What Are Enterprise AI Agents?
Enterprise AI agents are AI-powered systems that automate business processes, analyse data, and make recommendations using information from across your organisation. Unlike standalone AI tools, they work with your existing business systems to solve real operational challenges.
Our Expertise
Our Enterprise AI Agent Solutions
Inventory Agent
Overstock ties up cash. Stockouts cost the order. Most teams are guessing at the line between them. The Inventory Agent reads sales trends, demand patterns, supplier lead times, and purchasing history, and tells you where that line actually sits.
- Demand forecasts that account for seasonality and real supplier lead times
- Stockout and overstock risk flagged 3 to 6 weeks out, before you're air-freighting to save an order
- Reorder quantities recommended before anyone has to ask
- Slow-moving stock surfaced while it's still worth discounting
Product Enrichment Agent
Thousands of SKUs, inconsistent attributes, and a team retyping specs out of supplier PDFs. The Product Enrichment Agent pulls from manufacturer sites, supplier portals, PDF catalogs, and spec sheets to build listings that are complete, consistent, and actually filterable.
- Pulls specs out of the supplier PDFs your team is currently retyping by hand
- Fewer abandoned carts from missing sizes, specs, or images
- SKUs enriched automatically as new supplier data arrives
- Descriptions written to one voice across the whole catalog
- Categories and attributes standardized so search and faceted filtering work
- Flags the SKUs that are still incomplete, ranked by revenue impact
Margin Erosion Agent
Margins erode quietly: cost creep, discount drift, one rep's standing exception, until the quarter closes and someone asks what happened. The Margin Erosion Agent watches costs, pricing, and supplier changes as they move.
- Declining margins flagged by product and by account, so you see which customers quietly dropped four points last quarter
- Supplier cost increases caught in the week they land, not the month they hurt
- Pricing anomalies and discount leakage surfaced before they compound across a catalog
AI Visibility Agent
Buyers now research suppliers through AI assistants before they ever reach your site. If your catalog and content aren't built for that, you lose them before the first click. The AI Visibility Agent tracks how your business appears across ChatGPT, Claude, Gemini, and Perplexity.
- See where your brand and products get mentioned, and where they don't
- Compare your visibility against named competitors
- Catch missing or inaccurate information before it costs a deal
- Get specific fixes, not just a diagnosis
AI Campaign Agent
Most campaign calendars are built on gut instinct and last year's calendar. The AI Campaign Agent uses inventory position, sales performance, customer behavior, and seasonal trends to recommend the campaigns worth running.
- Products to promote, chosen by what the data supports and what you can actually ship
- Customer segments most likely to convert, pulled from real purchase history
- Campaign concepts and content generated from that analysis
- Performance measured against forecast, with adjustments recommended as results come in
How Each Agent Drives Growth
Agent
Solves
Reads from
Output
Go-live
Product Enrichment
Incomplete SKU data
PIM, supplier PDFs, manufacturer sites
Enriched listings
4–5 wks
Inventory
Stockouts and dead stock
ERP, WMS, purchase history
Reorder recommendations
5–6 wks
Margin Erosion
Silent profit leaks
ERP, pricing tables, cost files
Margin alerts by SKU/account
4–6 wks
AI Campaign
Slow, guess-based promos
Ecommerce, CRM, inventory
Campaign plans + content
4 wks
AI Visibility
Invisibility in AI search
Public web, competitor data
Content gap actions
3–4 wks
What Makes Enterprise AI Agents for B2B Commerce Different
Klizer’s custom AI agent runs on the same connected orchestration layer, giving it access to the same business data across your ERP, ecommerce platform, CRM, PIM, and WMS. That means every recommendation is based on the same source of truth, not disconnected systems.
Connected by Design
Every AI agent runs on the same orchestration layer, sharing data across your ERP, ecommerce platform, CRM, PIM, and WMS, so every recommendation comes from one source of truth.
Built for B2B Commerce
Built for manufacturers and distributors: complex catalogues, ERP dependencies, customer-specific pricing, multi-channel operations.
Transparent and Explainable
Every recommendation can be traced back to the data and logic behind it, giving your team the confidence to understand, validate, and act on every decision.
Powered by Proven AI Accelerators
We start with proven AI accelerators and tailor them to your products, business rules, and operational workflows, reducing implementation time.
Your Data, Your
Infrastructure
Deploy using self-hosted, open-source LLMs or your preferred model provider. Your data stays under your control, not locked into a proprietary platform.
How We Build and Deploy Enterprise AI Agents
Start with Proven AI Accelerators (Week 1)
We begin with AI accelerators built for commerce use cases like inventory planning, product enrichment, and margin analysis. This reduces development time while providing a strong foundation.
Deploy with the Right Level of Control (Weeks 5–6)
Depending on the use case, agents can automate tasks or provide recommendations for human approval, giving your team complete control over critical decisions.
Train on Your Business Data (Weeks 2–3)
Each agent is trained using your product catalogue, transaction history, pricing rules, supplier data, and operational workflows, ensuring recommendations reflect how your business operates.
Continuously Improve
After go-live, each agent is reviewed monthly against real outcomes. Recommendations that miss are traced back to the data or rule that caused it, and the model is retrained accordingly.
Validate Before Go-Live (Week 4)
Before deployment, every agent is tested against your historical data and real business scenarios to verify its recommendations and minimise risk.
Start with Proven AI Accelerators (Week 1)
We begin with AI accelerators built for commerce use cases like inventory planning, product enrichment, and margin analysis. This reduces development time while providing a strong foundation.
Train on Your Business Data (Weeks 2–3)
Each agent is trained using your product catalogue, transaction history, pricing rules, supplier data, and operational workflows, ensuring recommendations reflect how your business operates.
Validate Before Go-Live (Week 4)
Before deployment, every agent is tested against your historical data and real business scenarios to verify its recommendations and minimise risk.
Deploy with the Right Level of Control (Weeks 5–6)
Depending on the use case, agents can automate tasks or provide recommendations for human approval, giving your team complete control over critical decisions.
Continuously Improve
After go-live, each agent is reviewed monthly against real outcomes. Recommendations that miss are traced back to the data or rule that caused it, and the model is retrained accordingly.
Systems We Integrate With
Our agents connect to the systems you already run. If it has an API or a database we can read, we can work with it.
ERP
Epicor Prophet 21, Epicor Kinetic, NetSuite, Infor, Acumatica, Microsoft Dynamics 365
PIM
Akeneo, Salsify, inRiver, Pimcore
Ecommerce
Adobe Commerce, BigCommerce, Shopify Plus, Shopware
CRM
Salesforce, HubSpot, Microsoft Dynamics
Discover the journeys we have impacted
We've worked with manufacturing and distribution businesses across the globe, helping them solve real challenges and grow with confidence. Browse through our client success stories to see the difference we've made.
Client Experiences, in Their Words
We have been a partner for Klizer for five years now, and the experience has been terrific. They have been an excellent partner to help us grow and sustain our business.
Ryan Van Hoozer
VP of Operations,
Marysville Marine Distributors
Klizer’s communication skills were above and beyond what I have
experienced with vendors. The relationship was such a great fit that we brought on Klizer employees in-house to work with us directly.
Dan Schuessler
Digital Project Manager,
Riddell
Klizer delivered a high-functioning website that perfectly coordinates with our company branding while enhancing our ecommerce capabilities for our customers
Jennifer Krach
Vice President Sales, Marketing, &
Customer Service, C-Line
Insights from Our Experts
Frequently Asked Questions
What are enterprise AI agents?
Enterprise AI agents are AI-powered systems that automate tasks, analyse business data, and make recommendations across your existing technology stack. Unlike standalone AI tools, they connect with systems like your ERP, ecommerce platform, CRM, PIM, and WMS to support business operations.
Do we need all five AI agents?
No. You can start with the AI agent that addresses your biggest operational challenge and add more over time. Because every agent runs on the same orchestration layer, new agents integrate with the existing ones without added setup.
Can your AI agents work with our existing systems?
Yes. Our AI agents are designed to integrate with your existing ERP, ecommerce platform, CRM, PIM, WMS, and other business applications. They enhance your current technology instead of replacing it.
How long does it take to deploy an AI agent?
Deployment timelines depend on the use case and business complexity, but most AI agents can be implemented within 4 to 6 weeks from discovery to go-live.
How much does an enterprise AI agent cost?
Cost depends on the agent, your existing systems, and how much customization your business rules require. We’ll give you a scoped estimate after the discovery call, once we know what you’re working with.
Is our business data secure?
Your data stays within your infrastructure if you choose self-hosted deployment. Access is scoped to what each agent needs, and read and write permissions are set separately for each system.
Will this work with our ERP?
What do we need internally to make this work?
Can AI agents make decisions without human approval?
Where does our data stay?
Can we see how an AI agent reached a recommendation?
What happens after deployment?
Find out which agent you should invest in first.
Bring your biggest operational challenge: stockouts, margin leaks, or a catalogue nobody trusts. In 30 minutes, we'll tell you which agent fits, roughly what it takes to build, and whether your data is ready. If it isn't, we'll say so.
