AI Services in Search Engine & RAG

AI search engines that leverage semantic understanding and RAG technology for information retrievalFeaturing 8 AI services in total.

ジェンビュー

Genview

Genview is a GEO (generative AI search optimization) platform built to help your brand be understood correctly and chosen by generative AI such as ChatGPT and Gemini. Whether your name comes up in answers to questions like "What's a good ~ ?" affects every stage of the buying journey, from awareness and consideration to purchase and word of mouth. Genview makes visible the gap between the ideal brand image you want to convey and what generative AI actually says, working end-to-end from measurement and diagnosis through to improvement proposals across three perspectives: brand perception, mentions and citations for important queries, and your whole website (structured data, llms.txt, and more). It goes beyond mere measurement to present concrete actions for improvement. Genview is operated by FID, Inc. (Shinjuku, Tokyo), which has provided CRM and marketing support for more than 15 years, and was officially released on August 1, 2026, with 30 companies participating as early adopters in its beta.

# LLMO・GEO（生成AI検索最適化）# マーケティング# 検索エンジン・RAG# 生成AI（LLM）# 業務効率化# 生産性向上

ヘルプフィール

Helpfeel

An AI knowledge search system from Helpfeel Inc., built around the patented “intent prediction search” technology. Its defining strength is landing users on the right FAQ article even from vague phrasing, spelling variants, or typos — the company reports a 98% search hit rate. Alongside search-type FAQ, it offers an AI agent that searches across internal PDFs and Word files to answer, an inquiry form that shows answers before submission, and analysis of accumulated inquiry data (VoC) with article improvement proposals, all on one platform. Deployed on 900+ sites as of January 2026, with a reported 70% reduction in inquiries and a 99% retention rate. Pricing is a package of an initial fee plus a monthly fee, quoted individually.

# AIチャットボット# 検索エンジン・RAG# AIエージェント# 業務効率化# コスト削減# 自動化・省力化# 日本語対応

パープレキシティ

Perplexity

An AI-powered answer engine that searches the latest information across the web from a single question and answers with sources (citations). Switch among high-performance models like GPT, Claude, and Gemini, and use Deep Research for deeper investigation, the "Comet" AI browser, and agents that autonomously run tasks. Fully supports Japanese.

# 検索・レコメンド# 検索エンジン・RAG# AIエージェント# 要約・翻訳# 生成AI（LLM）# 日本語対応

メモリーク

Memoriq

A private, end-to-end-encrypted, open-source 'AI memory' that lets you save and search conversations from ChatGPT, Claude, Gemini, and Grok across one vault. A browser extension captures chats and encrypts them on your device (AES-256) before upload; self-hosting is also possible. Keep your important AI exchanges without leaving them in plaintext on the cloud.

# 検索エンジン・RAG# AIエージェント# 業務効率化# 生産性向上

ヴァンナエーアイ

Vanna AI

An open-source (MIT) Text-to-SQL framework that generates accurate SQL from natural-language questions. Train it on your database's DDL, docs, and example SQL, and it generates runnable SQL via agentic retrieval. Now "Vanna 2.0 (The SQL Agent)" with user-aware row-level control and a web chat UI; the OSS core is free while managed Vanna Cloud is paid. Works with major DBs (Postgres, Snowflake, BigQuery) and LLMs (OpenAI, Anthropic).

# 検索エンジン・RAG# コード生成# AIエージェント# 生成AI（LLM）

カサナレ

Kasanare

An enterprise 'work-completion AI platform' that integrates company-specific knowledge understanding (beyond RAG), usage governance, and action control over existing business systems (including legacy) to complete actual work — not just generate answers. With adoption at Mitsubishi UFJ Trust and Banking and others. By Kasanare Inc.

# AIエージェント# AIチャットボット# 検索エンジン・RAG# 業務効率化# 自動化・省力化# 日本語対応

ディープシーク

DeepSeek

DeepSeek is an open large language model (LLM) family, together with the AI chat and API services built on it, developed by DeepSeek (Hangzhou, China). You can try the latest flagship models, DeepSeek-V4 (V4-Flash / V4-Pro), for free in chat, while the developer API offers a 1M-token long context, Thinking mode, Agent capabilities, and OpenAI / Anthropic compatibility, all at a low price. DeepSeek also publishes purpose-built models such as the reasoning-focused R1 and its code and vision models.

# 検索エンジン・RAG# 生成AI（LLM）

ジェヴ

Jev

Jev is the first System One model from TypeSafe AI, released on 15 September 2026. Unlike an LLM it generates no text: give it a state (text or JSON) and it returns typed values — Choice (classification), Score (rating) and Noul (a 0–1 truth value) — each with probabilities and a calibrated confidence. Because no string comes back, there is nothing to parse and nothing to validate. Vendor-published figures are 70–500 ms end to end and $0.042 per million input tokens, with output tokens free. Questions in one request are evaluated in parallel, so stacking them barely changes latency — which suits support triage, LLM guardrails and RAG re-ranking, where the same judgement repeats at volume. In early access behind a waitlist as of September 2026; the docs state that CJK scripts are accepted with lower accuracy than English.

# API・SDK# AIエージェント# 検索エンジン・RAG# 自動化・省力化# コスト削減

Recommended Articles on Search Engine & RAG

What Jev Is [September 2026]: The AI That Generates No Text — How System One Models Work, Pricing and Use Cases

On 15 September 2026, TypeSafe AI came out of two years of stealth with $40M in funding and shipped Jev — and it spread past social media into developer communities, with Qiita running an official campaign from 16 September to 2 October. What caught on was not the benchmarks but the positioning: an AI that does not generate text. Jev does not chat; it picks from options you defined and returns the answer with a probability attached. This article covers what the three question types (Choice, Score, Noul) actually return, the speculative fan-out that makes stacking questions free in latency, the pricing model of $0.042 per million input tokens with output free, the path from waitlist to Python SDK, HTTP API and the Claude Code skill, how to gate on confidence and route the uncertain cases to a person, and where it pays off — support triage, LLM guardrails, RAG re-ranking. It also covers what TypeSafe publishes about its own weak spots: lower accuracy on CJK scripts, unreliable counting, and weak date comparison.

LLMO/GEO Tools Compared: 12 Best Picks for 2026 (Domestic & Overseas) — by Supported AI, Features, and Pricing

A thorough comparison of LLMO/GEO optimization tools that help your brand get cited and recommended in AI search (ChatGPT, Gemini, and more), split into 8 Japanese tools (Genview, DolphinX AIO, AKARUMI, Mieruca GEO, SUPER ACT, User Insight, BringRitera, LLMOinsight) and 4 overseas tools (Profound, Peec AI, OtterlyAI, AthenaHQ), by supported AI, feature type, pricing (monthly / annual), and free tiers. Includes a 14-tool comparison table (adding the GEO-ready production tools Writesonic and Readdy), a three-line verdict, picks by goal, six axes for choosing, price ranges, free options, and an FAQ on LLMO vs. GEO and the metrics for measuring results — based on official listings as of August 2026.

Customer Support AI Tools Compared: 8 Products [2026] | Pricing, Automation Scope, and How to Choose

A comparison of eight customer support AI tools on pricing, how much they can automate, and Japanese-language support. Sorts chatbots, AI agents, and VoC analytics into three types, then walks through the four decision criteria, a four-step rollout, and frequently asked questions.