AI agent to support B2B sales
Reads sales inquiries, identifies products by SKU and EAN, checks availability and prepares a ready quote or response as draft in your salesperson's inboxThe team approves with one click, and the customer receives a response twice as fast.
This is the solution for producers and distributors, which receive dozens of repetitive inquiries daily—about offers, availability, order status, and technical details. This isn't a chatbot for a website—it's automation for the sales department and customer service office.
50 %
shorter response time to inquiries
~3 000
inquiries per month covered by Agent support
90 %
precision in automatic product selection
Your sales department prescribes the same thing every day
Requests for quotes, order statuses, questions about technical data. The same messages come back every day. Salespeople search for SKUs in the catalog, check stock levels in the ERP, calculate discounts in Excel, and enter prices—instead of closing the sale. The larger the catalog and the more customers with individual terms, the more expensive this work becomes, and the more likely it is to make a mistake in pricing or availability.
What is Agent AI for Sales Support?
Agent AI is an automation system designed specifically for your sales process. It analyzes incoming sales inquiries, retrieves data from your systems, and prepares ready-made responses: quotes, order status, and technical information. Each response is then submitted to an employee for approval.
This isn't a chatbot on a website or just another learning tool. The agent works where your team already works—for example, in your email inbox. The same mechanism will also handle other query sources: chat, WhatsApp, or a form from an external application.
I understand the query
It analyzes the message content and recognizes the intent: request for quotation, order status, complaint, technical question. It handles colloquial language – converting "white socket with a frame" into a specific index.
Reaching for data
It pulls prices, inventory, and product data from PIM, ERP, and your knowledge base. No guesswork or internet access.
He submits a ready-made draft
Prepares a shopping cart, quote, or technical response. Sends only after the employee approves the proposed response.
Cognize's AI agent never sends responses on its own. Each draft is approved by a human.
In what situations does Agent AI replace the sales department and customer service?
Modular B2B sales process automation. Implement as many areas as you need—from quotation automation, through customer service, to technical inquiries.
Automation of bidding (Sales Department)
The customer writes "request a quote" or pastes a list of EAN and SKU codes. The agent identifies the products, checks availability, and prepares a ready-made basket or quote with appropriate pricing conditions. If the item is unavailable, they suggest a substitute or ask for clarification.
What it looked like at Ostrowski Handel Internetowy:
1. The customer writes in everyday language that he needs a series of sockets in a specific color.
2. The agent extracts the features from the email (series, color, variant) and translates them into the catalog nomenclature.
3. It searches the product database multiple times and compares the results with the customer's specifications – this is why it distinguishes variants that differ in one technical detail (e.g. Berker Q.1 from Q.3).
4. Checks stock levels in real time and creates a ready-made shopping cart in the store.
5. The merchant receives a draft response in Gmail with product pages and a payment link. They add a discount and send it.
Result: 90% precision in product selection and half the response time.
Order Statuses (Logistics)
When asked "Where is my package?", the agent verifies the order number in the system, checks the status and internal comments, and then prepares a response for the customer. Without involving the team.
Initial complaint handling
The agent classifies complaints such as "damaged product" or "missing item", checks compliance with the complaint process and instructs the customer on the next steps.
Technical Inquiries (Technical Department)
The agent handles questions about installation, component matching, or service based on instructions, technical data sheets, and your knowledge base. They provide a step-by-step response without involving engineers.
Automation of B2B customer service (CSC)
Questions about technical data, dimensions or availability – without the intention of buying "here and now". The agent collects data from PIM and ERP and provides a precise product answer.
Have any questions?
Let's talk about cooperation.
Application
Who does Agent AI work best for?
An agent makes the most sense where scale and complexity make manual work a bottleneck. We'll be upfront if we're not seeing a return on investment for you.
It will work if:
- You have a wide catalog – from hundreds to tens of thousands of SKUs.
- You sell B2B with individual trading conditions for contractors.
- Requests for proposals are repetitive: they take time but do not require creativity.
- Prices and stock levels change dynamically, and the speed of response determines the margin.
- Customers describe products in their own language, not with catalog indexes.
- You have data in ERP, PIM or in the store even if it is not yet organized.
What Agent AI is not:
- This isn't a chatbot for customers on your website. The agent works on your team's end, for example, in their email inbox.
- He doesn't make commercial decisions. He prepares the response, then leaves the decision and shipping to a human.
- It doesn't work without data. If the catalog and price lists are in disarray, we start by organizing the data, and we discuss this before the quote, not after implementation.
- It's not a product out of the box. Each Agent is configured for a specific process, catalog, and systems.
Why are our Agent's responses repeatable and not random?
Language models are inherently nondeterministic, meaning they can answer the same question twice differently. This isn't a problem in marketing content. It's unacceptable in pricing and technical responses. Therefore, we've separated two layers in our system:
The technical layer works deterministically
Product lists, prices, discounts, inventory levels, and statuses are derived from queries to your systems, not from a language model. The same input data always produces the same offer.
AI is only responsible for the soft layer
The language model understands the intent of the query and formulates a message to the customer – the context, tone and manner of communication are consistent with your communication style.
The result: a repeatable, fully verified offer in a personalized message. The salesperson also receives an internal note from the agent—for example, a low-stock warning—before submitting the quote.
Security and control over what the Agent responds to
In our architecture, the language model is one element of the system, not the entire system. It doesn't have direct access to your databases and doesn't decide what data it can retrieve—it operates within a restricted scope of permissions, which we establish together with the company's IT department. This makes it resistant to data theft attempts and malicious instructions hidden in the message content.
Resistance to manipulation.
Attempts to extract internal data, system prompts, or API tokens do not have access to the layer where this data resides.
Controlled data scope.
The agent only collects information to which we knowingly grant it access. Sensitive data remains beyond its reach.
No Vendor Lock.
The architecture allows you to swap language models (OpenAI, Gemini, and others) without redesigning the system. This eliminates your company's dependence on a single AI vendor.
Narrowed thematic scope.
The agent will not engage in conversation outside of a business context and will automatically reject content that does not comply with the rules.
And above all: The agent never sends a response itself. Every decision is approved by a human.
Why Cognize eCommerce B2B agency?
We specialize in digitizing B2B sales for medium-sized and large companies – manufacturers and distributors. Our offering is distinguished by three substantive pillars:
A consultant who cares about the quality of your project
Each project is led by an experienced consultant – a former e-commerce manager from the B2B industry. This ensures that the implementation is led by someone who understands the day-to-day operations, challenges, and needs of your company.
“Flexible Accelerators” that reduce implementation costs and time
When implementing systems, we use ready-made "accelerators." These are systems and modules we've developed ourselves, based on open technologies. They reduce costs and shorten implementation time while remaining fully configurable to your unique needs.
Narrow specialization = we have already completed a project similar to your needs
Over 100 completed projects have allowed us to understand the specifics of companies operating in the B2B (often combined with B2C) sector. As a result, we have reference implementations and customer reviews for 92% of our inquiries.
Implementation without changing team habits: Agent AI facilitates work in already available tools
The AI agent doesn't require learning another tool. It integrates with what the team already uses—for example, email. If queries also come in from chat, WhatsApp, or a form in your app, we connect them to the same process.
Natural work environment
Salespeople and customer service representatives don't have to leave their email.
Ready-made answer suggestions
For each inquiry, the Agent prepares a draft version of the response message along with an internal note.
Full control and editing
The draft appears where the employee would normally type a response. It can be edited, personalized, or approved with a single click.
Zero resistance to new technology
The team isn't learning a new system. They're verifying the work the Agent has performed.
Have any questions?
Let's talk about cooperation.
AI Agent Operation
How does the AI Agent work in practice?
Several process elements that we configure for your product catalog and systems.
Main machine
Incoming messages are analyzed and categorized as requests for quotes, status inquiries, technical queries, or complaints. This process directs the message to the appropriate support path.
A product dictionary built from your queries
Customers use different names for the same products. The agent detects these terms and learns from dictionaries we build based on your real-world queries.
Order status inquiry
Based on the message, the system checks the status and internal comments for the order, and then prepares a response for the customer.
How do we implement AI Agent, step by step?
01
Workshop and analysis
We map the inquiry process, message sources, use cases, and proposal creation concept. You'll leave the workshop with a process diagram—even if you decide not to collaborate.
02
Analytical work and product data
We work with your IT department to determine the method of data exchange, assess the quality of the catalog, and prepare a product database in an agent-friendly format.
03
Configuration and implementation
We build process logic, configure API queries and message templates, and connect the product database. We select tools and environments for specific tasks – n8n is one of the frameworks we use, but not the only one.
04
Maintenance and supervision
We monitor performance, fine-tune responses based on team feedback, and provide technical support.
Have any questions?
Let's talk about cooperation.
Inquiries
How does the request for quotation work?
We take responsibility for our clients' businesses.
Our approach and effective actions build partnerships that we mutually appreciate.
01
Contact and talk about the project
Contact us and explain your needs. We'll gather all your requirements and discuss your project together (in person or via video call).
02
Specification and planning
We'll work with you to develop project specifications during a workshop at your company. At the end of the meeting, we'll create documentation, a feature list, and a full project plan.
03
Offer and implementation
We will respond to your specifications and present our offer. We will begin the project with a kick-off meeting, during which we will introduce the experts from our dedicated team and present the work schedule.
Scoping process
and project budget (free of charge)
The result of the recognition process is:
01.
Knowledge of Cognize's experience in similar projects
02.
Knowledge of customer needs
03.
Knowledge of the project implementation process
04.
Preliminary project estimate
Pre-implementation analysis process
(about 4 weeks)
The result of the Pre-Implementation Analysis Process is a planned project – Pre-Implementation Analysis*,
which includes:
01.
Technical Specifications (text document)
02.
List of functionalities
03.
Project budget and schedule
*The prepared Pre-Implementation Analysis is the property of the Client and may be used to perform market research and collect offers.
What else can we do for your company?
Cognize B2B eCommerce Agency - What do we do?
We offer services aimed at increasing revenue, optimizing processes and improving profitability.
Investment
Implementation and maintenance
integrations
Technology
B2B consulting
Not sure what system you need yet?
Before you decide on a specific technology, it's worth exploring which solution truly fits your sales model. Our experienced B2B eCommerce Manager consultants help companies choose the right direction—without predetermined answers. If you feel it's a good time for a consultation, learn what such a collaboration looks like.
Experience
Experience in your industry
The electrical, heating, lighting, cosmetics, medical, motorcycle, automotive, FMCG, clothing, and sports industries are just some of the industries we have implemented. Ask about our experience in your industry.
What do our clients say about us?
Punctuality, flexibility, availability, professionalism (...)
In 2017, we began working with Cognize (KMK Group) on the BAST system. Since then, the project has been developed and managed with exemplary skill. Cognize's (KMK Group) work is characterized by timeliness, flexibility, availability, professionalism, and, most importantly, the ability to present complex programming solutions in an accessible format.
This cooperation has resulted in our development and stability.
This cooperation has resulted in our development and stability, and the form of business contacts based on mutual trust is increasingly rare today, yet extremely effective.
(…) we can now easily and effectively manage our product catalog (…)
Cognize provided us with two services: Digital Sales Transformation Consulting and PIM Implementation. They provided the necessary know-how and demonstrated methods for various business process integrations with PIM systems. Thanks to their expertise, we can now easily and effectively manage our product catalog while minimizing implementation costs.
They helped us understand our needs and proposed the best solution based on the analysis results.
Our collaboration with Cognize began with a consultation. At this stage, they helped us understand our needs and proposed the best solution based on the analysis results. Cognize then began implementing the final system. The project was conducted with a high level of communication, on time, and, most importantly, with the Cognize team's ongoing initiative.
Immediately after opening the new store, we saw an immediate increase in sales.
After launching the new online store, sales immediately increased. The Cognize team (formerly KMK Group) was able to manage the project independently, working with minimal involvement from the snowboard brand. Their independence and communication skills were also impressive.
(...) we recorded a dynamic increase in our company's turnover
(...) The e-commerce platform they created not only meets all our expectations but also provides enormous opportunities for future technological development. Thanks to the solid technical architecture and innovative features, we have seen dynamic growth in our company's turnover, which we attribute directly to the functionality of the new website. Excellent communication and high availability of the team ensured we could count on support at every stage of the project. (...)
Case study
Effect on the customer: Ostrowski Online Trade
A distributor in the electrical and lighting industry (OtoLampy.pl, LuxMarket.pl, DobreGniazdka.pl). The customer service office was dealing with approximately 3,000 messages per month. After implementing an AI agent to handle requests for quotes:
50 % shorter time to prepare a response to a request for quotation
~3 000 inquiries per month covered by Agent support
90 % precision of automatic product selection
FAQ
Frequently asked questions about AI Agent for B2B sales support
Does Agent AI only support email?
We most often implement it in email, as that's where most B2B inquiries go. However, the same process can also handle other sources – chat, WhatsApp, or an external application querying the Agent via webhook.
What if AI doesn't find the product?
The system is programmed so that if there is no clear match for the product (e.g. incorrect EAN code), it will ask the customer for details or request data verification, instead of creating a false offer.
What technologies does Cognize AI Agent work with?
We use the n8n platform for process design, OpenAI models for natural language analysis (LLM), and vector databases for fast product catalog searches.
Will we have access to the tool configuration?
Yes. We believe in a partnership model, so we don't lock the system away from users. Full configuration and oversight of the AI Agent's operation is available to your team. Furthermore, comprehensive training is a regular part of every implementation process.
Our goal is to educate your employees so that over time they can fully independently manage the settings, knowledge base, and response scenarios, adapting them to the current needs of the company.
How is Agent AI different from a chatbot?
A chatbot is a chat window on your website, primarily for B2C traffic. Cognize's AI agent works on your team's end—for example, in the email inboxes of your sales department and customer service. It integrates with PIM and ERP systems and prepares ready-made offer drafts.
Can an AI agent make a mistake in pricing or offering?
Prices, discounts, and inventory levels come from queries to your systems, not from the language model—the same input data always produces the same offer. The model is responsible only for the message content. Furthermore, the agent doesn't send anything independently: the draft is approved by the salesperson.
What systems does it integrate with?
With email, ERP (e.g., Comarch Optima and XL, Streamsoft, SAP), and PIM (Akeneo, Ergonode). During the workshop, we discuss directly whether integration with your system is possible and what it requires.
What if our product data is not organized?
This is a typical situation. We can build a product database for an agent from what you have—PIM, store database, or product pages. We quote the scope of this work separately and discuss it before the project begins.
How long does implementation take?
We begin with a free workshop and scope assessment. The time depends on the number of areas being implemented, the state of product data, and the number of integrations. Modularity allows us to start with a single area—usually just the offer itself.
Do you have an idea, a ready specification or a business need?
Write to us. We will contact you within 24 hours.
