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.

The ROI of AI Automation: A Framework for Calculating Business Value

"OpenAI's o1 model usage grew over 300% quarter-over-quarter as enterprises adopted reasoning models for complex analytical and planning tasks — signalling that slow-thinking AI has found its market." — OpenAI, September 2025

The number one question we hear from business leaders before they commit to an AI project: "What's the return?"

It's the right question. And it deserves a real answer — not a vague gesture at "efficiency gains" or a vendor's generic case study.

Here's the framework we use with clients to calculate AI automation ROI before a project starts, and to measure it after.

Why Standard ROI Calculations Break Down

Most people try to apply traditional cost-benefit analysis to AI projects. The problem: AI doesn't fit neatly into the model.

Traditional automation reduces a specific, measurable cost (labor for task X). AI automation operates on probability — it handles most cases well, some cases imperfectly, and occasionally gets things wrong. The value is real but noisier.

You also have to account for capability expansion. Sometimes AI doesn't just reduce the cost of existing work — it makes entirely new work possible. That upside doesn't appear in a standard cost calculation.

Use this framework as a starting structure, not a spreadsheet to fill in once and forget.

The Four Value Levers

Every AI automation creates value through one or more of these mechanisms:

1. Labor hour reduction. The most measurable. Someone was spending X hours per week on a task; now they're spending Y. The delta is quantifiable at their loaded hourly cost. 2. Speed/throughput increase. AI can process faster than humans at scale. If response time or processing speed affects revenue (sales follow-up, quote turnaround, content production), the velocity gain has direct commercial value. 3. Error/cost reduction. Mistakes cost money — in corrections, returns, customer churn, compliance issues. If AI reduces error rate, calculate the average cost per error and multiply by errors prevented. 4. Revenue enablement. This is the hardest to quantify but often the largest. AI that helps your team do more deals, respond to more leads, personalize at scale, or enter new markets generates revenue that wouldn't exist otherwise.

Map your use case to one or more of these before building the business case.

The Calculation Structure

Here's the simplified model:

Annual Gross Benefit = (Hours saved × Loaded hourly cost) + (Error reduction × Avg. error cost) + (Revenue lift) Total Investment = Build cost + Annual run cost + Internal time cost Payback period = Total Investment ÷ Annual Gross Benefit 3-Year ROI = (3 × Annual Gross Benefit − Total Investment) ÷ Total Investment

Run the numbers at three scenarios: conservative (50% of projected benefit), base case, and optimistic (150%). If your conservative case still shows positive ROI within 18 months, you have a compelling project. If it only works in the optimistic scenario, think harder about the assumptions.

The Costs People Miss

Internal time. Your team will spend time on requirements, testing, iteration, and training. This isn't free. Budget 0.25–0.5 FTE equivalent for the first few months of a meaningful implementation. Ongoing governance. AI systems require monitoring. Outputs drift. Models update. Data quality degrades. Someone needs to own this — budget at least a few hours per week per system in production. Integration complexity. The AI model is rarely the expensive part. Connecting it to your existing systems, handling edge cases, and making it reliable is where cost surprises appear. Build in a 30–50% buffer on integration estimates. Retraining and iteration. Your first version won't be your best version. Budget for at least two rounds of meaningful refinement in the first year.

Benchmarks to Sanity-Check Your Numbers

Based on implementations across SMBs, here are rough ranges for common use cases:

Customer support automation: 30–60% ticket deflection; payback typically 6–12 months
Sales outreach automation: 40–70% time reduction on prospecting; payback 3–6 months
Document processing (invoices, contracts): 60–80% processing time reduction; payback 4–9 months
Internal knowledge/Q&A systems: Hard to measure in labor hours, high in decision quality and onboarding speed; payback 12–24 months

If your projections are wildly outside these ranges in either direction, revisit your assumptions.

When ROI Isn't the Right Question

Some AI investments are about strategic position rather than short-term return. If your competitors are deploying AI in customer experience and you aren't, the cost of not acting doesn't show up in a spreadsheet — until you see it in churn numbers a year later.

Be honest about whether you're calculating ROI or rationalizing a decision you've already made strategically. Both are valid; they just require different conversations.

The best AI decisions we see are made when teams understand the financial model clearly enough to not need it as the primary driver — because the strategic logic is strong enough on its own.

Want to implement AI? Book a call at blok-ai.com