The Forrester Wave™: Cognitive Search Platforms, Q4 2023

What Forrester Said About Sinequa

The Q4 2023 Forrester Wave report contains two specific findings about Sinequa that no other vendor can claim:

On LLM integration and innovation trajectory, Forrester stated that Sinequa continues to build on its existing innovation advantage — having been one of the first vendors to integrate LLMs into search — by using large language models and advanced technologies to deliver deeper and more contextual search experiences.

On enterprise fit and vertical depth, Forrester identified Sinequa as the right choice for large enterprises managing a variety of data types, particularly those with demanding sector-specific data requirements in areas such as pharma and manufacturing, where delivering highly contextual search across multi-modal content is a core operational need.

These are not boilerplate assessments. Forrester’s Wave reports produce vendor-specific findings from structured analyst evaluation and customer interviews. The combination of a first-mover LLM advantage and explicit vertical depth in pharma and manufacturing reflects Sinequa’s actual product architecture and go-to-market focus — not repositioned messaging.

What Is The Forrester Wave™ for Cognitive Search?

The Forrester Wave™ is Forrester Research’s primary vendor evaluation methodology — a structured, criteria-based assessment that identifies the most significant vendors in a given technology market and scores them across three independently weighted dimensions: Current Offering, Strategy, and Market Presence.

• Current Offering measures the breadth and depth of a vendor’s existing product — its features, capabilities, integrations, architecture, and performance across a defined set of evaluation criteria. A vendor that ranks highest on Current Offering has been assessed by Forrester analysts as having the most capable and complete product available in the market at the time of evaluation.
• Strategy measures a vendor’s product roadmap, innovation direction, partner ecosystem, and go-to-market clarity — Forrester’s view of where the vendor is heading and whether that direction aligns with where the market is going.
• Market Presence measures commercial scale — the size of the customer base, revenue, geographic reach, and installed base relevant to the evaluated market segment.

In The Forrester Wave™: Cognitive Search Platforms, Q4 2023, Forrester evaluated 14 vendors across 27 criteria. Sinequa’s Leader position — with the highest score on Current Offering — means Forrester assessed Sinequa’s platform as the most complete and capable cognitive search product among all vendors evaluated at the time of the report.

What Is Cognitive Search? How Forrester Defines the Category

Cognitive search is the application of AI and machine learning to enterprise information retrieval — going beyond keyword matching to understand the meaning, context, and intent behind a query, and to surface relevant information from across an organization’s full content estate, regardless of format, system, or data type.

Where traditional enterprise search returns a ranked list of documents based on keyword frequency, cognitive search applies natural language processing, semantic understanding, knowledge graphs, and machine learning relevance models to deliver contextually accurate results — synthesizing information across structured and unstructured sources to give users answers, not just documents.

In 2023, the cognitive search category was undergoing a significant transition. The emergence of large language models introduced new capabilities for answer synthesis, conversational search interfaces, and retrieval-augmented generation (RAG) — all of which depend on a high-quality, enterprise-grade retrieval layer beneath the generative AI interface. Cognitive search platforms that had already invested in deep NLP, multi-source indexing, and precision relevance were positioned to integrate LLMs productively. Those that had not were exposed to a fundamental architectural gap.

Forrester’s recognition of Sinequa as the highest-scoring vendor on Current Offering in Q4 2023 — explicitly citing LLM integration as an established advantage — placed Sinequa in the first group.

The LLM First-Mover Advantage — What It Means in Practice

Forrester’s specific observation — that Sinequa was one of the first vendors to integrate LLMs into search — reflects a design decision Sinequa made before the generative AI wave made LLM integration a market expectation.

Integrating LLMs into an enterprise search platform is not simply a matter of adding a chat interface. The core challenge is retrieval quality: LLMs can only produce accurate, grounded answers if the retrieval layer surfaces the right information with sufficient precision, breadth, and security awareness. An LLM connected to a weak retrieval system amplifies errors and hallucinations rather than generating useful answers. An LLM connected to a high-precision, enterprise-grade retrieval layer becomes a genuinely useful AI assistant — capable of answering complex queries across large, heterogeneous content estates while respecting the access controls that enterprise security requires.

Sinequa’s LLM integration was built on top of an existing retrieval architecture designed specifically for large, complex enterprise environments: deep connector ecosystem, multi-source indexing, NLP-enriched relevance, and early-binding security. This is the architecture that Forrester recognized when it cited Sinequa’s LLM advantage — not a bolt-on integration, but a retrieval-first design that was ready for generative AI before the rest of the market was looking for it.

Today, this architecture is the foundation of Sinequa’s enterprise agentic AI platform — supporting not just AI assistants and conversational search, but AI agents that retrieve, synthesize, and act on enterprise knowledge across automated workflows.