Allganize (올거나이즈)

Enterprise RAG 'AI coworkers' with layout-aware source citations

Agents & Automation Enterprise Has API
Researched · Published · Reviewed
RECATOOLS Score
6.8 / 10
Capability
7.5
Value for money
6
Ease of use
6
ASEAN readiness
5.5
API quality
7
Founded
HQ
Users
Launched
Developer

Overview

Allganize is a Seoul-founded (2017) enterprise AI platform building autonomous 'AI coworkers' for document analysis and report generation, with RAG 2.0 layout-preserving citations and SaaS, on-premise or hybrid deployment across 200+ clients including SMBC and Fujitsu.

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Pricing

Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.

Starter
$3,000/mo
200,000 credits included
  • Credit-based usage
  • Multi-LLM access
  • $2/100 credits overage
Professional
$5,000/mo
400,000 credits included
  • Credit-based usage
  • Multi-LLM access
  • $2/100 credits overage
Advanced
$7,000/mo
600,000 credits included
  • Credit-based usage
  • Multi-LLM access
  • $2/100 credits overage
Enterprise
$10,000/mo
1,000,000 credits included
  • Lower overage rate ($1/100 credits)
  • On-prem/hybrid deployment
  • Custom SLAs and consulting add-on

What you can produce with Allganize (올거나이즈)

  • RAG 2.0 engine with layout-preserving source citations
  • Autonomous "AI coworker" agents for document analysis and reporting
  • SaaS, on-premise and hybrid deployment
  • Multi-LLM support (GPT, Claude, Gemini, DeepSeek and others)
  • REST APIs, SSO and an MCP bridge
  • SOC 2 Type II and ISO 27001 certified
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ASEAN Perspective

Allganize (올거나이즈) in Southeast Asia

ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).

RECATOOLS Verdict

Allganize has been at this since 2017, longer than most enterprise RAG vendors, and its client list — SMBC, Nomura, Hitachi, Fujitsu, KB Securities — shows real traction in Korean and Japanese financial services and manufacturing, sectors that don't sign with vendors who can't clear a security review. The RAG 2.0 engine's layout-preserving citations, showing exactly where in a source document an answer came from, address a genuine hallucination-trust problem, and on-prem or hybrid deployment matters for banks that can't ship documents to a third-party cloud.

It's raised $35M across rounds and has talked about a Japanese exchange listing since 2022 without delivering one yet, worth knowing if you're evaluating it as a long-term platform bet rather than a point solution. Pricing starts at $3,000/month for a credit-based Starter plan and scales to $10,000+/month at Enterprise — squarely enterprise budget territory, with a 30% platform cut on third-party app revenue. Strong pick for regulated APAC enterprises; not built for anyone without a real procurement process.

Independent AI-assisted assessment by RECATOOLS.

What people say

Allganize's strongest signal is its client roster rather than review-site scores: the company counts Sumitomo Mitsui Banking Corporation, Nomura Securities, Hitachi, Fujitsu and KB Securities among its 200+ enterprise and public-sector customers, concentrated in Korea and Japan. One case study from a Mitsubishi Chemical Group customer-support manager reports "over 75% automation of employees and customer queries with some categories reaching 100%" after deploying Allganize's Alli platform — a specific, sourced number rather than the vaguer language vendors usually lean on.

Allganize cites 95% accuracy pulling answers from documents and data, and some customers report ticket-resolution-time cuts of up to 80%, though those are vendor-reported figures rather than independently audited benchmarks. Where more independent feedback exists, on aggregator sites collecting user comments, the interface is repeatedly called easy to navigate and support response quality gets singled out as a strength. The recurring criticism is initial setup: several users describe onboarding as more involved than expected, and pricing structure comes up as a friction point for smaller teams.

The credit-based pricing explains some of that friction. Starter runs $3,000/month for 200,000 credits, scaling through Professional ($5,000/mo, 400K credits) and Advanced ($7,000/mo, 600K credits) to Enterprise at $10,000/month for 1 million credits, with overage priced at $1-2 per 100 credits depending on tier. A $5,000/month consulting add-on is available on top, and third-party apps built on the platform split revenue 70/30 in the developer's favor. None of that is small-team pricing.

On the corporate side, Allganize raised a $20 million Series B in 2024 (bringing total funding to $35 million) with the stated goal of funding a Japanese Stock Exchange listing by 2025 — a target that, as of mid-2026, hasn't been hit, with no recent news confirming a revised timeline. That's not a red flag by itself, but it's worth knowing if IPO-driven governance or liquidity timing factors into how you're evaluating the vendor as a long-term partner rather than just a product.

Summary of public user & expert reviews, compiled by RECATOOLS.

About this listing

Researched on
Published on
Last reviewed

This entry was compiled from publicly available data including Allganize (올거나이즈)'s official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Allganize (올거나이즈) unless explicitly stated.

Data accuracy

Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.

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