# AI Agent Development Source: https://ordergroup.co/ai-software-development/ai-agent-development/ Last updated: 2026-10-22 > AI agent development services: chatbots and agents that work on your product's data, with rules enforced on the server, human checks and a free consultation. # AI agent development services: chatbots and agents inside your product You want an AI chat or an agent that answers from your catalogue and data and does only what a person approved. We build chats and agents with the rules enforced in code and on the server. We do this for a product platform in the renovation market and use the same approach on our own MCP server. [Book a free consultation](https://ordergroup.co/contact-us/) Tell us what the AI should do in your product. A short description of your data and your users helps us prepare the free consultation. - ![AASA24](https://ordergroup.co/media/images/aasa24-mono.max-208x64.format-webp.webp) - [![AP-Tech](https://ordergroup.co/media/images/ap-tech-mono_ihuJP5T_6b2rSSb.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/monster-airport-lighting-system/) - ![Avafin](https://ordergroup.co/media/images/avafin-mono.max-208x64.format-webp.webp) - [![BizBot](https://ordergroup.co/media/images/bizbot-mono_StdJIUN.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/bizbot-fintech-ux-design/) - [![Enerace](https://ordergroup.co/media/images/enerace-mono_FKuME1X_Fp3WF4B.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/enerace-energy-trading-software/) - ![Filmgrail](https://ordergroup.co/media/images/filmgrail-mono_gPdfbHO.max-208x64.format-webp.webp) - [![Kyoto Group](https://ordergroup.co/media/images/kyoto-group-mono_hlqECHG.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/kyoto-digital-twin-software/) ## AI agent development services for products with real data and real rules Our AI agent development services put a chat or an agent inside a product that already has data and users: a catalogue, a B2B platform or an internal system. The AI answers from your data, and the rules sit in code and on the server. This work is part of our [AI software development](https://ordergroup.co/ai-software-development/). A project covers: - a chat or an agent working on your product's data - a separate AI service that your application calls - tools the agent can use, each with a description and a schema - rules enforced on the server - tests that try to push the model off its task - support after launch For a product platform in the renovation and interior fittings market we run an AI chat in the application and a product-search agent, and the work is ongoing. On our own CMS, AI agents create pages, briefs and SEO changes through a production MCP server that has run since 9 July 2026. The server side has its own page, [MCP server development](https://ordergroup.co/ai-software-development/mcp-server-development/), and putting AI into an existing product is covered in [AI integration services](https://ordergroup.co/ai-software-development/ai-integration-services/). This work is for product owners and CTOs of companies whose product holds real data. They want an AI chat or an agent that works on that data and stays inside the rules they set. Software projects **160+** delivered since 2013 Industries **15+** where we have built software App users **40,000+** people using apps we built, across all our projects Clutch rating **5.0/5 on Clutch** average rating of our client reviews on Clutch Clutch reviews **18 verified reviews** verified client reviews ![AI content generation writing (Unsplash)](https://ordergroup.co/media/images/photo-1499750310107-5fef28a66643.format-webp.width-2880.webp) ## AI chatbot development: a chat that knows your catalogue Building an AI chatbot begins with what the chat should know. On the renovation platform the chat answers the user, and the product-search agent next to it searches the texts and metadata of many products at once, across the offers of many suppliers. When a user asks about a price, the agent fetches the price information, and the chat's answer contains the product's source URL and the price from the platform. The message passed to the AI carries the customer's context: name and phone number. The conversation can then move on to customer service. We reviewed the chat's performance on real conversations, in successive rounds. ## How the product-search agent works In the product-search agent, Python code builds the search query and the model handles the conversation. When a search finds nothing, the agent repeats it with changed parameters. The chat and the agent run in a separate AI service. The main application calls it through its own service on the backend. The AI part can therefore be measured, changed or switched off without touching the rest of the product. A flag set at project level in the application, ai_enabled, controls whether the AI is on. We describe this architecture in [AI integration services](https://ordergroup.co/ai-software-development/ai-integration-services/). ![emile-perron-xrVDYZRGdw4-unsplash](https://ordergroup.co/media/images/emile-perron-xrVDYZRGdw4-unsplas.format-webp.width-2880.webp) ## Agents that act in your system: rules on the server, not in the prompt For an agent that creates and saves things in your system, we put the rules on the server. On our own MCP server the rules an agent must not break are response codes: 1. Creating a page without a brief returns HTTP 400. The brief is the description of a page, tied to a goal. A person approves it before an agent writes content. 2. Writing content before a person approves the brief returns HTTP 409. 3. Publishing with audit errors returns HTTP 409. The errors include facts outside the approved list, client names covered by an NDA and no verdict from an independent critic agent. No tool on the server has a parameter that skips these gates. Every request from an agent carries the token of one person or integration and lands in a call log in the admin panel. On 20 October 2026 the server had 164 tools. Agents reach it through the open [Model Context Protocol](https://ordergroup.co/glossary/model-context-protocol/). According to Anthropic's announcement of 9 December 2025, ChatGPT, Cursor, Gemini, Microsoft Copilot and Visual Studio Code support it. Anthropic created the standard, and its assistant Claude works with it too. We also run a public endpoint, https://ordergroup.co/mcp. It needs no token, only reads our case studies and sends a project enquiry, and it is listed in the official MCP registry as co.ordergroup/public. How the server works in practice is in our article [MCP vs API: what we learned running an MCP server in production](https://ordergroup.co/blog/mcp-vs-api/). ## A person approves what matters Where a wrong output costs something, we keep a person in the loop. On the [Centrum Komunikacji](https://ordergroup.co/case-studies/centrum-komunikacji-sign-language-interpreting-platform/) platform, speech recognition writes a draft of the text live, a transcription specialist corrects it, and only the corrected text reaches the user, as a chat message. The feature runs in production. Encrypted fields, the option to delete a user's data and an event log are among the measures that protect personal data. Our own agents follow the same pattern: a person approves the brief before an agent writes any content. We test a chat and an agent like the rest of the application. On the PSONI project the AI simplifies official letters. QA runs jailbreak tests that try to pull the model off its task, for example with a request for an apple pie recipe, and repeats them with every new iteration. Have a product with data that an AI chat or agent should work on? Start with a free consultation. [Book a free consultation](https://ordergroup.co/contact-us/) ## Chatbot or agent: what to build What a chatbot and an agent do, what they work with and how we check them. | Aspect | AI chatbot | AI agent | |---|---|---| | What it does | Answers in a conversation, based on your product's data | Acts in the system: searches, creates, saves | | What it works with | Your product's data, such as a catalogue | Tools, each with a description and a schema; the server decides what is allowed | | Where we run it | The AI chat on the renovation platform | The product-search agent there, and the agents on our own CMS | | How we check it | Review on real conversations, in successive rounds | Server gates, and a person who approves the brief | ## Why work with us on AI agent development When you choose an AI agent development company, look at what you can check. - The AI can be switched off. The chat and the agent run in a separate AI service, and a project-level flag decides whether the AI is on. - The rules sit on the server. On our MCP server, HTTP 400 and 409 responses enforce them, and every request carries a token and lands in a call log. - Jailbreak tests run with every new iteration. - The code is yours. Copyright passes to you with each payment, within the scope of use set in the contract. - Support continues after launch, because models, prompts and the data they work on keep changing. See [support and maintenance](https://ordergroup.co/services/platform-cloud-engineering/support-maintenance/). A project starts with a free consultation or a free [discovery workshop](https://ordergroup.co/services/consulting-discovery/product-workshops/), where we use our own AI toolkit. We reply to a message sent through the form within 48 hours on working days. Do you have questions? ## AI agent development services - frequently asked questions ![Łukasz Gajownik](https://ordergroup.co/media/images/T02DHCC1Z-UT420UBA7-d74022d27c3c-512.format-webp.webp) Łukasz Gajownik Head of AI & Frontend [Book a free consultation](https://ordergroup.co/contact-us/) ### What do AI agent development services include? A chat or an agent working on your product's data, a separate AI service that your application calls, tools the agent can use, rules enforced on the server, tests that try to push the model off its task, and support after launch. A project starts with a free consultation. ### What is the difference between an AI chatbot and an AI agent? A chatbot answers in a conversation, based on your product's data. An agent acts in your system through tools, each with a description and a schema: it searches, creates and saves. The server decides what the agent is allowed to do. ### Who builds AI agents and chatbots for companies? We do, for products with real data. For a product platform in the renovation and interior fittings market we run an AI chat and a product-search agent. On our own CMS, AI agents work through a production MCP server that has run since 9 July 2026 and had 164 tools on 20 October 2026. ### How do we choose an AI chatbot development company? Look at what you can check: rules enforced by the server instead of the prompt, a token for every request and a call log, jailbreak tests, and who owns the code. With us, copyright to the code passes to you with each payment, within the scope of use set in the contract. ### How do you stop an AI agent from doing something it should not? With gates on the server. On our MCP server, creating a page without a brief returns HTTP 400, and writing content before a person approves the brief, or publishing with audit errors, returns HTTP 409. No tool has a parameter that skips them. Each request carries a token and lands in a call log. ### Can an AI chatbot search our product catalogue? Yes. On a product platform from the renovation market, a product-search agent searches the texts and metadata of many products and the offers of many suppliers, and the chat answers from the results. Python code builds the search query, and an answer about price includes the product's source URL and the price from the platform. ### How does an AI product-search agent work? The model handles the conversation, and Python code builds the search query. When a search finds nothing, the agent repeats it with changed parameters. The answer carries the product's source URL and the price from the platform, and the customer's context goes along, so the conversation can move on to customer service. ### What does the chat pass on when a conversation moves to customer service? The message passed to the AI carries the customer's context: name and phone number. With that context the conversation can move on to customer service. We reviewed the chat's performance on real conversations, in successive rounds. ### Can we switch the AI off without breaking the product? Yes. On the renovation platform the chat and the agent run in a separate AI service that the application's backend calls through its own service, and a project-level flag, ai_enabled, controls whether the AI is on. The AI part can be measured, changed or switched off without touching the rest of the product. ### Which AI assistants can work with an MCP server like yours? Clients that support the Model Context Protocol. According to Anthropic's announcement of 9 December 2025, that includes ChatGPT, Cursor, Gemini, Microsoft Copilot and Visual Studio Code, and Claude works with it too. We describe the server side in [MCP server development](https://ordergroup.co/ai-software-development/mcp-server-development/). ### Is there a public MCP endpoint we can look at? Yes. https://ordergroup.co/mcp needs no token. It only reads our case studies and sends a project enquiry, and it is listed in the official MCP registry as co.ordergroup/public. Agents reach it through the open Model Context Protocol. ### Does a person stay in the loop? Yes, where it matters. At Centrum Komunikacji speech recognition writes a draft and a transcription specialist corrects it before the user sees it. In our own content process, a person approves the brief before an agent writes any content. ### How do you test an AI chatbot or agent? Like the rest of the application. We reviewed the chat on real conversations, in successive rounds. On the PSONI project QA runs jailbreak tests that try to pull the model off its task, for example with a request for an apple pie recipe, and repeats them with every new iteration. ### Do you support the AI after launch? Yes. We stay on for support and maintenance, because models, prompts and the data they work on keep changing. A project starts with a free consultation or a free discovery workshop, and we reply to a message sent through the form within 48 hours on working days. ### How do we start? With a free consultation or a free discovery workshop. We reply to a message sent through the form within 48 hours on working days. Copyright to the code passes to you with each payment, within the scope of use set in the contract, and after launch we stay on for support and maintenance. ![Developer with headphones coding at desktop monitor in an open office](https://ordergroup.co/media/images/Image_1_3kejLC8_Y69T2Sz.format-webp.width-2880.webp) ## AI chat and agents that work on your product's data. Your message goes to ![Filip Szamborski](https://ordergroup.co/media/images/Filip_dTWHyBo.2e16d0ba.fill-432x432.format-webp.webp) Filip Szamborski Co-founder & CEO [](https://www.linkedin.com/in/filip-szamborski/) SO FAR WE HAVE WORKED WITH BRANDS LIKE: - [![RAW Cyber](https://ordergroup.co/media/images/raw-cyber-mono_M2DWvZf_pHEQtjP.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/raw-cyber-custom-android-os/) - [![Skyfri](https://ordergroup.co/media/images/skyfri-mono_KGicBgp.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/skyfri-solar-asset-management-platform/) - ![Spacestor](https://ordergroup.co/media/images/spacestor-mono_woFaKhf.max-208x64.format-webp.webp) - [![Zeronest](https://ordergroup.co/media/images/zeronest-mono_BqSPQJQ_2nGxsSc.max-208x64.format-webp.webp)](https://ordergroup.co/case-studies/zeronest-solar-panel-monitoring-app/) - ![AASA24](https://ordergroup.co/media/images/aasa24-mono.max-208x64.format-webp.webp) Thank you for your message. We read every message ourselves and get back to you within 48 hrs on business days. Something urgent? [hello@ordergroup.co](mailto:hello@ordergroup.co)