to drive its search solution and includes fusion AI features. More for developers as it uses an open architecture model; ideal for teams looking to develop their own AI applications. (lucidworks.com)
  • •
    Azure Cognitive Search: An AI search service native to Microsoft that integrates with all of Azure's AI tools. Less expensive for users of Azure, but has less specialization when dealing with unstructured data common to most enterprise organizations. (azure.microsoft.com)
  • •
    Algolia: Offers fast, API-first search-as-a-service focused on site search. Great option for developers who need to quickly implement search functionality, also great for smaller scale organizations; less suitable for large-scale enterprise search silos. (algolia.com)

What Core Search Capabilities Does Sinequa Offer?

Unified Multilingual Search

The single entry point into your entire corporate knowledge base using 20+ different languages and semantic contextual matching

Semantic Search Engine

Artificially intelligent comprehension of synonyms, context, and user intent using full-text, structured and semantic indexes

Faceted Search & Dynamic Filters

Interactive facets, suggestions and filters for quick and efficient results refinements across your organization's dataset

RAG Copilot Integration

Retrieval-Augmented Generation for exact, traceable and contextualized answers to natural language questions

Hybrid Index Architecture

Combination of full-text, structured metadata and semantic indexes for comprehensive relevance at scale

Multimedia Search

Allows for searchable audio, video and images through automated transcription, entity extraction and visual analysis

Search Analytics

Provides query patterns, user engagement and performance metrics for ongoing relevance optimization

What Data Integration Connectors Does Sinequa Offer?

200+ Native Connectors

Provides comprehensive access to all structured and unstructured content types, including Microsoft 365, SharePoint, Teams, Salesforce, and SAP

Microsoft Ecosystem Integration

Optimizes natively within Azure through connectors for Teams, OneDrive, Exchange, and Azure services

Collaboration Platform Connectors

Conversations, Projects, Documentation Search via Slack, Microsoft Teams, Jira, Confluence

Enterprise Applications

Integration of ERP/CRM software with SAP, Salesforce, ServiceNow for company information and customer data.

Database Connectors

Business Intelligence and Operational Data via Structured Databases (SQL Server, Oracle, PostgreSQL)

Real-time Change Detection

Triggering incremental index rebuilds based on Events, Schedules, On-Demand for Fresh Content

Custom Connector SDK

Developer Toolkit for Proprietary Systems and Legacy Application Integrations

What Is Sinequa's Deployment And Scalability?

Deployment Options
Cloud (Azure-optimized), On-premises, Hybrid
Cloud Platforms
Microsoft Azure (native), AWS, Google Cloud
Document Capacity
Tens of millions of documents with distributed indexing
Scaling Architecture
Dynamic auto-scaling, Kubernetes containerization
Content Processing
Structured/unstructured/multimodal (text, audio, video, images)
Language Support
20+ languages including double-byte (Chinese, Japanese)
Indexing Modes
Real-time incremental, scheduled, on-demand, event-triggered
Security Integration
Azure KeyVault, SSO synchronization, multilayer security

What Are Sinequa's Business Impact Outcomes?

32+ days/year saved per employee
Productivity Gains
Hours to minutes for complex queries
Search Time Reduction
Faster task automation via AI copilot
Team Efficiency
Cross-functional data democratization
Knowledge Accessibility
Rapid user uptake via intuitive UX
Adoption Rate
Dynamic resource scaling reduces infrastructure waste
Cost Optimization

What Is Sinequa's Compliance And Security Controls Status?

Multilayer SecurityCloud, on-premises, SSO, per-user access controls, security filters
Encryption PipelineBuilt-in encryption during indexing with IP restrictions
Compliance StandardsInternational and industry-specific regulatory adherence
Fine-grained GovernancePermission synchronization and content-level security
Access TraceabilityFull audit trails with enterprise-grade scalability
Data ResidencyAzure region selection for sovereignty compliance
Zero-Trust ArchitectureSecure-by-design with continuous validation

How Does Sinequa's Primary Use Cases By Department Compare?

DepartmentPrimary Use CaseBusiness OutcomesKey Data Sources
Research & DevelopmentUnified access to technical documents, patents, and experimental dataAccelerated innovation cycles, reduced duplication of R&D effortsPLM systems, experiment logs, technical papers, collaboration platforms
Customer SupportInstant retrieval of solutions during customer interactionsFaster resolution times, improved customer satisfactionKnowledge base, support tickets, product documentation, chat logs
Compliance & LegalRapid eDiscovery across all enterprise contentReduced legal risk, faster regulatory compliance fulfillmentContracts, policies, email archives, regulatory documents
Sales & MarketingBrand asset discovery and competitive intelligenceImproved campaign execution, brand consistencyCRM data, marketing assets, market research, competitive filings
IT OperationsIncident resolution through unified system knowledgeFaster MTTR, improved operational reliabilitySystem logs, runbooks, architecture docs, monitoring data
Executive LeadershipStrategic insights from aggregated enterprise dataData-driven decision making, competitive advantageAll enterprise systems, financials, market intelligence
HR & Talent ManagementInternal talent discovery and policy accessImproved talent mobility, faster onboardingResumes, performance reviews, training materials, policies

What Ai And Machine Learning Capabilities Does Sinequa Offer?

Retrieval-Augmented Generation (RAG)

Enterprise Grounded Copilot using Generative AI to Reduce Hallucination and Provide Traceable Answers

Semantic Extraction & NLP

Automatic Entity Extraction, Concept Extraction, Relationship Extraction Across 20 Languages and Content Types

Multimodal Processing

Transcription of Audio/Video Content and Visual Entity Extraction for Multimedia Searchability

Knowledge Graph Creation

Automatically Map Relationships Between Entities in All Enterprise Datasets

Hybrid Retrieval Engine

Optimal Relevance through Combination of Full-Text Indexes, Structured Metadata, Semantic Indexes

Configurable AI Agents

Secure Assistants Using Machine Learning to Support Company Workflows and Security Requirements

Automated Classification

Categorizing Content and Enriching Metadata at Scale via Machine Learning

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