How much does AI consulting cost?

BlokAI's engagements range from $5,000 to $75,000 depending on scope. Simple automations and LLM integrations start around $5K–$15K. Custom AI agent systems and full data infrastructure projects run $30K–$75K. We scope every project before committing to a price.

What does BlokAI build?

BlokAI builds AI agents, LLM applications, RAG systems, automation pipelines, and data infrastructure for startups and SMBs. We take projects from architecture to production — not demos, not prototypes.

Is BlokAI based in Japan?

Yes. BlokAI is a solo studio run by Kent Tran, based in Tokyo, Japan. We work with clients globally in English.

What is RAG and why does my business need it?

RAG (Retrieval-Augmented Generation) lets AI systems search your own documents, databases, or knowledge bases before answering — instead of relying only on training data. It powers AI customer support, internal search tools, and sales enablement systems that are accurate and up-to-date.

How Much Does AI Consulting Actually Cost? 2025 Honest Pricing Guide

"AI agents are moving rapidly from experimental to enterprise-ready. Gartner predicts that by 2028, 15% of day-to-day business decisions will be made autonomously by AI agents." — Gartner, June 2025

I wrote a version of this post in June 2024. A lot has changed in a year: the technology has evolved, the market has matured, project patterns have become more established, and costs have both increased (for complex, agent-heavy projects) and decreased (for commodity implementations that are now faster to build).

This is the 2025 update.

How the Market Has Shifted in 12 Months

A year ago, there was still significant confusion in the market about what AI implementation projects actually involved. Many clients came with unrealistic expectations about build times and costs, often set by vendors who'd quoted low to win the engagement and then hit overruns.

The market has gotten more sophisticated. Buyers have better questions. The projects that get scoped and delivered well are more predictable now because the patterns are more established. RAG systems, agent workflows, document processing pipelines — these aren't novel territory anymore. Scoping them accurately is easier.

What's new in the complexity frontier: multi-agent systems, sophisticated evaluation infrastructure, AI systems integrated with complex enterprise data infrastructure, and Japan-market-specific requirements (multilingual, compliance, enterprise integration patterns). These remain genuinely complex and difficult to scope.

Rate Benchmarks (Japan/Global Market, Mid-2025)

Independent AI consultant (strong portfolio, 3+ years): ¥25,000–¥40,000/hour ($160–$260), ¥200,000–¥320,000/day Small AI studio (3-8 person team): ¥30,000–¥55,000/hour ($190–$360), varies by seniority of lead Mid-size consultancy with AI practice: ¥50,000–¥100,000/hour ($325–$650) at the senior end — often lower for delivery staff Big consultancies (Big 4 AI practice, major tech consultancies): ¥80,000–¥150,000+/hour ($520–$975) at partner/principal level Japan-specific note: AI consulting in Japan with Japanese-language capability and enterprise cultural fluency commands a meaningful premium over equivalent work in Western markets — typically 15-25% above comparable international rates. The talent pool is thinner relative to demand.

Project Cost Guide (2025 Figures)

Strategy and Assessment Engagements

AI readiness assessment (what's your data situation, what are your opportunities, what should you build first): ¥750,000–¥2,000,000 ($5,000–$13,000), 2-4 weeks AI roadmap development (multi-department, full business analysis, prioritised implementation plan): ¥2,000,000–¥6,000,000 ($13,000–$40,000), 4-8 weeks

Implementation Projects

RAG / Knowledge Base System

Basic (single data source, internal users, standard interface): ¥1,800,000–¥3,500,000 ($12,000–$23,000)

Complex (multi-source, external users, multilingual, enterprise integration): ¥4,000,000–¥10,000,000 ($26,000–$65,000)

Timeline: 6-14 weeks depending on complexity

Document Processing Automation

Invoice/form extraction pipeline: ¥2,000,000–¥4,500,000 ($13,000–$30,000)

Complex document analysis (contracts, technical docs, compliance): ¥4,000,000–¥9,000,000 ($26,000–$59,000)

Timeline: 6-12 weeks

AI Agent Implementation

Single-workflow agent (research, reporting, lead intel): ¥3,000,000–¥6,000,000 ($20,000–$40,000)

Multi-agent system (multiple agents coordinating): ¥6,000,000–¥18,000,000 ($40,000–$118,000)

Timeline: 8-20 weeks

Customer Support AI

Internal (employee helpdesk): ¥2,500,000–¥5,000,000 ($16,000–$33,000)

External-facing (customer-facing chatbot with escalation): ¥5,000,000–¥12,000,000 ($33,000–$78,000)

Timeline: 8-16 weeks

Ongoing Services

Maintenance retainer (monitoring, updates, improvements): ¥150,000–¥500,000/month ($1,000–$3,300) Infrastructure costs (vector database, LLM API, hosting): ¥30,000–¥300,000/month ($200–$2,000) depending on usage volume

What Moves the Needle on Cost

Data quality is still the biggest wildcard. Projects where the client arrives with clean, well-structured, accessible data run significantly under typical cost ranges. Projects that discover data chaos mid-engagement (the norm, not the exception) run over. Integration complexity. The model call is cheap. The integration with your existing CRM, ERP, helpdesk, or proprietary systems is often where most of the engineering hours go. Evaluation requirements. Rigorous evaluation infrastructure — automated test sets, production monitoring, systematic quality tracking — adds 15-25% to project cost and is worth every yen. Systems without it degrade faster and cost more to fix later. Japanese language requirements. Japanese-language RAG systems require Japanese-optimised embedding models, different chunking strategies for Japanese text, and sometimes different retrieval approaches. This adds complexity and cost — roughly 20-30% premium over English-only equivalents in our experience. Regulatory and compliance requirements. Heavily regulated industries (finance, healthcare, legal) add significant compliance overhead to any AI project. Not optional, not cheap.

How to Use This Information

These ranges represent quality work from experienced practitioners. The lower end of each range assumes good client conditions (clean data, clear requirements, responsive stakeholders). The upper end assumes more complexity.

If you're getting quotes significantly below these ranges, ask why. Common reasons: less experienced team, significant scope assumptions that will lead to change orders, or plans to cut corners on evaluation and operations infrastructure.

If you're getting quotes significantly above these ranges from smaller shops (not Big 4), ask for justification. The market is more competitive now and rates have stabilised.

The right question isn't "how do I find the cheapest AI consultant?" It's "how do I find the consultant who will deliver the most value for this specific project?" Those are different questions with different answers.

Want to implement AI in your business? Book a 30-minute architecture call at blok-ai.com.