Kore.ai Leads Forrester Wave Cognitive Search Q4 2025

TL;DR: Kore.ai was named a leader in the Forrester Wave cognitive search Q4 2025, with top marks in 11 of 21 criteria and the highest ranking in strategy (Kore.ai, 2025). The bigger story is the report itself: Forrester now ranks enterprise search vendors with the same structured rigor it applies to databases, which means cognitive search has graduated from a feature into a category buyers shortlist on its own.

For years, enterprise search was a checkbox inside some other product. You got it bundled with a content management system or a help desk, and nobody benchmarked it. That era is ending. When an analyst firm publishes a dedicated Wave for cognitive search and scores 14 vendors against 21 criteria (Kore.ai, 2025), it is treating search the way it treats foundational infrastructure. This post looks at what the kore ai forrester wave cognitive search q4 2025 leader placement actually tells us, and why the format of the report matters more than any single vendor’s dot on the chart.

What did the Forrester Wave cognitive search Q4 2025 actually find?

Forrester evaluated 14 vendors against 21 criteria and placed Kore.ai in the Leaders group. Kore.ai received the highest score possible in 11 of those criteria and ranked highest in the strategy category (Kore.ai, 2025).

The criteria themselves are worth reading, because they read like an infrastructure spec sheet. The areas where Kore.ai scored full marks included data connectors, data ingestion and prep, search methods, intent understanding, results, applications and workflow, testing and evaluation tools, hosting, platform security, innovation, partner ecosystem, and adoption (Kore.ai, 2025).

Notice what that list is not. It is not “relevance” and “speed.” It is connectors, ingestion, security, hosting, and evaluation tooling. Those are the things you grade a database or a data platform on. The scoring sheet for cognitive search now looks like the scoring sheet for core enterprise infrastructure.

How a Forrester Wave works, and why the format is the signal

A Forrester Wave is a structured comparison of the most important vendors in a defined market, scored against a public, consistent methodology and plotted on two axes: current offering and strategy (Forrester, 2025). Analysts score each vendor relative to the others, interview real customers rather than relying on surveys, and publish the scores and the scales behind them so buyers can see the reasoning (Forrester, 2025).

Firms reserve that treatment for markets they consider real and comparable. Forrester covers more than 2,500 vendors across its Wave and Landscape research portfolio (Forrester, 2025), and a category earns a dedicated Wave only when buyers are making deliberate, head-to-head purchasing decisions in it. Databases got that treatment decades ago. Data warehouses, CRM, and integration platforms followed. Cognitive search getting its own Q4 2025 Wave put it in that company.

So the headline for the industry is not just that one vendor led. It is that enterprise search is now a thing you put out to bid, score on a rubric, and defend to a procurement committee.

Why is cognitive search suddenly infrastructure?

The short answer is agents. Forrester’s own framing in the report is that cognitive search is becoming the “brain” behind agentic AI (Kore.ai, 2025).

Here is the mechanism. An AI agent is only as good as the context it can retrieve. Ask an agent to draft a renewal quote, resolve a ticket, or summarize a customer’s history, and every useful answer starts with a retrieval step against your real systems. If that retrieval is shallow, the agent confidently makes things up. If it is deep and governed, the agent grounds its answer in fact.

That reframes search from a convenience for humans into the dependency layer for software. Cognitive search is enterprise search that understands intent and context across many connected systems, rather than matching keywords in one. When agents sit on top of it, the quality of search becomes the ceiling on the quality of every agent you deploy. A weak search layer is no longer an annoyance; it is a hard limit on your AI roadmap.

That is also why the criteria look the way they do. Connectors, ingestion, security, and evaluation tooling are exactly what you need to feed and trust an agent. They are infrastructure concerns, not search-box concerns.

What this means for the semantic layer underneath

A ranking validates a category. It does not solve the underlying problem, which is that the knowledge an agent needs is scattered across dozens of tools that do not share context.

This is the layer SemanticOS works on. SemanticOS is a knowledge-graph and AI-search system, a unified semantic layer that connects fragmented enterprise tools so both people and AI agents can find and reason over institutional knowledge. The Forrester criteria, connectors, ingestion, intent understanding, and results, describe the plumbing required to make scattered knowledge queryable as one thing. A knowledge graph is one way to build that plumbing: it models people, documents, projects, and systems as connected entities, so a single query can traverse relationships that would otherwise stay locked in separate apps.

The point is not which logo leads the chart. The point is that buyers now have a shared rubric for asking whether their search and retrieval layer is good enough to build agents on. That rubric is the useful artifact.

A concrete example

Consider Vantage Health, a mid-size health insurer rolling out an AI agent to help its claims team. The pilot looked great in the demo and fell apart in production. When an adjuster asked the agent about a prior authorization exception, it cited a policy that had been retired eight months earlier.

The agent was not broken. Its retrieval layer was. The current policy lived in a SharePoint folder, the exception history sat in the claims system, and the relevant email thread was in a shared mailbox, none of them connected. The agent retrieved the first plausible match and presented it with full confidence.

When Vantage Health’s procurement team went looking for a fix, they did not have to invent their own checklist. They pulled the Forrester Wave criteria and asked each vendor to demonstrate data connectors, ingestion and prep, intent understanding, and platform security against their actual systems (Kore.ai, 2025). The maturing of cognitive search into a graded category gave a non-technical buyer a credible way to evaluate the layer their entire agent strategy depended on. That is what a Wave is for.

Key takeaways

• Forrester named Kore.ai a leader in the Forrester Wave cognitive search Q4 2025, with top scores in 11 of 21 criteria and the highest strategy ranking (Kore.ai, 2025).
• The real signal is the report’s existence: a dedicated, structured Wave means analysts now rank enterprise search the way they rank databases.
• The scoring criteria, connectors, ingestion, security, hosting, and evaluation, read like an infrastructure spec, not a search-box feature list.
• Cognitive search is becoming the retrieval brain for AI agents, so its quality caps the quality of every agent built on top of it.
• A graded category gives buyers a shared rubric to judge whether their semantic and retrieval layer is ready for agentic AI.