AI chatbots that know your product, not just language
We build custom chatbots and assistants grounded in your own data and integrated with the systems you already run — for customer support, internal teams, or embedded directly in your product.
Why a custom chatbot
An off-the-shelf widget answers generic questions. A chatbot built around your product, your data, and your support process is what actually reduces tickets and gets used twice.
Grounded in Your Own Content
Built on retrieval over your docs, help center, or internal knowledge base, so answers reflect your product, not a generic script.
Fits Your Existing Systems
Integrated with your CRM, support desk, or product backend, so the chatbot can look things up and take action, not just talk about them.
On-Brand, Not Generic
Tone, scope, and escalation paths designed around your product and your support team's process, not a one-size-fits-all template.
Handoff When It Should
Built to recognize what it cannot answer and route to a human cleanly, instead of guessing or looping a frustrated user.
What we deliver
Conversation & Scope Design
Defining what the chatbot should handle, what it should escalate, and the tone that fits your product and your users.
Chatbot Development
Building the chatbot on retrieval over your own content, with the conversation flow and escalation logic your support process needs.
System Integration
Connecting the chatbot to your CRM, support desk, or product backend, so it can look up real information and take action.
Testing & Launch
Testing against real user questions before launch, then a controlled release with monitoring in place.
Process
- 01
Scope
Define what the chatbot should own, where it should escalate, and which systems it needs access to.
- 02
Build
Build the chatbot on retrieval over your content, testing against real questions as we go.
- 03
Ship
Launch with monitoring in place, then tune scope and answers against what users actually ask.
Where this fits
The same underlying build, aimed at a different job depending on who it talks to.
Customer Support
Handles common questions and routine requests from your own help content, escalating cleanly to a human for anything it cannot resolve.
Internal Knowledge Assistant
Lets your team ask questions against internal docs, wikis, and runbooks instead of searching for them.
Sales & Lead Qualification
Answers product questions and qualifies inbound leads before they reach a sales conversation.
Embedded in Your Product
Answers in-context questions inside your own app or dashboard, grounded in the user's own data and account state.
Common questions about AI chatbot development
A generic widget answers from a script or a small FAQ. This is built on retrieval over your own documentation, product data, or support history, and integrated with the systems it needs to actually help — which is what makes it useful past the first few questions.
Yes — that is most of the value. We integrate it with your knowledge base, CRM, or product backend so it can look up real information and, where appropriate, take action, rather than only talking about your product in the abstract.
It says so and hands off to a person, with the conversation history intact. Escalation logic is part of the design, not an afterthought bolted on after launch.
Yes — on your website, inside your product, or through channels like your existing support tool, depending on where the conversation needs to happen.
It overlaps. A chatbot is the conversational interface; an agent is the ability to take action. Many chatbots we build include agent-style tool calls — looking up an order, updating a ticket — and a pure agent can run with no chat interface at all. Tell us the job and we will scope the right shape for it.
Yes. You own the codebase, the content pipeline, and the configuration, documented and handed over runnable by your own team.
Explore other services
Book a call with our CEO
Denys Havryliak
Founder & CEO
- 10+ years in Software Engineering
- Master’s in Cybersecurity
- Deep, current knowledge of AI tooling
You’ll talk to the person who builds. Denys works hands-on across product, architecture, and delivery — and keeps a close watch on what today’s AI tooling can genuinely do in production, not just in a demo.