A chatbot is a conversational interface that answers questions and handles requests. It works with customers on a website or with employees in Teams. A copilot works inside the tools people already use and helps them do their jobs. It finds information, drafts content, and takes actions in business systems. Our AI chatbot development services and AI copilot development services can start with either one.
AI chatbot & copilot development services
We build AI chatbots that handle real customer conversations and enterprise copilots that help your teams work faster. Both run on Azure OpenAI and Semantic Kernel, and both answer from your real business data through RAG.
Microsoft Partner / ISO 27001 / Azure OpenAI / Copilot Studio
Copilot & AI chatbot development
A regular chatbot carries the conversations with your customers or employees and answers their questions. A copilot works alongside your team inside the tools they already use, finding information and taking action on their behalf.
As an AI chatbot development company, we build both. We connect them to the CRM, ERP, and document systems where you store your business data. Our AI chatbot development services start with your users’ current communication and the data needed to answer them correctly.
Why so many AI chatbots and copilots disappoint in production
-
The chatbot can’t answer specific questions
A general-purpose language model without access to your documentation doesn’t know your products, policies, processes, nuances, and specifics. It answers quickly, but makes mistakes. Or gives vague responses that are of no use. If your system acts like that, it can hurt customer trust. That kind of chatbot is a very poor business choice.
-
No proper handoff to a human
When a question is too complex, the chatbot either keeps going in circles or sends the customer to a generic contact form. When the chatbot hands over the conversation to a human agent, it often loses the context. The conversation starts over from a blank page, and no customer with a problem wants that.
-
Copilot doesn’t get properly connected
Even when deployed, the copilot can’t access the company data or systems your employees use. It can write an email, but it can not check a customer’s latest contract or pull up an order. Without access to the right information, it becomes another general-purpose tool people didn’t need.
-
There are security gaps
This means a chatbot can access more company data than it should, with no clear access rules or proper records of what it does. There may also be no controls over the data storage. When this happens, IT and legal teams stop the launch until these issues are fixed, which can mean going far back and redesigning the system.
Our AI chatbot & copilot development services
Customer support chatbot
A support chatbot that answers around the clock, based on your documentation and knowledge base through RAG. It resolves routine questions on its own and passes complex ones to your agents with the full conversation attached.
This is the most common starting point for our custom AI chatbot development services.
E-commerce and transactional chatbot
A chatbot that tracks orders, recommends products, and helps customers through checkout and payment. It connects to your backend, so it works with live stock, prices, and order statuses.
We build these as part of our AI chatbot app development services for web and mobile.
Enterprise internal chatbot
Enterprise AI chatbot development services like this take routine questions off your HR and IT teams. These internal assistants handle HR questions, IT support, and company knowledge, and are available in Microsoft Teams.
Role-based access makes sure each employee sees only the information they are allowed to see.
Enterprise knowledge copilot
A copilot that finds, summarizes, and explains information from company documents and SharePoint through RAG. It shows the sources behind each answer, so people can verify the answers and get context.
Many companies begin their custom AI copilot development services here, because research is part of almost every team’s day.
Workflow automation copilot
A copilot that carries out actions in your .NET, CRM, and ERP systems when a user asks in plain language, such as creating a ticket or updating a deal. Before it makes any important changes, it shows the user what it is about to do and asks for confirmation.
As an AI copilot development company, we treat these confirmation steps as a required part of the design.
Microsoft Copilot Studio extensions
Custom agents, plugins, and connectors that extend Microsoft 365 Copilot and Teams with your company’s data and systems.
Our copilot development services cover both low-code work in Copilot Studio and custom code for cases where Copilot Studio reaches its limits.
Why choose Blackthorn Vision as your AI chatbot development company
-
Answers grounded in your data
Your chatbot shouldn’t guess. We make sure it answers from your company’s information. We use Azure AI Search and RAG to connect the assistant to your documents and business records. If the answer isn’t in the available data, it says so instead of making the answer up, and directs the user to a person or another source.
-
Built into the Microsoft stack
We work with Azure OpenAI, Semantic Kernel, Copilot Studio, Microsoft 365, Teams, Dynamics 365, and SharePoint. This means the assistant fits into the tools most teams use. It doesn’t become another standalone system to learn and maintain. As a Microsoft Partner, we build around Microsoft’s supported technologies and patterns.
-
Connected to your .NET systems
A useful enterprise chatbot needs access to the systems where you store your business data. Our chatbots and copilots can connect to your CRM, ERP, and .NET backends, so they can do way more than answer general questions. Depending on the permissions you give them, they can check an order, retrieve a contract, make summaries, or update a record.
-
Ready for real users
We build stable chatbots that hold up when hundreds or thousands of people start using them. We build in human handoff and keep the conversation history when an issue needs a human agent. We also use role-based access, audit logs, and cost controls to keep the system manageable in production. We also test how it handles difficult questions and failures.
Technologies we use for AI chatbot & copilot development
All technologiesThe stack depends on where the assistant is located and which systems it needs to reach. Our AI chatbot app development services use Copilot Studio when low-code speed fits the task, and the Microsoft 365 Agents SDK or custom code when you need full control. Channels have their own category because one assistant often serves several of them from the same backend, and that is how we shape AI copilot development solutions around your environment.
Meet the AI chatbot & copilot development team at Blackthorn Vision
“A chatbot without RAG is an expensive FAQ page. A copilot without integration is a mock-up. Our goal is to build assistants that people would use. Ones that solve problems, free up time, bring new customers, and help to build trust.”
Mykhailo Terentiak, Founder & CEO
How Blackthorn Vision builds your AI chatbot or copilot
-
01
AI chatbot development service
Our usual AI chatbot development service follows the same path, and so does every AI copilot development service. Each step ends with the deliverable you can review and analyze before we move on.
The process is the same across all our AI chatbot development services, from a simple FAQ bot to an assistant that works inside your ERP.
-
02
Use case and conversation design
We start by analyzing the conversations your users will have. We map the main scenarios, what users are trying to achieve, the fallback responses, the points where a human should take over, and the channels the assistant will use. You receive a clear conversation design document with flow diagrams.
-
03
Knowledge architecture and RAG setup
We list the data sources the assistant will draw on and decide how to split documents into chunks and retrieve them. We also look for knowledge gaps. These are topics users ask about that aren’t yet covered in your documentation. You get a knowledge architecture document that shows where each answer will come from.
-
04
Bot development and integration
We build the LLM and RAG pipeline, the .NET connectors to your systems, and the channel integrations, plus a user interface if you need one. The assistant runs in a staging environment where your team can try it. At the end of this step, you have a working chatbot or copilot in staging.
-
05
Conversation testing and safety review
We test edge cases, unclear questions, and prompt injection attempts, where users try to make the assistant say or do something it shouldn’t. We check answers for made-up content, validate role-based access, confirm that audit logs record the right events, and hand you over a safety review report.
-
06
Production deployment and analytics
We roll out one chunk at a time and set up conversation analytics to track which questions the assistant handles well and where it struggles. That data feeds a regular improvement cycle for content and prompts. You get a live assistant and an analytics dashboard.
FAQ
-
What is the difference between an AI chatbot and an AI copilot?
-
How do you handle sensitive data and compliance in chatbot deployments?
As an AI chatbot development company, we treat compliance as part of the design. We limit each assistant to the data it needs and apply role-based access from the source systems. Azure OpenAI runs in the Azure region your policies require, and we log conversations for audit, masking sensitive fields where needed.
Each enterprise AI chatbot development service we deliver follows our ISO 27001-certified information security management system, and your IT and legal teams review the design before launch.
-
How long does it take to build and deploy an AI chatbot or copilot?
It depends on the number of use cases, data sources, and systems the assistant has to work with.
A chatbot grounded in a well-organized knowledge base is faster to build than a copilot that takes actions in several business systems. We provide a timeline after the use case and conversation design step, once the scope is clear. As an AI copilot development company, we also plan the rollout so that one team can start using the assistant while the rest of the scope is still in progress.
-
Can you build a copilot that integrates with Microsoft Teams and our .NET systems?
Yes. We build copilots that run in Microsoft Teams and connect to your .NET systems through APIs and Azure Functions.
Depending on your needs, we use Copilot Studio for faster low-code delivery or the Microsoft 365 Agents SDK for full control over the logic. The copilot uses the user’s permissions through Microsoft Entra ID, so it can access only permitted data. This kind of integration is one of the most common requests in our custom AI copilot development services, and a main reason clients look for an enterprise AI chatbot development company.
-
Which channels can the chatbot be deployed on?
We deploy on Microsoft Teams, website chat widgets, WhatsApp, Slack, Telegram, and through a REST API for your own web and mobile applications. One assistant can serve several channels from the same backend, so answers stay consistent across all of them.
Enterprise AI chatbot development service for websites usually starts with a web chat widget and adds other channels once the core assistant works well. Our AI chatbot development solutions are built so that we can add new channels without rebuilding the assistant.
-
How do you prevent the chatbot from giving wrong or hallucinated answers?
We ground answers in your own data through RAG, so the assistant responds from retrieved documents and records. It can show the sources behind an answer, and when it can’t find one, it says so and offers a next step.
Before launch, we test it against a set of real questions with known correct answers and review every failure. After launch, conversation analytics show where answers were weak, so we can fix the underlying content. This testing is a part of all our AI chatbot development services.
