Question 1

What exactly does KorBon AI do?

Accepted Answer

We help businesses actually use AI in their day-to-day operations. That means we figure out where AI can help your team (consulting), build the systems to make it happen (agentic workflows), and train your people so they can run it themselves (education). Think of us as the team that takes AI from 'interesting idea' to 'working tool your team uses every day.'

Question 2

Is this only for big tech companies?

Accepted Answer

Not at all. We work with any business that has repetitive work that could be automated. Support teams drowning in tickets, operations teams manually creating reports, customer success teams routing inquiries. If you have 5+ people doing similar tasks repeatedly, there's probably a way AI can help.

Question 3

We have zero AI experience. Can you still help us?

Accepted Answer

Yes, that's actually most of our clients. You don't need to know anything about AI models or machine learning. We handle all the technical complexity. You just need to know your business and where your team wastes time on manual work. We'll figure out the rest together.

Question 4

How do we get started?

Accepted Answer

Book a call with us. We'll spend 30-45 minutes understanding your business, what's eating up your team's time, and what tools you currently use. If there's a good fit, we'll propose a Discovery Sprint to map out specific opportunities. No pressure, no commitment required for that first conversation.

Question 5

What does a typical engagement look like?

Accepted Answer

Most engagements follow three phases: (1) Discovery Sprint (1-2 weeks): We assess your operations and identify where AI can help most. (2) Pilot Build (3-6 weeks): We build and deploy one working AI system like automated ticket triage or report generation. (3) Scale & Enablement (ongoing): Once the pilot proves value, we expand to more workflows and train your team to own it.

Question 6

How long until we see results?

Accepted Answer

You'll see your first working AI system within 4-8 weeks from kickoff. The Discovery Sprint gives you a clear roadmap in week 2. The Pilot Build delivers a production-ready system by week 8. Unlike most AI projects that stay in 'pilot hell,' we focus on shipping something useful fast.

Question 7

What do you need from us?

Accepted Answer

Three things: (1) Access to people who know the workflows we're automating (like your support lead or ops manager). (2) Access to the tools and systems we'll integrate with (APIs, Slack, CRM, etc.). (3) Someone who can review and approve the AI's work during testing. That's it - we handle the rest.

Question 8

Do you work remotely or do you need to be on-site?

Accepted Answer

We work remotely by default, which keeps costs down and timelines fast. For larger implementations or if you prefer, we can do on-site workshops or design sessions. Most of our clients find remote works great since we're constantly sharing screens and collaborating in your existing tools anyway.

Question 9

Do you just give us a plan, or do you actually build it?

Accepted Answer

We build it. Yes, you'll get a strategy and roadmap, but our focus is shipping working systems. We write the code, set up the integrations, deploy to production, and train your team. You're not paying for a consultant's deck - you're paying for software that does real work.

Question 10

What's an 'agentic workflow'? (In normal English please)

Accepted Answer

Think of it as an AI assistant that can do multi-step tasks on its own. For example: (1) Read a support ticket, (2) Figure out what category it is, (3) Look up relevant documentation, (4) Draft a response, (5) Send it to a human for approval, (6) Post the approved response. That entire sequence runs automatically - you just review step 5 before it goes out. That's an agentic workflow.

Question 11

What are some real examples of what you build?

Accepted Answer

Common ones: Automated support ticket triage and response drafting. Weekly report generation from your data sources. Routing customer inquiries to the right team member based on content. Meeting notes → action items → calendar invites. Document Q&A for internal knowledge bases. Lead qualification from form submissions. Each one saves hours per week and reduces errors.

Question 12

Does this work with tools we already use?

Accepted Answer

That's the whole point. We integrate with Slack (for notifications and approvals), your CRM (Salesforce, HubSpot), ticketing systems (Zendesk, Jira), Google Workspace or Microsoft 365, and your internal APIs. The AI works inside your existing workflow - your team doesn't have to learn a new platform.

Question 13

Can AI make mistakes? How do we stay in control?

Accepted Answer

Yes, AI can make mistakes. That's why we build review checkpoints into every workflow. For example, AI might draft a customer response, but a human approves it before it sends. Or AI might categorize a ticket, but route edge cases to a person. You decide what needs human review and what can run automatically. Full control, but way less manual work.

Question 14

How accurate is the AI?

Accepted Answer

It depends on the task. For well-defined tasks like categorization or data extraction, AI can hit 95%+ accuracy. For creative tasks like drafting responses, it's more about saving time (AI does the first draft in 10 seconds, human edits in 30 seconds vs. writing from scratch in 5 minutes). We measure accuracy during the pilot and tune it before going live.

Question 15

How much does this cost?

Accepted Answer

Pricing varies based on scope and complexity. Discovery Sprints help us assess opportunities and provide accurate estimates. Pilot Builds depend on the workflow complexity and integrations needed. Contact us for a detailed quote based on your specific needs. Most clients see positive ROI within 3-4 months from time savings alone.

Question 16

What kind of ROI can we expect?

Accepted Answer

Typical outcomes: 40-60% reduction in cycle time for automated workflows (e.g., 2-day support response becomes same-day). 10-20 hours/week saved per team member on repetitive tasks. Fewer errors in manual data entry or categorization. Most clients break even in 3-4 months and see 2-3X ROI in the first year.

Question 17

Are there ongoing costs after the pilot?

Accepted Answer

Yes, but they're typically manageable. You'll pay for the AI model usage (varies by volume - providers like OpenAI or Anthropic charge per request). If you want ongoing support, monitoring, and new feature development, we offer retainer packages. Many clients just do the pilot and run it themselves.

Question 18

How does payment work?

Accepted Answer

Discovery Sprints are typically paid upfront. Pilot Builds are usually 50% upfront, 50% at delivery. Ongoing retainers are monthly. We're flexible for larger organizations - happy to work within your procurement process.

Question 19

Is our data safe? Where does it go?

Accepted Answer

Your data stays in your systems or with the AI provider you choose (like OpenAI or Anthropic). We don't store your operational data. When we integrate AI with your tools, we use secure API connections with proper access controls. Everything is logged and auditable. We never use your data to train external AI models.

Question 20

How do you handle confidentiality?

Accepted Answer

Every engagement is covered by a strict NDA before we even see your data. We treat your business processes, customer information, and internal systems with complete confidentiality. Many of our clients are in competitive or regulated industries - we know how to handle sensitive information.

Question 21

What about compliance? (HIPAA, SOC 2, etc.)

Accepted Answer

We design systems with compliance in mind. If you're in healthcare (HIPAA), finance (SOC 2), or another regulated industry, we'll architect the AI workflows to meet those requirements. We work with compliant AI providers and ensure proper data handling, access controls, and audit trails are built in from day one.

Question 22

Who on your team will have access to our systems?

Accepted Answer

Only the engineers directly working on your project - typically 1-2 people. We use least-privilege access (only what's needed to integrate and test). All access is logged. When the project is done, access is revoked. We're very careful about this, especially for clients with sensitive data.

Question 23

Will you train our team, or do we depend on you forever?

Accepted Answer

We train your team - that's a core part of every engagement. We don't want you dependent on us. During the Pilot Build, we document everything, create runbooks, and do knowledge transfer sessions. By the end, your team should be able to monitor the AI, update prompts, and troubleshoot common issues on their own.

Question 24

Do we need a technical team to use this?

Accepted Answer

Not for day-to-day use. We design systems so non-technical people (like support managers or operations leads) can monitor performance, adjust settings, and review outputs. You'll want someone technical on your side for initial integration and ongoing maintenance, but it doesn't have to be a full engineering team.

Question 25

What workshops do you offer?

Accepted Answer

We offer: (1) AI for Operators (half-day) for support/ops teams to learn practical AI use. (2) Agentic Workflow Design Lab (full-day) for technical teams to design systems. (3) Leadership Briefing (60-90 min) for executives to understand ROI and risk. (4) Team Office Hours (ongoing) for troubleshooting. (5) Internal Playbook creation for documenting your AI standards.

Question 26

Do you guarantee results?

Accepted Answer

We can't guarantee specific business outcomes (too many variables), but we do guarantee you'll have a working AI system deployed by the end of a Pilot Build. If we can't identify any high-ROI opportunities during Discovery, we'll tell you honestly and you won't waste money on a pilot.

Question 27

How do you measure success?

Accepted Answer

We start every Discovery Sprint by defining success metrics with you. Usually it's: time saved (hours/week), cycle time reduction (days → hours), error reduction, or cost savings. We measure baseline during Discovery, track during Pilot, and report on improvements. You'll know if it's working.

Question 28

What if something breaks after you leave?

Accepted Answer

We provide documentation and training so your team can handle common issues. For ongoing support, we offer Scale & Enablement retainers with SLAs for response time. Many clients start with a retainer for the first few months post-launch, then transition to running it themselves once they're confident.

Question 29

What happens after the first pilot works?

Accepted Answer

Most clients expand to 2-3 more workflows in the first year. Once you see one AI system working (e.g., support triage), it becomes easier to identify other opportunities (e.g., report generation, lead routing). We help you prioritize what to build next based on ROI and technical feasibility.

Question 30

Which AI models do you use?

Accepted Answer

We're model-agnostic and use whatever fits best: GPT-4 or GPT-4o for general tasks, Claude for long documents and analysis, open-source models for cost-sensitive or private deployments. We'll recommend the right fit based on your use case, budget, and security requirements.

Question 31

Where does the AI run?

Accepted Answer

Usually on cloud AI providers (OpenAI, Anthropic, etc.) via secure API calls. For clients with strict data residency or security requirements, we can deploy models on your own infrastructure (AWS, Azure, GCP). We'll design it to fit your compliance needs.

Question 32

Can you integrate with our custom internal tools?

Accepted Answer

Yes. If your internal system has an API (or we can build one), we can integrate AI with it. We've connected AI to custom CRMs, proprietary ticketing systems, legacy databases, and internal admin tools. As long as we can read/write data programmatically, we can make it work.

Question 33

How much maintenance do these systems need?

Accepted Answer

Less than you'd think. Once deployed, most AI workflows run automatically. You'll want to check quality metrics weekly (we set up dashboards for this) and update prompts occasionally as your business changes. Major maintenance is usually only needed when you update your underlying tools or want to add new features.

Frequently Asked Questions

Getting Started